Mercurial > repos > deepakjadmin > mayatool3_test3

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.\"
.IX Title "SIMILARITYSEARCHINGFINGERPRINTS 1"
.TH SIMILARITYSEARCHINGFINGERPRINTS 1 "2015-03-29" "perl v5.14.2" "MayaChemTools"
.\" For nroff, turn off justification.  Always turn off hyphenation; it makes
.\" way too many mistakes in technical documents.
.if n .ad l
.nh
.SH "NAME"
SimilaritySearchingFingerprints.pl \- Perform similarity search using fingerprints strings data in SD, FP and CSV/TSV text file(s)
.SH "SYNOPSIS"
.IX Header "SYNOPSIS"
SimilaritySearchingFingerprints.pl ReferenceFPFile DatabaseFPFile
.PP
SimilaritySearchingFingerprints.pl [\fB\-\-alpha\fR \fInumber\fR] [\fB\-\-beta\fR \fInumber\fR]
[\fB\-b, \-\-BitVectorComparisonMode\fR \fITanimotoSimilarity | TverskySimilarity | ...\fR]
[\fB\-\-DatabaseColMode\fR \fIColNum | ColLabel\fR] [\fB\-\-DatabaseCompoundIDCol\fR \fIcol number | col name\fR]
[\fB\-\-DatabaseCompoundIDPrefix\fR \fItext\fR] [\fB\-\-DatabaseCompoundIDField\fR \fIDataFieldName\fR]
[\fB\-\-DatabaseCompoundIDMode\fR \fIDataField | MolName | LabelPrefix | MolNameOrLabelPrefix\fR]
[\fB\-\-DatabaseDataCols\fR \fI\*(L"DataColNum1, DataColNum2,... \*(R" | DataColLabel1, DataCoLabel2,... "\fR]
[\fB\-\-DatabaseDataColsMode\fR \fIAll | Specify | CompoundID\fR] [\fB\-\-DatabaseDataFields\fR \fI\*(L"FieldLabel1, FieldLabel2,... \*(R"\fR]
[\fB\-\-DatabaseDataFieldsMode\fR \fIAll | Common | Specify | CompoundID\fR]
[\fB\-\-DatabaseFingerprintsCol\fR \fIcol number | col name\fR] [\fB\-\-DatabaseFingerprintsField\fR \fIFieldLabel\fR]
[]\fB\-\-DistanceCutoff\fR \fInumber\fR] [\fB\-d, \-\-detail\fR \fIInfoLevel\fR] [\fB\-f, \-\-fast\fR]
[\fB\-\-FingerprintsMode\fR \fIAutoDetect | FingerprintsBitVectorString | FingerprintsVectorString\fR]
[\fB\-g, \-\-GroupFusionRule\fR \fIMax, Mean, Median, Min, Sum, Euclidean\fR] [\fB\-\-GroupFusionApplyCutoff\fR \fIYes | No\fR]
[\fB\-h, \-\-help\fR]  [\fB\-\-InDelim\fR \fIcomma | semicolon\fR] [\fB\-k, \-\-KNN\fR \fIall | number\fR]
[\fB\-m, \-\-mode\fR \fIIndividualReference | MultipleReferences\fR]
[\fB\-n, \-\-NumOfSimilarMolecules\fR \fInumber\fR] [\fB\-\-OutDelim\fR \fIcomma | tab | semicolon\fR]
[\fB\-\-output\fR \fI\s-1SD\s0 | text | both\fR] [\fB\-o, \-\-overwrite\fR]
[\fB\-p, \-\-PercentSimilarMolecules\fR \fInumber\fR] [\fB\-\-precision\fR \fInumber\fR] [\fB\-q, \-\-quote\fR \fIYes | No\fR]
[\fB\-\-ReferenceColMode\fR \fIColNum | ColLabel\fR] [\fB\-\-ReferenceCompoundIDCol\fR \fIcol number | col name\fR]
[\fB\-\-ReferenceCompoundIDPrefix\fR \fItext\fR] [\fB\-\-ReferenceCompoundIDField\fR \fIDataFieldName\fR]
[\fB\-\-ReferenceCompoundIDMode\fR \fIDataField | MolName | LabelPrefix | MolNameOrLabelPrefix\fR]
[\fB\-\-ReferenceFingerprintsCol\fR \fIcol number | col name\fR] [\fB\-\-ReferenceFingerprintsField\fR \fIFieldLabel\fR]
[\fB\-r, \-\-root\fR \fIRootName\fR] [\fB\-s, \-\-SearchMode\fR \fISimilaritySearch | DissimilaritySearch\fR]
[\fB\-\-SimilarCountMode\fR \fINumOfSimilar | PercentSimilar\fR] [\fB\-\-SimilarityCutoff\fR \fInumber\fR]
[\fB\-v, \-\-VectorComparisonMode\fR \fITanimotoSimilairy | ... | ManhattanDistance | ...\fR]
[\fB\-\-VectorComparisonFormulism\fR \fIAlgebraicForm | BinaryForm | SetTheoreticForm\fR]
[\fB\-w, \-\-WorkingDir\fR dirname] ReferenceFingerprintsFile DatabaseFingerprintsFile
.SH "DESCRIPTION"
.IX Header "DESCRIPTION"
Perform molecular similarity search [ Ref 94\-113 ] using fingerprint bit-vector or vector strings
data in \fI\s-1SD\s0, \s-1FP\s0, or \s-1CSV/TSV\s0 text\fR files corresponding to \fIReferenceFingerprintsFile\fR and
\&\fIDatabaseFingerprintsFile\fR, and generate \s-1SD\s0 and \s-1CSV/TSV\s0 text file(s) containing database
molecules which are similar to reference molecule(s). The reference molecules are also referred
to as query or seed molecules and database molecules as target molecules in the literature.
.PP
The current release of MayaChemTools supports two types of similarity search modes:
\&\fIIndividualReference or MultipleReferences\fR. For default value of \fIMultipleReferences\fR for \fB\-m, \-\-mode\fR
option, reference molecules are considered as a set and \fB\-g, \-\-GroupFusionRule\fR is used to calculate
similarity of a database molecule against reference molecules set. The group fusion rule is also
referred to as data fusion of consensus scoring in the literature. However, for \fIIndividualReference\fR
value of \fB\-m, \-\-mode\fR option, reference molecules are treated as individual molecules and each reference
molecule is compared against a database molecule by itself to identify similar molecules.
.PP
The molecular dissimilarity search can also be performed using \fIDissimilaritySearch\fR value for
\&\fB\-s, \-\-SearchMode\fR option. During dissimilarity search or usage of distance comparison coefficient
in similarity similarity search, the meaning of fingerprints comparison value is automatically reversed
as shown below:
.PP
.Vb 1
\&    SeachMode      ComparisonCoefficient  ResultsSort   ComparisonValues
\&
\&    Similarity     SimilarityCoefficient  Descending    Higher value imples
\&                                                        high similarity
\&    Similarity     DistanceCoefficient    Ascending     Lower value implies
\&                                                        high similarity
\&
\&    Dissimilarity  SimilarityCoefficient  Ascending     Lower value implies
\&                                                        high dissimilarity
\&    Dissimilarity  DistanceCoefficient    Descending    Higher value implies
\&                                                        high dissimilarity
.Ve
.PP
During \fIIndividualReference\fR value of  \fB\-m, \-\-Mode\fR option for similarity search, fingerprints bit-vector
or vector string of each reference molecule is compared with database molecules using specified
similarity or distance coefficients to identify most similar molecules for each reference molecule.
Based on value of \fB\-\-SimilarCountMode\fR, up to \fB\-\-n, \-\-NumOfSimilarMolecules\fR or \fB\-p,
\&\-\-PercentSimilarMolecules\fR at specified \fB\-\-SimilarityCutoff\fR or \fB\-\-DistanceCutoff\fR are
identified for each reference molecule.
.PP
During \fIMultipleReferences\fR value \fB\-m, \-\-mode\fR option for similarity search, all reference molecules
are considered as a set and \fB\-g, \-\-GroupFusionRule\fR is used to calculate similarity of a database
molecule against reference molecules set either using all reference molecules or number of k\-nearest
neighbors (k\-NN) to a database molecule specified using \fB\-k, \-\-kNN\fR. The fingerprints bit-vector
or vector string of each reference molecule in a set is compared with a database molecule using
a similarity or distance coefficient specified via \fB\-b, \-\-BitVectorComparisonMode\fR or \fB\-v,
\&\-\-VectorComparisonMode\fR. The reference molecules whose comparison values with a database
molecule fall outside specified \fB\-\-SimilarityCutoff\fR or \fB\-\-DistanceCutoff\fR are ignored during \fIYes\fR
value of \fB\-\-GroupFusionApplyCutoff\fR. The specified \fB\-g, \-\-GroupFusionRule\fR is applied to
\&\fB\-k, \-\-kNN\fR reference molecules to calculate final similarity value between a database molecule
and reference molecules set.
.PP
The input fingerprints \fI\s-1SD\s0, \s-1FP\s0, or Text (\s-1CSV/TSV\s0)\fR files for \fIReferenceFingerprintsFile\fR and
\&\fIDatabaseTextFile\fR must contain valid fingerprint bit-vector or vector strings data corresponding to
same type of fingerprints.
.PP
The valid fingerprints \fISDFile\fR extensions are \fI.sdf\fR and \fI.sd\fR. The valid fingerprints \fIFPFile\fR
extensions are \fI.fpf\fR and \fI.fp\fR. The valid fingerprints \fITextFile (\s-1CSV/TSV\s0)\fR extensions are
\&\fI.csv\fR and \fI.tsv\fR for comma/semicolon and tab delimited text files respectively. The \fB\-\-indelim\fR
option determines the format of \fITextFile\fR. Any file which doesn't correspond to the format indicated
by \fB\-\-indelim\fR option is ignored.
.PP
Example of \fI\s-1FP\s0\fR file containing fingerprints bit-vector string data:
.PP
.Vb 10
\&    #
\&    # Package = MayaChemTools 7.4
\&    # ReleaseDate = Oct 21, 2010
\&    #
\&    # TimeStamp =  Mon Mar 7 15:14:01 2011
\&    #
\&    # FingerprintsStringType = FingerprintsBitVector
\&    #
\&    # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
\&    # Size = 1024
\&    # BitStringFormat = HexadecimalString
\&    # BitsOrder = Ascending
\&    #
\&    Cmpd1 9c8460989ec8a49913991a6603130b0a19e8051c89184414953800cc21510...
\&    Cmpd2 000000249400840040100042011001001980410c000000001010088001120...
\&    ... ...
\&    ... ..
.Ve
.PP
Example of \fI\s-1FP\s0\fR file containing fingerprints vector string data:
.PP
.Vb 10
\&    #
\&    # Package = MayaChemTools 7.4
\&    # ReleaseDate = Oct 21, 2010
\&    #
\&    # TimeStamp =  Mon Mar 7 15:14:01 2011
\&    #
\&    # FingerprintsStringType = FingerprintsVector
\&    #
\&    # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
\&    # VectorStringFormat = IDsAndValuesString
\&    # VectorValuesType = NumericalValues
\&    #
\&    Cmpd1 338;C F N O C:C C:N C=O CC CF CN CO C:C:C C:C:N C:CC C:CF C:CN C:
\&    N:C C:NC CC:N CC=O CCC CCN CCO CNC NC=O O=CO C:C:C:C C:C:C:N C:C:CC...;
\&    33 1 2 5 21 2 2 12 1 3 3 20 2 10 2 2 1 2 2 2 8 2 5 1 1 1 19 2 8 2 2 2 2
\&    6 2 2 2 2 2 2 2 2 3 2 2 1 4 1 5 1 1 18 6 2 2 1 2 10 2 1 2 1 2 2 2 2 ...
\&    Cmpd2 103;C N O C=N C=O CC CN CO CC=O CCC CCN CCO CNC N=CN NC=O NCN O=C
\&    O C CC=O CCCC CCCN CCCO CCNC CNC=N CNC=O CNCN CCCC=O CCCCC CCCCN CC...;
\&    15 4 4 1 2 13 5 2 2 15 5 3 2 2 1 1 1 2 17 7 6 5 1 1 1 2 15 8 5 7 2 2 2 2
\&    1 2 1 1 3 15 7 6 8 3 4 4 3 2 2 1 2 3 14 2 4 7 4 4 4 4 1 1 1 2 1 1 1 ...
\&    ... ...
\&    ... ...
.Ve
.PP
Example of \fI\s-1SD\s0\fR file containing fingerprints bit-vector string data:
.PP
.Vb 10
\&    ... ...
\&    ... ...
\&    $$$$
\&    ... ...
\&    ... ...
\&    ... ...
\&    41 44  0  0  0  0  0  0  0  0999 V2000
\&     \-3.3652    1.4499    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0
\&    ... ...
\&    2  3  1  0  0  0  0
\&    ... ...
\&    M  END
\&    >  <CmpdID>
\&    Cmpd1
\&
\&    >  <PathLengthFingerprints>
\&    FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLengt
\&    h1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a49913991a66
\&    03130b0a19e8051c89184414953800cc2151082844a201042800130860308e8204d4028
\&    00831048940e44281c00060449a5000ac80c894114e006321264401600846c050164462
\&    08190410805000304a10205b0100e04c0038ba0fad0209c0ca8b1200012268b61c0026a
\&    aa0660a11014a011d46
\&
\&    $$$$
\&    ... ...
\&    ... ...
.Ve
.PP
Example of \s-1CSV\s0 \fITextFile\fR containing fingerprints bit-vector string data:
.PP
.Vb 7
\&    "CompoundID","PathLengthFingerprints"
\&    "Cmpd1","FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes
\&    :MinLength1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a4
\&    9913991a6603130b0a19e8051c89184414953800cc2151082844a20104280013086030
\&    8e8204d402800831048940e44281c00060449a5000ac80c894114e006321264401..."
\&    ... ...
\&    ... ...
.Ve
.PP
The current release of MayaChemTools supports the following types of fingerprint
bit-vector and vector strings:
.PP
.Vb 6
\&    FingerprintsVector;AtomNeighborhoods:AtomicInvariantsAtomTypes:MinRadi
\&    us0:MaxRadius2;41;AlphaNumericalValues;ValuesString;NR0\-C.X1.BO1.H3\-AT
\&    C1:NR1\-C.X3.BO3.H1\-ATC1:NR2\-C.X1.BO1.H3\-ATC1:NR2\-C.X3.BO4\-ATC1 NR0\-C.X
\&    1.BO1.H3\-ATC1:NR1\-C.X3.BO3.H1\-ATC1:NR2\-C.X1.BO1.H3\-ATC1:NR2\-C.X3.BO4\-A
\&    TC1 NR0\-C.X2.BO2.H2\-ATC1:NR1\-C.X2.BO2.H2\-ATC1:NR1\-C.X3.BO3.H1\-ATC1:NR2
\&    \-C.X2.BO2.H2\-ATC1:NR2\-N.X3.BO3\-ATC1:NR2\-O.X1.BO1.H1\-ATC1 NR0\-C.X2.B...
\&
\&    FingerprintsVector;AtomTypesCount:AtomicInvariantsAtomTypes:ArbitraryS
\&    ize;10;NumericalValues;IDsAndValuesString;C.X1.BO1.H3 C.X2.BO2.H2 C.X2
\&    .BO3.H1 C.X3.BO3.H1 C.X3.BO4 F.X1.BO1 N.X2.BO2.H1 N.X3.BO3 O.X1.BO1.H1
\&    O.X1.BO2;2 4 14 3 10 1 1 1 3 2
\&
\&    FingerprintsVector;AtomTypesCount:SLogPAtomTypes:ArbitrarySize;16;Nume
\&    ricalValues;IDsAndValuesString;C1 C10 C11 C14 C18 C20 C21 C22 C5 CS F
\&    N11 N4 O10 O2 O9;5 1 1 1 14 4 2 1 2 2 1 1 1 1 3 1
\&
\&    FingerprintsVector;AtomTypesCount:SLogPAtomTypes:FixedSize;67;OrderedN
\&    umericalValues;IDsAndValuesString;C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C
\&    12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 CS N1 N
\&    2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 N13 N14 NS O1 O2 O3 O4 O5 O6 O7 O8
\&    O9 O10 O11 O12 OS F Cl Br I Hal P S1 S2 S3 Me1 Me2;5 0 0 0 2 0 0 0 0 1
\&    1 0 0 1 0 0 0 14 0 4 2 1 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0...
\&
\&    FingerprintsVector;EStateIndicies:ArbitrarySize;11;NumericalValues;IDs
\&    AndValuesString;SaaCH SaasC SaasN SdO SdssC SsCH3 SsF SsOH SssCH2 SssN
\&    H SsssCH;24.778 4.387 1.993 25.023 \-1.435 3.975 14.006 29.759 \-0.073 3
\&    .024 \-2.270
\&
\&    FingerprintsVector;EStateIndicies:FixedSize;87;OrderedNumericalValues;
\&    ValuesString;0 0 0 0 0 0 0 3.975 0 \-0.073 0 0 24.778 \-2.270 0 0 \-1.435
\&    4.387 0 0 0 0 0 0 3.024 0 0 0 0 0 0 0 1.993 0 29.759 25.023 0 0 0 0 1
\&    4.006 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
\&    0 0 0 0 0 0 0 0 0 0 0 0 0 0
\&
\&    FingerprintsVector;ExtendedConnectivity:AtomicInvariantsAtomTypes:Radi
\&    us2;60;AlphaNumericalValues;ValuesString;73555770 333564680 352413391
\&    666191900 1001270906 1371674323 1481469939 1977749791 2006158649 21414
\&    08799 49532520 64643108 79385615 96062769 273726379 564565671 85514103
\&    5 906706094 988546669 1018231313 1032696425 1197507444 1331250018 1338
\&    532734 1455473691 1607485225 1609687129 1631614296 1670251330 17303...
\&
\&    FingerprintsVector;ExtendedConnectivityCount:AtomicInvariantsAtomTypes
\&    :Radius2;60;NumericalValues;IDsAndValuesString;73555770 333564680 3524
\&    13391 666191900 1001270906 1371674323 1481469939 1977749791 2006158649
\&    2141408799 49532520 64643108 79385615 96062769 273726379 564565671...;
\&    3 2 1 1 14 1 2 10 4 3 1 1 1 1 2 1 2 1 1 1 2 3 1 1 2 1 3 3 8 2 2 2 6 2
\&    1 2 1 1 2 1 1 1 2 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1
\&
\&    FingerprintsBitVector;ExtendedConnectivityBits:AtomicInvariantsAtomTyp
\&    es:Radius2;1024;BinaryString;Ascending;0000000000000000000000000000100
\&    0000000001010000000110000011000000000000100000000000000000000000100001
\&    1000000110000000000000000000000000010011000000000000000000000000010000
\&    0000000000000000000000000010000000000000000001000000000000000000000000
\&    0000000000010000100001000000000000101000000000000000100000000000000...
\&
\&    FingerprintsVector;ExtendedConnectivity:FunctionalClassAtomTypes:Radiu
\&    s2;57;AlphaNumericalValues;ValuesString;24769214 508787397 850393286 8
\&    62102353 981185303 1231636850 1649386610 1941540674 263599683 32920567
\&    1 571109041 639579325 683993318 723853089 810600886 885767127 90326012
\&    7 958841485 981022393 1126908698 1152248391 1317567065 1421489994 1455
\&    632544 1557272891 1826413669 1983319256 2015750777 2029559552 20404...
\&
\&    FingerprintsVector;ExtendedConnectivity:EStateAtomTypes:Radius2;62;Alp
\&    haNumericalValues;ValuesString;25189973 528584866 662581668 671034184
\&    926543080 1347067490 1738510057 1759600920 2034425745 2097234755 21450
\&    44754 96779665 180364292 341712110 345278822 386540408 387387308 50430
\&    1706 617094135 771528807 957666640 997798220 1158349170 1291258082 134
\&    1138533 1395329837 1420277211 1479584608 1486476397 1487556246 1566...
\&
\&    FingerprintsBitVector;MACCSKeyBits;166;BinaryString;Ascending;00000000
\&    0000000000000000000000000000000001001000010010000000010010000000011100
\&    0100101010111100011011000100110110000011011110100110111111111111011111
\&    11111111111110111000
\&
\&    FingerprintsBitVector;MACCSKeyBits;322;BinaryString;Ascending;11101011
\&    1110011111100101111111000111101100110000000000000011100010000000000000
\&    0000000000000000000000000000000000000000000000101000000000000000000000
\&    0000000000000000000000000000000000000000000000000000000000000000000000
\&    0000000000000000000000000000000000000011000000000000000000000000000000
\&    0000000000000000000000000000000000000000
\&
\&    FingerprintsVector;MACCSKeyCount;166;OrderedNumericalValues;ValuesStri
\&    ng;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
\&    0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0
\&    0 0 0 0 1 1 8 0 0 0 1 0 0 1 0 1 0 1 0 3 1 3 1 0 0 0 1 2 0 11 1 0 0 0
\&    5 0 0 1 2 0 1 1 0 0 0 0 0 1 1 0 1 1 1 1 0 4 0 0 1 1 0 4 6 1 1 1 2 1 1
\&    3 5 2 2 0 5 3 5 1 1 2 5 1 2 1 2 4 8 3 5 5 2 2 0 3 5 4 1
\&
\&    FingerprintsVector;MACCSKeyCount;322;OrderedNumericalValues;ValuesStri
\&    ng;14 8 2 0 2 0 4 4 2 1 4 0 0 2 5 10 5 2 1 0 0 2 0 5 13 3 28 5 5 3 0 0
\&    0 4 2 1 1 0 1 1 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 5 3 0 0 0 1 0
\&    0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
\&    0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 2 0 0 0 0 0 0 0 0 0
\&    0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ...
\&
\&    FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLeng
\&    th1:MaxLength8;1024;BinaryString;Ascending;001000010011010101011000110
\&    0100010101011000101001011100110001000010001001101000001001001001001000
\&    0010110100000111001001000001001010100100100000000011000000101001011100
\&    0010000001000101010100000100111100110111011011011000000010110111001101
\&    0101100011000000010001000011000010100011101100001000001000100000000...
\&
\&    FingerprintsVector;PathLengthCount:AtomicInvariantsAtomTypes:MinLength
\&    1:MaxLength8;432;NumericalValues;IDsAndValuesPairsString;C.X1.BO1.H3 2
\&    C.X2.BO2.H2 4 C.X2.BO3.H1 14 C.X3.BO3.H1 3 C.X3.BO4 10 F.X1.BO1 1 N.X
\&    2.BO2.H1 1 N.X3.BO3 1 O.X1.BO1.H1 3 O.X1.BO2 2 C.X1.BO1.H3C.X3.BO3.H1
\&    2 C.X2.BO2.H2C.X2.BO2.H2 1 C.X2.BO2.H2C.X3.BO3.H1 4 C.X2.BO2.H2C.X3.BO
\&    4 1 C.X2.BO2.H2N.X3.BO3 1 C.X2.BO3.H1:C.X2.BO3.H1 10 C.X2.BO3.H1:C....
\&
\&    FingerprintsVector;PathLengthCount:MMFF94AtomTypes:MinLength1:MaxLengt
\&    h8;463;NumericalValues;IDsAndValuesPairsString;C5A 2 C5B 2 C=ON 1 CB 1
\&    8 COO 1 CR 9 F 1 N5 1 NC=O 1 O=CN 1 O=CO 1 OC=O 1 OR 2 C5A:C5B 2 C5A:N
\&    5 2 C5ACB 1 C5ACR 1 C5B:C5B 1 C5BC=ON 1 C5BCB 1 C=ON=O=CN 1 C=ONNC=O 1
\&    CB:CB 18 CBF 1 CBNC=O 1 COO=O=CO 1 COOCR 1 COOOC=O 1 CRCR 7 CRN5 1 CR
\&    OR 2 C5A:C5B:C5B 2 C5A:C5BC=ON 1 C5A:C5BCB 1 C5A:N5:C5A 1 C5A:N5CR ...
\&
\&    FingerprintsVector;TopologicalAtomPairs:AtomicInvariantsAtomTypes:MinD
\&    istance1:MaxDistance10;223;NumericalValues;IDsAndValuesString;C.X1.BO1
\&    .H3\-D1\-C.X3.BO3.H1 C.X2.BO2.H2\-D1\-C.X2.BO2.H2 C.X2.BO2.H2\-D1\-C.X3.BO3.
\&    H1 C.X2.BO2.H2\-D1\-C.X3.BO4 C.X2.BO2.H2\-D1\-N.X3.BO3 C.X2.BO3.H1\-D1\-...;
\&    2 1 4 1 1 10 8 1 2 6 1 2 2 1 2 1 2 2 1 2 1 5 1 10 12 2 2 1 2 1 9 1 3 1
\&    1 1 2 2 1 3 6 1 6 14 2 2 2 3 1 3 1 8 2 2 1 3 2 6 1 2 2 5 1 3 1 23 1...
\&
\&    FingerprintsVector;TopologicalAtomPairs:FunctionalClassAtomTypes:MinDi
\&    stance1:MaxDistance10;144;NumericalValues;IDsAndValuesString;Ar\-D1\-Ar
\&    Ar\-D1\-Ar.HBA Ar\-D1\-HBD Ar\-D1\-Hal Ar\-D1\-None Ar.HBA\-D1\-None HBA\-D1\-NI H
\&    BA\-D1\-None HBA.HBD\-D1\-NI HBA.HBD\-D1\-None HBD\-D1\-None NI\-D1\-None No...;
\&    23 2 1 1 2 1 1 1 1 2 1 1 7 28 3 1 3 2 8 2 1 1 1 5 1 5 24 3 3 4 2 13 4
\&    1 1 4 1 5 22 4 4 3 1 19 1 1 1 1 1 2 2 3 1 1 8 25 4 5 2 3 1 26 1 4 1 ...
\&
\&    FingerprintsVector;TopologicalAtomTorsions:AtomicInvariantsAtomTypes;3
\&    3;NumericalValues;IDsAndValuesString;C.X1.BO1.H3\-C.X3.BO3.H1\-C.X3.BO4\-
\&    C.X3.BO4 C.X1.BO1.H3\-C.X3.BO3.H1\-C.X3.BO4\-N.X3.BO3 C.X2.BO2.H2\-C.X2.BO
\&    2.H2\-C.X3.BO3.H1\-C.X2.BO2.H2 C.X2.BO2.H2\-C.X2.BO2.H2\-C.X3.BO3.H1\-O...;
\&    2 2 1 1 2 2 1 1 3 4 4 8 4 2 2 6 2 2 1 2 1 1 2 1 1 2 6 2 4 2 1 3 1
\&
\&    FingerprintsVector;TopologicalAtomTorsions:EStateAtomTypes;36;Numerica
\&    lValues;IDsAndValuesString;aaCH\-aaCH\-aaCH\-aaCH aaCH\-aaCH\-aaCH\-aasC aaC
\&    H\-aaCH\-aasC\-aaCH aaCH\-aaCH\-aasC\-aasC aaCH\-aaCH\-aasC\-sF aaCH\-aaCH\-aasC\-
\&    ssNH aaCH\-aasC\-aasC\-aasC aaCH\-aasC\-aasC\-aasN aaCH\-aasC\-ssNH\-dssC a...;
\&    4 4 8 4 2 2 6 2 2 2 4 3 2 1 3 3 2 2 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2
\&
\&    FingerprintsVector;TopologicalAtomTriplets:AtomicInvariantsAtomTypes:M
\&    inDistance1:MaxDistance10;3096;NumericalValues;IDsAndValuesString;C.X1
\&    .BO1.H3\-D1\-C.X1.BO1.H3\-D1\-C.X3.BO3.H1\-D2 C.X1.BO1.H3\-D1\-C.X2.BO2.H2\-D1
\&    0\-C.X3.BO4\-D9 C.X1.BO1.H3\-D1\-C.X2.BO2.H2\-D3\-N.X3.BO3\-D4 C.X1.BO1.H3\-D1
\&    \-C.X2.BO2.H2\-D4\-C.X2.BO2.H2\-D5 C.X1.BO1.H3\-D1\-C.X2.BO2.H2\-D6\-C.X3....;
\&    1 2 2 2 2 2 2 2 8 8 4 8 4 4 2 2 2 2 4 2 2 2 4 2 2 2 2 1 2 2 4 4 4 2 2
\&    2 4 4 4 8 4 4 2 4 4 4 2 4 4 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 8...
\&
\&    FingerprintsVector;TopologicalAtomTriplets:SYBYLAtomTypes:MinDistance1
\&    :MaxDistance10;2332;NumericalValues;IDsAndValuesString;C.2\-D1\-C.2\-D9\-C
\&    .3\-D10 C.2\-D1\-C.2\-D9\-C.ar\-D10 C.2\-D1\-C.3\-D1\-C.3\-D2 C.2\-D1\-C.3\-D10\-C.3\-
\&    D9 C.2\-D1\-C.3\-D2\-C.3\-D3 C.2\-D1\-C.3\-D2\-C.ar\-D3 C.2\-D1\-C.3\-D3\-C.3\-D4 C.2
\&    \-D1\-C.3\-D3\-N.ar\-D4 C.2\-D1\-C.3\-D3\-O.3\-D2 C.2\-D1\-C.3\-D4\-C.3\-D5 C.2\-D1\-C.
\&    3\-D5\-C.3\-D6 C.2\-D1\-C.3\-D5\-O.3\-D4 C.2\-D1\-C.3\-D6\-C.3\-D7 C.2\-D1\-C.3\-D7...
\&
\&    FingerprintsVector;TopologicalPharmacophoreAtomPairs:ArbitrarySize:Min
\&    Distance1:MaxDistance10;54;NumericalValues;IDsAndValuesString;H\-D1\-H H
\&    \-D1\-NI HBA\-D1\-NI HBD\-D1\-NI H\-D2\-H H\-D2\-HBA H\-D2\-HBD HBA\-D2\-HBA HBA\-D2\-
\&    HBD H\-D3\-H H\-D3\-HBA H\-D3\-HBD H\-D3\-NI HBA\-D3\-NI HBD\-D3\-NI H\-D4\-H H\-D4\-H
\&    BA H\-D4\-HBD HBA\-D4\-HBA HBA\-D4\-HBD HBD\-D4\-HBD H\-D5\-H H\-D5\-HBA H\-D5\-...;
\&    18 1 2 1 22 12 8 1 2 18 6 3 1 1 1 22 13 6 5 7 2 28 9 5 1 1 1 36 16 10
\&    3 4 1 37 10 8 1 35 10 9 3 3 1 28 7 7 4 18 16 12 5 1 2 1
\&
\&    FingerprintsVector;TopologicalPharmacophoreAtomPairs:FixedSize:MinDist
\&    ance1:MaxDistance10;150;OrderedNumericalValues;ValuesString;18 0 0 1 0
\&    0 0 2 0 0 1 0 0 0 0 22 12 8 0 0 1 2 0 0 0 0 0 0 0 0 18 6 3 1 0 0 0 1
\&    0 0 1 0 0 0 0 22 13 6 0 0 5 7 0 0 2 0 0 0 0 0 28 9 5 1 0 0 0 1 0 0 1 0
\&    0 0 0 36 16 10 0 0 3 4 0 0 1 0 0 0 0 0 37 10 8 0 0 0 0 1 0 0 0 0 0 0
\&    0 35 10 9 0 0 3 3 0 0 1 0 0 0 0 0 28 7 7 4 0 0 0 0 0 0 0 0 0 0 0 18...
\&
\&    FingerprintsVector;TopologicalPharmacophoreAtomTriplets:ArbitrarySize:
\&    MinDistance1:MaxDistance10;696;NumericalValues;IDsAndValuesString;Ar1\-
\&    Ar1\-Ar1 Ar1\-Ar1\-H1 Ar1\-Ar1\-HBA1 Ar1\-Ar1\-HBD1 Ar1\-H1\-H1 Ar1\-H1\-HBA1 Ar1
\&    \-H1\-HBD1 Ar1\-HBA1\-HBD1 H1\-H1\-H1 H1\-H1\-HBA1 H1\-H1\-HBD1 H1\-HBA1\-HBA1 H1\-
\&    HBA1\-HBD1 H1\-HBA1\-NI1 H1\-HBD1\-NI1 HBA1\-HBA1\-NI1 HBA1\-HBD1\-NI1 Ar1\-...;
\&    46 106 8 3 83 11 4 1 21 5 3 1 2 2 1 1 1 100 101 18 11 145 132 26 14 23
\&    28 3 3 5 4 61 45 10 4 16 20 7 5 1 3 4 5 3 1 1 1 1 5 4 2 1 2 2 2 1 1 1
\&    119 123 24 15 185 202 41 25 22 17 3 5 85 95 18 11 23 17 3 1 1 6 4 ...
\&
\&    FingerprintsVector;TopologicalPharmacophoreAtomTriplets:FixedSize:MinD
\&    istance1:MaxDistance10;2692;OrderedNumericalValues;ValuesString;46 106
\&    8 3 0 0 83 11 4 0 0 0 1 0 0 0 0 0 0 0 0 21 5 3 0 0 1 2 2 0 0 1 0 0 0
\&    0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 101 18 11 0 0 145 132 26
\&    14 0 0 23 28 3 3 0 0 5 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 61 45 10 4 0
\&    0 16 20 7 5 1 0 3 4 5 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 5 ...
.Ve
.SH "OPTIONS"
.IX Header "OPTIONS"
.IP "\fB\-\-alpha\fR \fInumber\fR" 4
.IX Item "--alpha number"
Value of alpha parameter for calculating \fITversky\fR similarity coefficient specified for
\&\fB\-b, \-\-BitVectorComparisonMode\fR option. It corresponds to weights assigned for bits set
to \*(L"1\*(R" in a pair of fingerprint bit-vectors during the calculation of similarity coefficient. Possible
values: \fI0 to 1\fR. Default value: <0.5>.
.IP "\fB\-\-beta\fR \fInumber\fR" 4
.IX Item "--beta number"
Value of beta parameter for calculating \fIWeightedTanimoto\fR and  \fIWeightedTversky\fR
similarity coefficients specified for \fB\-b, \-\-BitVectorComparisonMode\fR option. It is used to
weight the contributions of bits set to \*(L"0\*(R" during the calculation of similarity coefficients. Possible
values: \fI0 to 1\fR. Default value of <1> makes \fIWeightedTanimoto\fR and  \fIWeightedTversky\fR
equivalent to \fITanimoto\fR and  \fITversky\fR.
.IP "\fB\-b, \-\-BitVectorComparisonMode\fR \fITanimotoSimilarity | TverskySimilarity | ...\fR" 4
.IX Item "-b, --BitVectorComparisonMode TanimotoSimilarity | TverskySimilarity | ..."
Specify what similarity coefficient to use for calculating similarity between fingerprints bit-vector
string data values in \fIReferenceFingerprintsFile\fR and \fIDatabaseFingerprintsFile\fR during similarity
search. Possible values: \fITanimotoSimilarity | TverskySimilarity | ...\fR. Default: \fITanimotoSimilarity\fR
.Sp
The current release supports the following similarity coefficients: \fIBaroniUrbaniSimilarity, BuserSimilarity,
CosineSimilarity, DiceSimilarity, DennisSimilarity, ForbesSimilarity, FossumSimilarity, HamannSimilarity, JacardSimilarity,
Kulczynski1Similarity, Kulczynski2Similarity, MatchingSimilarity, McConnaugheySimilarity, OchiaiSimilarity,
PearsonSimilarity, RogersTanimotoSimilarity, RussellRaoSimilarity, SimpsonSimilarity, SkoalSneath1Similarity,
SkoalSneath2Similarity, SkoalSneath3Similarity, TanimotoSimilarity, TverskySimilarity, YuleSimilarity,
WeightedTanimotoSimilarity, WeightedTverskySimilarity\fR. These similarity coefficients are described below.
.Sp
For two fingerprint bit-vectors A and B of same size, let:
.Sp
.Vb 4
\&    Na = Number of bits set to "1" in A
\&    Nb = Number of bits set to "1" in B
\&    Nc = Number of bits set to "1" in both A and B
\&    Nd = Number of bits set to "0" in both A and B
\&
\&    Nt = Number of bits set to "1" or "0" in A or B (Size of A or B)
\&    Nt = Na + Nb \- Nc + Nd
\&
\&    Na \- Nc = Number of bits set to "1" in A but not in B
\&    Nb \- Nc = Number of bits set to "1" in B but not in A
.Ve
.Sp
Then, various similarity coefficients [ Ref. 40 \- 42 ] for a pair of bit-vectors A and B are
defined as follows:
.Sp
\&\fIBaroniUrbaniSimilarity\fR: ( \s-1SQRT\s0( Nc * Nd ) + Nc ) / (  \s-1SQRT\s0 ( Nc * Nd ) + Nc + ( Na \- Nc )  + ( Nb \- Nc ) ) ( same as Buser )
.Sp
\&\fIBuserSimilarity\fR: ( \s-1SQRT\s0 ( Nc * Nd ) + Nc ) / (  \s-1SQRT\s0 ( Nc * Nd ) + Nc + ( Na \- Nc )  + ( Nb \- Nc ) ) ( same as BaroniUrbani )
.Sp
\&\fICosineSimilarity\fR: Nc / \s-1SQRT\s0 ( Na * Nb ) (same as Ochiai)
.Sp
\&\fIDiceSimilarity\fR: (2 * Nc) / ( Na + Nb )
.Sp
\&\fIDennisSimilarity\fR: ( Nc * Nd \- ( ( Na \- Nc ) * ( Nb \- Nc ) ) ) / \s-1SQRT\s0 ( Nt * Na * Nb)
.Sp
\&\fIForbesSimilarity\fR: ( Nt * Nc ) / ( Na * Nb )
.Sp
\&\fIFossumSimilarity\fR: ( Nt * ( ( Nc \- 1/2 ) ** 2 ) / ( Na * Nb )
.Sp
\&\fIHamannSimilarity\fR: ( ( Nc + Nd ) \- ( Na \- Nc ) \- ( Nb \- Nc ) ) / Nt
.Sp
\&\fIJaccardSimilarity\fR: Nc /  ( ( Na \- Nc) + ( Nb \- Nc ) + Nc ) = Nc / ( Na + Nb \- Nc ) (same as Tanimoto)
.Sp
\&\fIKulczynski1Similarity\fR: Nc / ( ( Na \- Nc ) + ( Nb \- Nc) ) = Nc / ( Na + Nb \- 2Nc )
.Sp
\&\fIKulczynski2Similarity\fR: ( ( Nc / 2 ) * ( 2 * Nc + ( Na \- Nc ) + ( Nb \- Nc) ) ) / ( ( Nc + ( Na \- Nc ) ) * ( Nc + ( Nb \- Nc ) ) ) = 0.5 * ( Nc / Na + Nc / Nb )
.Sp
\&\fIMatchingSimilarity\fR: ( Nc + Nd ) / Nt
.Sp
\&\fIMcConnaugheySimilarity\fR: ( Nc ** 2 \- ( Na \- Nc ) * ( Nb \- Nc) ) / (  Na * Nb )
.Sp
\&\fIOchiaiSimilarity\fR: Nc / \s-1SQRT\s0 ( Na * Nb ) (same as Cosine)
.Sp
\&\fIPearsonSimilarity\fR: ( ( Nc * Nd ) \- ( ( Na \- Nc ) * ( Nb \- Nc ) ) / \s-1SQRT\s0 ( Na * Nb * (  Na \- Nc + Nd ) * ( Nb \- Nc + Nd ) )
.Sp
\&\fIRogersTanimotoSimilarity\fR: ( Nc + Nd ) / ( ( Na \- Nc)  + ( Nb  \- Nc) + Nt) = ( Nc + Nd ) / ( Na  + Nb  \- 2Nc + Nt)
.Sp
\&\fIRussellRaoSimilarity\fR: Nc / Nt
.Sp
\&\fISimpsonSimilarity\fR: Nc / \s-1MIN\s0 ( Na, Nb)
.Sp
\&\fISkoalSneath1Similarity\fR: Nc / ( Nc + 2 * ( Na \- Nc)  + 2 * ( Nb \- Nc) ) = Nc / ( 2 * Na + 2 * Nb \- 3 * Nc )
.Sp
\&\fISkoalSneath2Similarity\fR: ( 2 * Nc + 2 * Nd ) / ( Nc + Nd + Nt )
.Sp
\&\fISkoalSneath3Similarity\fR: ( Nc + Nd ) / ( ( Na \- Nc ) + ( Nb \- Nc ) ) = ( Nc + Nd ) / ( Na + Nb \- 2 * Nc  )
.Sp
\&\fITanimotoSimilarity\fR: Nc /  ( ( Na \- Nc) + ( Nb \- Nc ) + Nc ) = Nc / ( Na + Nb \- Nc ) (same as Jaccard)
.Sp
\&\fITverskySimilarity\fR: Nc / ( alpha * ( Na \- Nc ) + ( 1 \- alpha) * ( Nb \- Nc) + Nc ) = Nc / ( alpha * ( Na \- Nb )  + Nb)
.Sp
\&\fIYuleSimilarity\fR: ( ( Nc * Nd ) \- ( ( Na \- Nc ) * ( Nb \- Nc ) ) ) / ( ( Nc * Nd ) + ( ( Na \- Nc ) * ( Nb \- Nc ) )  )
.Sp
Values of Tanimoto/Jaccard and Tversky coefficients are dependent on only those bit which
are set to \*(L"1\*(R" in both A and B. In order to take into account all bit positions, modified versions
of Tanimoto [ Ref. 42 ] and Tversky [  Ref. 43 ] have been developed.
.Sp
Let:
.Sp
.Vb 3
\&    Na\*(Aq = Number of bits set to "0" in A
\&    Nb\*(Aq = Number of bits set to "0" in B
\&    Nc\*(Aq = Number of bits set to "0" in both A and B
.Ve
.Sp
Tanimoto': Nc' /  ( ( Na' \- Nc') + ( Nb' \- Nc' ) + Nc' ) = Nc' / ( Na' + Nb' \- Nc' )
.Sp
Tversky': Nc' / ( alpha * ( Na' \- Nc' ) + ( 1 \- alpha) * ( Nb' \- Nc' ) + Nc' ) = Nc' / ( alpha * ( Na' \- Nb' )  + Nb')
.Sp
Then:
.Sp
\&\fIWeightedTanimotoSimilarity\fR = beta * Tanimoto + (1 \- beta) * Tanimoto'
.Sp
\&\fIWeightedTverskySimilarity\fR = beta * Tversky + (1 \- beta) * Tversky'
.IP "\fB\-\-DatabaseColMode\fR \fIColNum | ColLabel\fR" 4
.IX Item "--DatabaseColMode ColNum | ColLabel"
Specify how columns are identified in database fingerprints \fITextFile\fR: using column
number or column label. Possible values: \fIColNum or ColLabel\fR. Default value: \fIColNum\fR.
.IP "\fB\-\-DatabaseCompoundIDCol\fR \fIcol number | col name\fR" 4
.IX Item "--DatabaseCompoundIDCol col number | col name"
This value is \fB\-\-DatabaseColMode\fR mode specific. It specifies column to use for retrieving compound
\&\s-1ID\s0 from database fingerprints \fITextFile\fR during similarity and dissimilarity search for output \s-1SD\s0 and
\&\s-1CSV/TSV\s0 text files. Possible values: \fIcol number or col label\fR. Default value: \fIfirst column containing
the word compoundID in its column label or sequentially generated IDs\fR.
.Sp
This is only used for \fICompoundID\fR value of \fB\-\-DatabaseDataColsMode\fR option.
.IP "\fB\-\-DatabaseCompoundIDPrefix\fR \fItext\fR" 4
.IX Item "--DatabaseCompoundIDPrefix text"
Specify compound \s-1ID\s0 prefix to use during sequential generation of compound IDs for database fingerprints
\&\fISDFile\fR and \fITextFile\fR. Default value: \fICmpd\fR. The default value generates compound IDs which look
like Cmpd<Number>.
.Sp
For database fingerprints \fISDFile\fR, this value is only used during \fILabelPrefix | MolNameOrLabelPrefix\fR
values of \fB\-\-DatabaseCompoundIDMode\fR option; otherwise, it's ignored.
.Sp
Examples for \fILabelPrefix\fR or \fIMolNameOrLabelPrefix\fR value of \fB\-\-DatabaseCompoundIDMode\fR:
.Sp
.Vb 1
\&    Compound
.Ve
.Sp
The values specified above generates compound IDs which correspond to Compound<Number>
instead of default value of Cmpd<Number>.
.IP "\fB\-\-DatabaseCompoundIDField\fR \fIDataFieldName\fR" 4
.IX Item "--DatabaseCompoundIDField DataFieldName"
Specify database fingerprints \fISDFile\fR datafield label for generating compound IDs. This value is
only used during \fIDataField\fR value of \fB\-\-DatabaseCompoundIDMode\fR option.
.Sp
Examples for \fIDataField\fR value of \fB\-\-DatabaseCompoundIDMode\fR:
.Sp
.Vb 2
\&    MolID
\&    ExtReg
.Ve
.IP "\fB\-\-DatabaseCompoundIDMode\fR \fIDataField | MolName | LabelPrefix | MolNameOrLabelPrefix\fR" 4
.IX Item "--DatabaseCompoundIDMode DataField | MolName | LabelPrefix | MolNameOrLabelPrefix"
Specify how to generate compound IDs from database fingerprints \fISDFile\fR during similarity and
dissimilarity search for output \s-1SD\s0 and \s-1CSV/TSV\s0 text files: use a \fISDFile\fR datafield value; use
molname line from \fISDFile\fR; generate a sequential \s-1ID\s0 with specific prefix; use combination of both
MolName and LabelPrefix with usage of LabelPrefix values for empty molname lines.
.Sp
Possible values: \fIDataField | MolName | LabelPrefix | MolNameOrLabelPrefix\fR.
Default: \fILabelPrefix\fR.
.Sp
For \fIMolNameAndLabelPrefix\fR value of \fB\-\-DatabaseCompoundIDMode\fR, molname line in \fISDFile\fR takes
precedence over sequential compound IDs generated using \fILabelPrefix\fR and only empty molname
values are replaced with sequential compound IDs.
.Sp
This is only used for \fICompoundID\fR value of \fB\-\-DatabaseDataFieldsMode\fR option.
.ie n .IP "\fB\-\-DatabaseDataCols\fR \fI""DataColNum1,DataColNum2,... "" | DataColLabel1,DataCoLabel2,... ""\fR" 4
.el .IP "\fB\-\-DatabaseDataCols\fR \fI``DataColNum1,DataColNum2,... '' | DataColLabel1,DataCoLabel2,... ""\fR" 4
.IX Item "--DatabaseDataCols DataColNum1,DataColNum2,...  | DataColLabel1,DataCoLabel2,... """
This value is \fB\-\-DatabaseColMode\fR mode specific. It is a comma delimited list of database fingerprints
\&\fITextFile\fR data column numbers or labels to extract and write to \s-1SD\s0 and \s-1CSV/TSV\s0 text files along with
other information for \fI\s-1SD\s0 | text | both\fR values of \fB\-\-output\fR option.
.Sp
This is only used for \fISpecify\fR value of \fB\-\-DatabaseDataColsMode\fR option.
.Sp
Examples:
.Sp
.Vb 2
\&    1,2,3
\&    CompoundName,MolWt
.Ve
.IP "\fB\-\-DatabaseDataColsMode\fR \fIAll | Specify | CompoundID\fR" 4
.IX Item "--DatabaseDataColsMode All | Specify | CompoundID"
Specify how data columns from database fingerprints \fITextFile\fR are transferred to output \s-1SD\s0 and
\&\s-1CSV/TSV\s0 text files along with other information for \fI\s-1SD\s0 | text | both\fR values of \fB\-\-output\fR option:
transfer all data columns; extract specified data columns; generate a compound \s-1ID\s0 database compound
prefix. Possible values: \fIAll | Specify | CompoundID\fR. Default value: \fICompoundID\fR.
.ie n .IP "\fB\-\-DatabaseDataFields\fR \fI""FieldLabel1,FieldLabel2,... ""\fR" 4
.el .IP "\fB\-\-DatabaseDataFields\fR \fI``FieldLabel1,FieldLabel2,... ''\fR" 4
.IX Item "--DatabaseDataFields FieldLabel1,FieldLabel2,... "
Comma delimited list of database fingerprints \fISDFile\fR data fields to extract and write to \s-1SD\s0
and \s-1CSV/TSV\s0 text files along with other information for \fI\s-1SD\s0 | text | both\fR values of
\&\fB\-\-output\fR option.
.Sp
This is only used for \fISpecify\fR value of \fB\-\-DatabaseDataFieldsMode\fR option.
.Sp
Examples:
.Sp
.Vb 2
\&    Extreg
\&    MolID,CompoundName
.Ve
.IP "\fB\-\-DatabaseDataFieldsMode\fR \fIAll | Common | Specify | CompoundID\fR" 4
.IX Item "--DatabaseDataFieldsMode All | Common | Specify | CompoundID"
Specify how data fields from database fingerprints \fISDFile\fR are transferred to output \s-1SD\s0 and
\&\s-1CSV/TSV\s0 text files along with other information for \fI\s-1SD\s0 | text | both\fR values of \fB\-\-output\fR
option: transfer all \s-1SD\s0 data field; transfer \s-1SD\s0 data files common to all compounds; extract
specified data fields; generate a compound \s-1ID\s0 using molname line, a compound prefix, or a
combination of both. Possible values: \fIAll | Common | specify | CompoundID\fR. Default value:
\&\fICompoundID\fR.
.IP "\fB\-\-DatabaseFingerprintsCol\fR \fIcol number | col name\fR" 4
.IX Item "--DatabaseFingerprintsCol col number | col name"
This value is \fB\-\-DatabaseColMode\fR specific. It specifies fingerprints column to use during similarity
and dissimilarity search for database fingerprints \fITextFile\fR. Possible values: \fIcol number or col label\fR.
Default value: \fIfirst column containing the word Fingerprints in its column label\fR.
.IP "\fB\-\-DatabaseFingerprintsField\fR \fIFieldLabel\fR" 4
.IX Item "--DatabaseFingerprintsField FieldLabel"
Fingerprints field label to use during similarity and dissimilarity search for database fingerprints \fISDFile\fR.
Default value: \fIfirst data field label containing the word Fingerprints in its label\fR
.IP "\fB\-\-DistanceCutoff\fR \fInumber\fR" 4
.IX Item "--DistanceCutoff number"
Distance cutoff value to use during comparison of distance value between a pair of database
and reference molecule calculated by distance comparison methods for fingerprints vector
string data values. Possible values: \fIAny valid number\fR. Default value: \fI10\fR.
.Sp
The comparison value between a pair of database and reference molecule must meet the cutoff
criterion as shown below:
.Sp
.Vb 1
\&    SeachMode      CutoffCriterion  ComparisonValues
\&
\&    Similarity     <=               Lower value implies high similarity
\&    Dissimilarity  >=               Higher value implies high dissimilarity
.Ve
.Sp
This option is only used during distance coefficients values of \fB\-v, \-\-VectorComparisonMode\fR
option.
.Sp
This option is ignored during \fINo\fR value of \fB\-\-GroupFusionApplyCutoff\fR for \fIMultipleReferences\fR
\&\fB\-m, \-\-mode\fR.
.IP "\fB\-d, \-\-detail\fR \fIInfoLevel\fR" 4
.IX Item "-d, --detail InfoLevel"
Level of information to print about lines being ignored. Default: \fI1\fR. Possible values:
\&\fI1, 2 or 3\fR.
.IP "\fB\-f, \-\-fast\fR" 4
.IX Item "-f, --fast"
In this mode, fingerprints columns specified using \fB\-\-FingerprintsCol\fR for reference and database
fingerprints \fITextFile(s)\fR, and \fB\-\-FingerprintsField\fR for reference and database fingerprints \fISDFile(s)\fR
are assumed to contain valid fingerprints data and no checking is performed before performing similarity
and dissimilarity search. By default, fingerprints data is validated before computing pairwise similarity and
distance coefficients.
.IP "\fB\-\-FingerprintsMode\fR \fIAutoDetect | FingerprintsBitVectorString | FingerprintsVectorString\fR" 4
.IX Item "--FingerprintsMode AutoDetect | FingerprintsBitVectorString | FingerprintsVectorString"
Format of fingerprint strings data in reference and database fingerprints \fI\s-1SD\s0, \s-1FP\s0, or Text (\s-1CSV/TSV\s0)\fR
files: automatically detect format of fingerprints string created by MayaChemTools fingerprints
generation scripts or explicitly specify its format. Possible values: \fIAutoDetect | FingerprintsBitVectorString |
FingerprintsVectorString\fR. Default value: \fIAutoDetect\fR.
.IP "\fB\-g, \-\-GroupFusionRule\fR \fIMax, Min, Mean, Median, Sum, Euclidean\fR" 4
.IX Item "-g, --GroupFusionRule Max, Min, Mean, Median, Sum, Euclidean"
Specify what group fusion [ Ref 94\-97, Ref 100, Ref 105 ] rule to use for calculating similarity of
a database molecule against a set of reference molecules during \fIMultipleReferences\fR value of
similarity search \fB\-m, \-\-mode\fR. Possible values: \fIMax, Min, Mean, Median, Sum, Euclidean\fR. Default
value: \fIMax\fR. \fIMean\fR value corresponds to average or arithmetic mean. The group fusion rule is
also referred to as data fusion of consensus scoring in the literature.
.Sp
For a reference molecules set and a database molecule, let:
.Sp
.Vb 1
\&    N = Number of reference molecules in a set
\&
\&    i = ith reference reference molecule in a set
\&    n = Nth reference reference molecule in a set
\&
\&    d = dth database molecule
\&
\&    Crd = Fingerprints comparison value between rth reference and dth database
\&          molecule \- similarity/dissimilarity comparison using similarity or
\&          distance coefficient
.Ve
.Sp
Then, various group fusion rules to calculate fused similarity between a database molecule and
reference molecules set are defined as follows:
.Sp
\&\fBMax\fR: \s-1MAX\s0 ( C1d, C2d, ..., Cid, ..., Cnd )
.Sp
\&\fBMin\fR: \s-1MIN\s0 ( C1d, C2d, ..., Cid, ..., Cnd )
.Sp
\&\fBMean\fR: \s-1SUM\s0 ( C1d, C2d, ..., Cid, ..., Cnd ) / N
.Sp
\&\fBMedian\fR: \s-1MEDIAN\s0 (  C1d, C2d, ..., Cid, ..., Cnd )
.Sp
\&\fBSum\fR: \s-1SUM\s0 (  C1d, C2d, ..., Cid, ..., Cnd )
.Sp
\&\fBEuclidean\fR: \s-1SQRT\s0( \s-1SUM\s0( C1d ** 2, C2d ** 2, ..., Cid ** 2, ..., Cnd *** 2) )
.Sp
The fingerprints bit-vector or vector string of each reference molecule in a set is compared
with a database molecule using a similarity or distance coefficient specified via \fB\-b,
\&\-\-BitVectorComparisonMode\fR or \fB\-v, \-\-VectorComparisonMode\fR. The reference molecules
whose comparison values with a database molecule fall outside specified \fB\-\-SimilarityCutoff\fR
or \fB\-\-DistanceCutoff\fR are ignored during \fIYes\fR value of \fB\-\-GroupFusionApplyCutoff\fR. The
specified \fB\-g, \-\-GroupFusionRule\fR is applied to \fB\-k, \-\-kNN\fR reference molecules to calculate
final fused similarity value between a database molecule and reference molecules set.
.Sp
During dissimilarity search or usage of distance comparison coefficient in similarity search,
the meaning of fingerprints comaprison value is automatically reversed as shown below:
.Sp
.Vb 1
\&    SeachMode      ComparisonCoefficient  ComparisonValues
\&
\&    Similarity     SimilarityCoefficient  Higher value imples high similarity
\&    Similarity     DistanceCoefficient    Lower value implies high similarity
\&
\&    Dissimilarity  SimilarityCoefficient  Lower value implies high
\&                                          dissimilarity
\&    Dissimilarity  DistanceCoefficient    Higher value implies high
\&                                          dissimilarity
.Ve
.Sp
Consequently, \fIMax\fR implies highest and lowest comparison value for usage of similarity and
distance coefficient respectively during similarity search. And it corresponds to lowest and highest
comparison value for usage of similarity and distance coefficient respectively during dissimilarity
search. During \fIMin\fR fusion rule, the highest and lowest comparison values are appropriately
reversed.
.IP "\fB\-\-GroupFusionApplyCutoff\fR \fIYes | No\fR" 4
.IX Item "--GroupFusionApplyCutoff Yes | No"
Specify whether to apply \fB\-\-SimilarityCutoff\fR or \fB\-\-DistanceCutoff\fR values during application
of \fB\-g, \-\-GroupFusionRule\fR to reference molecules set. Possible values: \fIYes or No\fR. Default
value: \fIYes\fR.
.Sp
During \fIYes\fR value of \fB\-\-GroupFusionApplyCutoff\fR, the reference molecules whose comparison
values with a database molecule fall outside specified \fB\-\-SimilarityCutoff\fR or \fB\-\-DistanceCutoff\fR
are not used to calculate final fused similarity value between a database molecule and reference
molecules set.
.IP "\fB\-h, \-\-help\fR" 4
.IX Item "-h, --help"
Print this help message.
.IP "\fB\-\-InDelim\fR \fIcomma | semicolon\fR" 4
.IX Item "--InDelim comma | semicolon"
Input delimiter for reference and database fingerprints \s-1CSV\s0 \fITextFile(s)\fR. Possible values:
\&\fIcomma or semicolon\fR. Default value: \fIcomma\fR. For \s-1TSV\s0 files, this option is ignored
and \fItab\fR is used as a delimiter.
.IP "\fB\-k, \-\-kNN\fR \fIall | number\fR" 4
.IX Item "-k, --kNN all | number"
Number of k\-nearest neighbors (k\-NN) reference molecules to use during \fB\-g, \-\-GroupFusionRule\fR
for calculating similarity of a database molecule against a set of reference molecules. Possible values:
\&\fIall | positive integers\fR. Default: \fIall\fR.
.Sp
After ranking similarity values between a database molecule and reference molecules during
\&\fIMultipleReferences\fR value of similarity search \fB\-m, \-\-mode\fR option, a top \fB\-k, \-\-KNN\fR reference
molecule are selected and used during \fB\-g, \-\-GroupFusionRule\fR.
.Sp
This option is \fB\-s, \-\-SearchMode\fR dependent: It corresponds to dissimilar molecules during
\&\fIDissimilaritySearch\fR value of \fB\-s, \-\-SearchMode\fR option.
.IP "\fB\-m, \-\-mode\fR \fIIndividualReference | MultipleReferences\fR" 4
.IX Item "-m, --mode IndividualReference | MultipleReferences"
Specify how to treat reference molecules in \fIReferenceFingerprintsFile\fR during similarity search:
Treat each reference molecule individually during similarity search or perform similarity
search by treating multiple reference molecules as a set. Possible values: \fIIndividualReference
| MultipleReferences\fR. Default value: \fIMultipleReferences\fR.
.Sp
During \fIIndividualReference\fR value of  \fB\-m, \-\-Mode\fR for similarity search, fingerprints bit-vector
or vector string of each reference molecule is compared with database molecules using specified
similarity or distance coefficients to identify most similar molecules for each reference molecule.
Based on value of \fB\-\-SimilarCountMode\fR, upto \fB\-\-n, NumOfSimilarMolecules\fR or \fB\-p,
\&\-\-PercentSimilarMolecules\fR at specified <\-\-SimilarityCutoff> or \fB\-\-DistanceCutoff\fR are
identified for each reference molecule.
.Sp
During \fIMultipleReferences\fR value \fB\-m, \-\-mode\fR for similarity search, all reference molecules
are considered as a set and \fB\-g, \-\-GroupFusionRule\fR is used to calculate similarity of a database
molecule against reference molecules set either using all reference molecules or number of k\-nearest
neighbors (k\-NN) to a database molecule specified using \fB\-k, \-\-kNN\fR. The fingerprints bit-vector
or vector string of each reference molecule in a set is compared with a database molecule using
a similarity or distance coefficient specified via \fB\-b, \-\-BitVectorComparisonMode\fR or \fB\-v,
\&\-\-VectorComparisonMode\fR. The reference molecules whose comparison values with a database
molecule fall outside specified \fB\-\-SimilarityCutoff\fR or \fB\-\-DistanceCutoff\fR are ignored. The
specified \fB\-g, \-\-GroupFusionRule\fR is applied to rest of \fB\-k, \-\-kNN\fR reference molecules to calculate
final similarity value between a database molecule and reference molecules set.
.Sp
The meaning of similarity and distance is automatically reversed during \fIDissimilaritySearch\fR value
of \fB\-s, \-\-SearchMode\fR along with appropriate handling of \fB\-\-SimilarityCutoff\fR or
\&\fB\-\-DistanceCutoff\fR values.
.IP "\fB\-n, \-\-NumOfSimilarMolecules\fR \fInumber\fR" 4
.IX Item "-n, --NumOfSimilarMolecules number"
Maximum number of most similar database molecules to find for each reference molecule or set of
reference molecules based on \fIIndividualReference\fR or \fIMultipleReferences\fR value of similarity
search \fB\-m, \-\-mode\fR option. Default: \fI10\fR. Valid values: positive integers.
.Sp
This option is ignored during \fIPercentSimilar\fR value of \fB\-\-SimilarCountMode\fR option.
.Sp
This option is \fB\-s, \-\-SearchMode\fR dependent: It corresponds to dissimilar molecules during
\&\fIDissimilaritySearch\fR value of \fB\-s, \-\-SearchMode\fR option.
.IP "\fB\-\-OutDelim\fR \fIcomma | tab | semicolon\fR" 4
.IX Item "--OutDelim comma | tab | semicolon"
Delimiter for output \s-1CSV/TSV\s0 text file. Possible values: \fIcomma, tab, or semicolon\fR
Default value: \fIcomma\fR.
.IP "\fB\-\-output\fR \fI\s-1SD\s0 | text | both\fR" 4
.IX Item "--output SD | text | both"
Type of output files to generate. Possible values: \fI\s-1SD\s0, text, or both\fR. Default value: \fItext\fR.
.IP "\fB\-o, \-\-overwrite\fR" 4
.IX Item "-o, --overwrite"
Overwrite existing files
.IP "\fB\-p, \-\-PercentSimilarMolecules\fR \fInumber\fR" 4
.IX Item "-p, --PercentSimilarMolecules number"
Maximum percent of mosy similar database molecules to find for each reference molecule or set of
reference molecules based on \fIIndividualReference\fR or \fIMultipleReferences\fR value of similarity
search \fB\-m, \-\-mode\fR option. Default: \fI1\fR percent of database molecules. Valid values: non-zero values
in between \fI0 to 100\fR.
.Sp
This option is ignored during \fINumOfSimilar\fR value of \fB\-\-SimilarCountMode\fR option.
.Sp
During \fIPercentSimilar\fR value of \fB\-\-SimilarCountMode\fR option, the number of molecules
in \fIDatabaseFingerprintsFile\fR is counted and number of similar molecules correspond to
\&\fB\-\-PercentSimilarMolecules\fR of the total number of database molecules.
.Sp
This option is \fB\-s, \-\-SearchMode\fR dependent: It corresponds to dissimilar molecules during
\&\fIDissimilaritySearch\fR value of \fB\-s, \-\-SearchMode\fR option.
.IP "\fB\-\-precision\fR \fInumber\fR" 4
.IX Item "--precision number"
Precision of calculated similarity values for comparison and generating output files. Default: up to \fI2\fR
decimal places. Valid values: positive integers.
.IP "\fB\-q, \-\-quote\fR \fIYes | No\fR" 4
.IX Item "-q, --quote Yes | No"
Put quote around column values in output \s-1CSV/TSV\s0 text file. Possible values:
\&\fIYes or No\fR. Default value: \fIYes\fR.
.IP "\fB\-\-ReferenceColMode\fR \fIColNum | ColLabel\fR" 4
.IX Item "--ReferenceColMode ColNum | ColLabel"
Specify how columns are identified in reference fingerprints \fITextFile\fR: using column
number or column label. Possible values: \fIColNum or ColLabel\fR. Default value: \fIColNum\fR.
.IP "\fB\-\-ReferenceCompoundIDCol\fR \fIcol number | col name\fR" 4
.IX Item "--ReferenceCompoundIDCol col number | col name"
This value is \fB\-\-ReferenceColMode\fR mode specific. It specifies column to use for retrieving compound
\&\s-1ID\s0 from reference fingerprints \fITextFile\fR during similarity and dissimilarity search for output \s-1SD\s0 and \s-1CSV/TSV\s0
text files. Possible values: \fIcol number or col label\fR. Default value: \fIfirst column containing the word compoundID
in its column label or sequentially generated IDs\fR.
.IP "\fB\-\-ReferenceCompoundIDPrefix\fR \fItext\fR" 4
.IX Item "--ReferenceCompoundIDPrefix text"
Specify compound \s-1ID\s0 prefix to use during sequential generation of compound IDs for reference fingerprints
\&\fISDFile\fR and \fITextFile\fR. Default value: \fICmpd\fR. The default value generates compound IDs which looks
like Cmpd<Number>.
.Sp
For reference fingerprints \fISDFile\fR, this value is only used during \fILabelPrefix | MolNameOrLabelPrefix\fR
values of \fB\-\-ReferenceCompoundIDMode\fR option; otherwise, it's ignored.
.Sp
Examples for \fILabelPrefix\fR or \fIMolNameOrLabelPrefix\fR value of \fB\-\-DatabaseCompoundIDMode\fR:
.Sp
.Vb 1
\&    Compound
.Ve
.Sp
The values specified above generates compound IDs which correspond to Compound<Number>
instead of default value of Cmpd<Number>.
.IP "\fB\-\-ReferenceCompoundIDField\fR \fIDataFieldName\fR" 4
.IX Item "--ReferenceCompoundIDField DataFieldName"
Specify reference fingerprints \fISDFile\fR datafield label for generating compound IDs.
This value is only used during \fIDataField\fR value of \fB\-\-ReferenceCompoundIDMode\fR option.
.Sp
Examples for \fIDataField\fR value of \fB\-\-ReferenceCompoundIDMode\fR:
.Sp
.Vb 2
\&    MolID
\&    ExtReg
.Ve
.IP "\fB\-\-ReferenceCompoundIDMode\fR \fIDataField | MolName | LabelPrefix | MolNameOrLabelPrefix\fR" 4
.IX Item "--ReferenceCompoundIDMode DataField | MolName | LabelPrefix | MolNameOrLabelPrefix"
Specify how to generate compound IDs from reference fingerprints \fISDFile\fR during similarity and
dissimilarity search for output \s-1SD\s0 and \s-1CSV/TSV\s0 text files: use a \fISDFile\fR datafield value; use
molname line from \fISDFile\fR; generate a sequential \s-1ID\s0 with specific prefix; use combination of both
MolName and LabelPrefix with usage of LabelPrefix values for empty molname lines.
.Sp
Possible values: \fIDataField | MolName | LabelPrefix | MolNameOrLabelPrefix\fR.
Default: \fILabelPrefix\fR.
.Sp
For \fIMolNameAndLabelPrefix\fR value of \fB\-\-ReferenceCompoundIDMode\fR, molname line in \fISDFiles\fR
takes precedence over sequential compound IDs generated using \fILabelPrefix\fR and only empty molname
values are replaced with sequential compound IDs.
.IP "\fB\-\-ReferenceFingerprintsCol\fR \fIcol number | col name\fR" 4
.IX Item "--ReferenceFingerprintsCol col number | col name"
This value is \fB\-\-ReferenceColMode\fR specific. It specifies fingerprints column to use during similarity
and dissimilarity search for reference fingerprints \fITextFile\fR. Possible values: \fIcol number or col label\fR.
Default value: \fIfirst column containing the word Fingerprints in its column label\fR.
.IP "\fB\-\-ReferenceFingerprintsField\fR \fIFieldLabel\fR" 4
.IX Item "--ReferenceFingerprintsField FieldLabel"
Fingerprints field label to use during similarity and dissimilarity search for reference fingerprints \fISDFile\fR.
Default value: \fIfirst data field label containing the word Fingerprints in its label\fR
.IP "\fB\-r, \-\-root\fR \fIRootName\fR" 4
.IX Item "-r, --root RootName"
New file name is generated using the root: <Root>.<Ext>. Default for new file name:
<ReferenceFileName>SimilaritySearching.<Ext>. The output file type determines <Ext>
value. The sdf, csv, and tsv <Ext> values are used for \s-1SD\s0, comma/semicolon, and tab delimited
text files respectively.
.IP "\fB\-s, \-\-SearchMode\fR \fISimilaritySearch | DissimilaritySearch\fR" 4
.IX Item "-s, --SearchMode SimilaritySearch | DissimilaritySearch"
Specify how to find molecules from database molecules for individual reference molecules or
set of reference molecules: Find similar molecules or dissimilar molecules from database molecules.
Possible values: \fISimilaritySearch | DissimilaritySearch\fR. Default value: \fISimilaritySearch\fR.
.Sp
During \fIDissimilaritySearch\fR value of \fB\-s, \-\-SearchMode\fR option, the meaning of the following
options is switched and they correspond to dissimilar molecules instead of similar molecules:
\&\fB\-\-SimilarCountMode\fR, \fB\-n, \-\-NumOfSimilarMolecules\fR, \fB\-\-PercentSimilarMolecules\fR,
\&\fB\-k, \-\-kNN\fR.
.IP "\fB\-\-SimilarCountMode\fR \fINumOfSimilar | PercentSimilar\fR" 4
.IX Item "--SimilarCountMode NumOfSimilar | PercentSimilar"
Specify method used to count similar molecules found from database molecules for individual
reference molecules or set of reference molecules: Find number of similar molecules or percent
of similar molecules from database molecules. Possible values: \fINumOfSimilar | PercentSimilar\fR.
Default value: \fINumOfSimilar\fR.
.Sp
The values for number of similar molecules and percent similar molecules are specified
using options \fB\-n, NumOfSimilarMolecule\fR and \fB\-\-PercentSimilarMolecules\fR.
.Sp
This option is \fB\-s, \-\-SearchMode\fR dependent: It corresponds to dissimilar molecules during
\&\fIDissimilaritySearch\fR value of \fB\-s, \-\-SearchMode\fR option.
.IP "\fB\-\-SimilarityCutoff\fR \fInumber\fR" 4
.IX Item "--SimilarityCutoff number"
Similarity cutoff value to use during comparison of similarity value between a pair of database
and reference molecules calculated by similarity comparison methods for fingerprints bit-vector
vector strings data values. Possible values: \fIAny valid number\fR. Default value: \fI0.75\fR.
.Sp
The comparison value between a pair of database and reference molecule must meet the cutoff
criterion as shown below:
.Sp
.Vb 1
\&    SeachMode      CutoffCriterion  ComparisonValues
\&
\&    Similarity     >=               Higher value implies high similarity
\&    Dissimilarity  <=               Lower value implies high dissimilarity
.Ve
.Sp
This option is ignored during \fINo\fR value of \fB\-\-GroupFusionApplyCutoff\fR for \fIMultipleReferences\fR
\&\fB\-m, \-\-mode\fR.
.Sp
This option is \fB\-s, \-\-SearchMode\fR dependent: It corresponds to dissimilar molecules during
\&\fIDissimilaritySearch\fR value of \fB\-s, \-\-SearchMode\fR option.
.IP "\fB\-v, \-\-VectorComparisonMode\fR \fISupportedSimilarityName | SupportedDistanceName\fR" 4
.IX Item "-v, --VectorComparisonMode SupportedSimilarityName | SupportedDistanceName"
Specify what similarity or distance coefficient to use for calculating similarity between fingerprint
vector strings data values in \fIReferenceFingerprintsFile\fR and \fIDatabaseFingerprintsFile\fR during
similarity search. Possible values:  \fITanimotoSimilairy | ... | ManhattanDistance | ...\fR. Default
value: \fITanimotoSimilarity\fR.
.Sp
The value of \fB\-v, \-\-VectorComparisonMode\fR, in conjunction with \fB\-\-VectorComparisonFormulism\fR,
decides which type of similarity and distance coefficient formulism gets used.
.Sp
The current releases supports the following similarity and distance coefficients: \fICosineSimilarity,
CzekanowskiSimilarity, DiceSimilarity, OchiaiSimilarity, JaccardSimilarity, SorensonSimilarity, TanimotoSimilarity,
CityBlockDistance, EuclideanDistance, HammingDistance, ManhattanDistance, SoergelDistance\fR. These
similarity and distance coefficients are described below.
.Sp
\&\fBFingerprintsVector.pm\fR module, used to calculate similarity and distance coefficients,
provides support to perform comparison between vectors containing three different types of
values:
.Sp
Type I: OrderedNumericalValues
.Sp
.Vb 3
\&    . Size of two vectors are same
\&    . Vectors contain real values in a specific order. For example: MACCS keys
\&      count, Topological pharmnacophore atom pairs and so on.
.Ve
.Sp
Type \s-1II:\s0 UnorderedNumericalValues
.Sp
.Vb 3
\&    . Size of two vectors might not be same
\&    . Vectors contain unordered real value identified by value IDs. For example:
\&      Toplogical atom pairs, Topological atom torsions and so on
.Ve
.Sp
Type \s-1III:\s0 AlphaNumericalValues
.Sp
.Vb 3
\&    . Size of two vectors might not be same
\&    . Vectors contain unordered alphanumerical values. For example: Extended
\&      connectivity fingerprints, atom neighborhood fingerprints.
.Ve
.Sp
Before performing similarity or distance calculations between vectors containing UnorderedNumericalValues
or AlphaNumericalValues, the vectors are transformed into vectors containing unique OrderedNumericalValues
using value IDs for UnorderedNumericalValues and values itself for AlphaNumericalValues.
.Sp
Three forms of similarity and distance calculation between two vectors, specified using \fB\-\-VectorComparisonFormulism\fR
option, are supported: \fIAlgebraicForm, BinaryForm or SetTheoreticForm\fR.
.Sp
For \fIBinaryForm\fR, the ordered list of processed final vector values containing the value or
count of each unique value type is simply converted into a binary vector containing 1s and 0s
corresponding to presence or absence of values before calculating similarity or distance between
two vectors.
.Sp
For two fingerprint vectors A and B of same size containing OrderedNumericalValues, let:
.Sp
.Vb 1
\&    N = Number values in A or B
\&
\&    Xa = Values of vector A
\&    Xb = Values of vector B
\&
\&    Xai = Value of ith element in A
\&    Xbi = Value of ith element in B
\&
\&   SUM = Sum of i over N values
.Ve
.Sp
For SetTheoreticForm of calculation between two vectors, let:
.Sp
.Vb 2
\&    SetIntersectionXaXb = SUM ( MIN ( Xai, Xbi ) )
\&    SetDifferenceXaXb = SUM ( Xai ) + SUM ( Xbi ) \- SUM ( MIN ( Xai, Xbi ) )
.Ve
.Sp
For BinaryForm of calculation between two vectors, let:
.Sp
.Vb 5
\&    Na = Number of bits set to "1" in A = SUM ( Xai )
\&    Nb = Number of bits set to "1" in B = SUM ( Xbi )
\&    Nc = Number of bits set to "1" in both A and B = SUM ( Xai * Xbi )
\&    Nd = Number of bits set to "0" in both A and B
\&       = SUM ( 1 \- Xai \- Xbi + Xai * Xbi)
\&
\&    N = Number of bits set to "1" or "0" in A or B = Size of A or B = Na + Nb \- Nc + Nd
.Ve
.Sp
Additionally, for BinaryForm various values also correspond to:
.Sp
.Vb 4
\&    Na = | Xa |
\&    Nb = | Xb |
\&    Nc = | SetIntersectionXaXb |
\&    Nd = N \- | SetDifferenceXaXb |
\&
\&    | SetDifferenceXaXb | = N \- Nd = Na + Nb \- Nc + Nd \- Nd = Na + Nb \- Nc
\&                          =  | Xa | + | Xb | \- | SetIntersectionXaXb |
.Ve
.Sp
Various similarity and distance coefficients [ Ref 40, Ref 62, Ref 64 ] for a pair of vectors A and B
in \fIAlgebraicForm, BinaryForm and SetTheoreticForm\fR are defined as follows:
.Sp
\&\fBCityBlockDistance\fR: ( same as HammingDistance and ManhattanDistance)
.Sp
\&\fIAlgebraicForm\fR: \s-1SUM\s0 ( \s-1ABS\s0 ( Xai \- Xbi ) )
.Sp
\&\fIBinaryForm\fR: ( Na \- Nc ) + ( Nb \- Nc ) = Na + Nb \- 2 * Nc
.Sp
\&\fISetTheoreticForm\fR: | SetDifferenceXaXb | \- | SetIntersectionXaXb | = \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) )
.Sp
\&\fBCosineSimilarity\fR:  ( same as OchiaiSimilarityCoefficient)
.Sp
\&\fIAlgebraicForm\fR: \s-1SUM\s0 ( Xai * Xbi ) / \s-1SQRT\s0 ( \s-1SUM\s0 ( Xai ** 2) * \s-1SUM\s0 ( Xbi ** 2) )
.Sp
\&\fIBinaryForm\fR: Nc / \s-1SQRT\s0 ( Na * Nb)
.Sp
\&\fISetTheoreticForm\fR: | SetIntersectionXaXb | / \s-1SQRT\s0 ( |Xa| * |Xb| ) = \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) / \s-1SQRT\s0 ( \s-1SUM\s0 ( Xai ) * \s-1SUM\s0 ( Xbi ) )
.Sp
\&\fBCzekanowskiSimilarity\fR: ( same as DiceSimilarity and SorensonSimilarity)
.Sp
\&\fIAlgebraicForm\fR: ( 2 * ( \s-1SUM\s0 ( Xai * Xbi ) )  ) / ( \s-1SUM\s0 ( Xai ** 2) + \s-1SUM\s0 ( Xbi **2 ) )
.Sp
\&\fIBinaryForm\fR: 2 * Nc / ( Na + Nb )
.Sp
\&\fISetTheoreticForm\fR: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) = 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) ) / ( \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) )
.Sp
\&\fBDiceSimilarity\fR: ( same as CzekanowskiSimilarity and SorensonSimilarity)
.Sp
\&\fIAlgebraicForm\fR: ( 2 * ( \s-1SUM\s0 ( Xai * Xbi ) )  ) / ( \s-1SUM\s0 ( Xai ** 2) + \s-1SUM\s0 ( Xbi **2 ) )
.Sp
\&\fIBinaryForm\fR: 2 * Nc / ( Na + Nb )
.Sp
\&\fISetTheoreticForm\fR: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) = 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) ) / ( \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) )
.Sp
\&\fBEuclideanDistance\fR:
.Sp
\&\fIAlgebraicForm\fR: \s-1SQRT\s0 ( \s-1SUM\s0 ( ( ( Xai \- Xbi ) ** 2 ) ) )
.Sp
\&\fIBinaryForm\fR: \s-1SQRT\s0 ( ( Na \- Nc ) + ( Nb \- Nc ) ) = \s-1SQRT\s0 ( Na + Nb \- 2 * Nc )
.Sp
\&\fISetTheoreticForm\fR: \s-1SQRT\s0 ( | SetDifferenceXaXb | \- | SetIntersectionXaXb | ) = \s-1SQRT\s0 (  \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) ) )
.Sp
\&\fBHammingDistance\fR:  ( same as CityBlockDistance and ManhattanDistance)
.Sp
\&\fIAlgebraicForm\fR: \s-1SUM\s0 ( \s-1ABS\s0 ( Xai \- Xbi ) )
.Sp
\&\fIBinaryForm\fR: ( Na \- Nc ) + ( Nb \- Nc ) = Na + Nb \- 2 * Nc
.Sp
\&\fISetTheoreticForm\fR: | SetDifferenceXaXb | \- | SetIntersectionXaXb | = \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) )
.Sp
\&\fBJaccardSimilarity\fR: ( same as TanimotoSimilarity)
.Sp
\&\fIAlgebraicForm\fR:  \s-1SUM\s0 ( Xai * Xbi ) / ( \s-1SUM\s0 ( Xai ** 2 ) + \s-1SUM\s0 ( Xbi ** 2 ) \- \s-1SUM\s0 ( Xai * Xbi ) )
.Sp
\&\fIBinaryForm\fR:  Nc / ( ( Na \- Nc ) + ( Nb \- Nc ) + Nc ) = Nc / ( Na + Nb \- Nc )
.Sp
\&\fISetTheoreticForm\fR: | SetIntersectionXaXb | / | SetDifferenceXaXb | = \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) / (  \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) )
.Sp
\&\fBManhattanDistance\fR:  ( same as CityBlockDistance and HammingDistance)
.Sp
\&\fIAlgebraicForm\fR: \s-1SUM\s0 ( \s-1ABS\s0 ( Xai \- Xbi ) )
.Sp
\&\fIBinaryForm\fR: ( Na \- Nc ) + ( Nb \- Nc ) = Na + Nb \- 2 * Nc
.Sp
\&\fISetTheoreticForm\fR: | SetDifferenceXaXb | \- | SetIntersectionXaXb | = \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) )
.Sp
\&\fBOchiaiSimilarity\fR:  ( same as CosineSimilarity)
.Sp
\&\fIAlgebraicForm\fR: \s-1SUM\s0 ( Xai * Xbi ) / \s-1SQRT\s0 ( \s-1SUM\s0 ( Xai ** 2) * \s-1SUM\s0 ( Xbi ** 2) )
.Sp
\&\fIBinaryForm\fR: Nc / \s-1SQRT\s0 ( Na * Nb)
.Sp
\&\fISetTheoreticForm\fR: | SetIntersectionXaXb | / \s-1SQRT\s0 ( |Xa| * |Xb| ) = \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) / \s-1SQRT\s0 ( \s-1SUM\s0 ( Xai ) * \s-1SUM\s0 ( Xbi ) )
.Sp
\&\fBSorensonSimilarity\fR: ( same as CzekanowskiSimilarity and DiceSimilarity)
.Sp
\&\fIAlgebraicForm\fR: ( 2 * ( \s-1SUM\s0 ( Xai * Xbi ) )  ) / ( \s-1SUM\s0 ( Xai ** 2) + \s-1SUM\s0 ( Xbi **2 ) )
.Sp
\&\fIBinaryForm\fR: 2 * Nc / ( Na + Nb )
.Sp
\&\fISetTheoreticForm\fR: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) = 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) ) / ( \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) )
.Sp
\&\fBSoergelDistance\fR:
.Sp
\&\fIAlgebraicForm\fR:  \s-1SUM\s0 ( \s-1ABS\s0 ( Xai \- Xbi ) ) / \s-1SUM\s0 ( \s-1MAX\s0 ( Xai, Xbi ) )
.Sp
\&\fIBinaryForm\fR: 1 \- Nc / ( Na + Nb \- Nc ) = ( Na + Nb \- 2 * Nc ) / ( Na + Nb \- Nc )
.Sp
\&\fISetTheoreticForm\fR: ( | SetDifferenceXaXb | \- | SetIntersectionXaXb | ) / | SetDifferenceXaXb | = ( \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- 2 * ( \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) ) ) / ( \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) )
.Sp
\&\fBTanimotoSimilarity\fR:  ( same as JaccardSimilarity)
.Sp
\&\fIAlgebraicForm\fR:  \s-1SUM\s0 ( Xai * Xbi ) / ( \s-1SUM\s0 ( Xai ** 2 ) + \s-1SUM\s0 ( Xbi ** 2 ) \- \s-1SUM\s0 ( Xai * Xbi ) )
.Sp
\&\fIBinaryForm\fR:  Nc / ( ( Na \- Nc ) + ( Nb \- Nc ) + Nc ) = Nc / ( Na + Nb \- Nc )
.Sp
\&\fISetTheoreticForm\fR: | SetIntersectionXaXb | / | SetDifferenceXaXb | = \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) / (  \s-1SUM\s0 ( Xai ) + \s-1SUM\s0 ( Xbi ) \- \s-1SUM\s0 ( \s-1MIN\s0 ( Xai, Xbi ) ) )
.IP "\fB\-\-VectorComparisonFormulism\fR \fIAlgebraicForm | BinaryForm | SetTheoreticForm\fR" 4
.IX Item "--VectorComparisonFormulism AlgebraicForm | BinaryForm | SetTheoreticForm"
Specify fingerprints vector comparison formulism to use for calculation similarity and distance
coefficients during \fB\-v, \-\-VectorComparisonMode\fR. Possible values: \fIAlgebraicForm | BinaryForm |
SetTheoreticForm\fR. Default value: \fIAlgebraicForm\fR.
.Sp
For fingerprint vector strings containing \fBAlphaNumericalValues\fR data values \- \fBExtendedConnectivityFingerprints\fR,
\&\fBAtomNeighborhoodsFingerprints\fR and so on \- all three formulism result in same value during similarity and distance
calculations.
.IP "\fB\-w, \-\-WorkingDir\fR \fIDirName\fR" 4
.IX Item "-w, --WorkingDir DirName"
Location of working directory. Default: current directory.
.SH "EXAMPLES"
.IX Header "EXAMPLES"
To perform similarity search using Tanimoto coefficient by treating all reference molecules as a set
to find 10 most similar database molecules with application of Max group fusion rule and similarity
cutoff to supported fingerprints strings data in \s-1SD\s0 fingerprints files present in a data fields with
Fingerprint substring in their labels, and create a ReferenceFPHexSimilaritySearching.csv file containing
sequentially generated database compound IDs with Cmpd prefix, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-o ReferenceSampleFPHex.sdf
\&      DatabaseSampleFPHex.sdf
.Ve
.PP
To perform similarity search using Tanimoto coefficient by treating all reference molecules as a set
to find 10 most similar database molecules with application of Max group fusion rule and similarity
cutoff to supported fingerprints strings data in \s-1FP\s0 fingerprints files, and create a
SimilaritySearchResults.csv file containing database compound IDs retireved from \s-1FP\s0 file, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-r SimilaritySearchResults \-o
\&      ReferenceSampleFPBin.fpf DatabaseSampleFPBin.fpf
.Ve
.PP
To perform similarity search using Tanimoto coefficient by treating all reference molecules as a set
to find 10 most similar database database molecules with application of Max group fusion rule and
similarity cutoff to supported fingerprints strings data in text fingerprints files present in a column
names containing Fingerprint substring in their names, and create a ReferenceFPHexSimilaritySearching.csv
file containing database compound IDs retireved column name containing CompoundID substring or
sequentially generated compound IDs, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-o ReferenceSampleFPCount.csv
\&      DatabaseSampleFPCount.csv
.Ve
.PP
To perform similarity search  using Tanimoto coefficient by treating reference molecules as individual molecules
to find 10 most similar database molecules for each reference molecule with application of similarity cutoff to
supported fingerprints strings data in \s-1SD\s0 fingerprints files present in a data fields with Fingerprint substring
in their labels, and create a ReferenceFPHexSimilaritySearching.csv file containing sequentially generated
reference and database compound IDs with Cmpd prefix, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-mode IndividualReference \-o
\&      ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
.Ve
.PP
To perform similarity search  using Tanimoto coefficient by treating reference molecules as individual molecules
to find 10 most similar database molecules for each reference molecule with application of similarity cutoff to
supported fingerprints strings data in \s-1FP\s0 fingerprints files, and create a ReferenceFPHexSimilaritySearching.csv
file containing references and database compound IDs retireved from \s-1FP\s0 file, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-mode IndividualReference \-o
\&      ReferenceSampleFPHex.fpf DatabaseSampleFPHex.fpf
.Ve
.PP
To perform similarity search  using Tanimoto coefficient by treating reference molecules as individual molecules
to find 10 most similar database molecules for each reference molecule with application of similarity cutoff to
supported fingerprints strings data in text fingerprints files present in a column names containing Fingerprint
substring in their names, and create a ReferenceFPHexSimilaritySearching.csv file containing reference and
database compound IDs retrieved column name containing CompoundID substring or sequentially generated
compound IDs, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-mode IndividualReference \-o
\&      ReferenceSampleFPHex.csv DatabaseSampleFPHex.csv
.Ve
.PP
To perform dissimilarity search using Tanimoto coefficient by treating all reference molecules as a set
to find 10 most dissimilar database molecules with application of Max group fusion rule and similarity
cutoff to supported fingerprints strings data in \s-1SD\s0 fingerprints files present in a data fields with
Fingerprint substring in their labels, and create a ReferenceFPHexSimilaritySearching.csv file containing
sequentially generated database compound IDs with Cmpd prefix, type:
.PP
.Vb 2
\&    % SimilaritySearchingFingerprints.pl \-\-mode MultipleReferences \-\-SearchMode
\&      DissimilaritySearch \-o ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
.Ve
.PP
To perform similarity search using CityBlock distance by treating reference molecules as individual molecules
to find 10 most similar database molecules for each reference molecule with application of distance cutoff
to supported vector fingerprints strings data in \s-1SD\s0 fingerprints files present in a data fields with Fingerprint
substring in their labels, and create a ReferenceFPHexSimilaritySearching.csv file containing sequentially generated
reference and database compound IDs with Cmpd prefix, type:
.PP
.Vb 4
\&    % SimilaritySearchingFingerprints.pl \-mode IndividualReference
\&      \-\-VectorComparisonMode CityBlockDistance \-\-VectorComparisonFormulism
\&      AlgebraicForm \-\-DistanceCutoff 10 \-o
\&      ReferenceSampleFPCount.sdf DatabaseSampleFPCount.sdf
.Ve
.PP
To perform similarity search using Tanimoto coefficient by treating all reference molecules as a set
to find 100 most similar database molecules with application of Mean group fusion rule to to top 10
reference molecules with in similarity cutoff of 0.75 to supported fingerprints strings data in \s-1FP\s0 fingerprints
files, and create a ReferenceFPHexSimilaritySearching.csv file containing database compound IDs retrieved
from \s-1FP\s0 file, type:
.PP
.Vb 6
\&    % SimilaritySearchingFingerprints.pl \-\-mode MultipleReferences \-\-SearchMode
\&      SimilaritySearch \-\-BitVectorComparisonMode TanimotoSimilarity
\&      \-\-GroupFusionRule Mean \-\-GroupFusionApplyCutoff Yes \-\-kNN 10
\&      \-\-SimilarityCutoff 0.75 \-\-SimilarCountMode NumOfSimilar
\&      \-\-NumOfSimilarMolecules 100 \-o
\&      ReferenceSampleFPHex.fpf DatabaseSampleFPHex.fpf
.Ve
.PP
To perform similarity search  using Tanimoto coefficient by treating reference molecules as individual molecules
to find 2 percent of most similar database molecules for each reference molecule with application of similarity
cutoff of 0.85 to supported fingerprints strings data in text fingerprints files present in specific columns and
create a ReferenceFPHexSimilaritySearching.csv file containing reference and database compoundIDs retrieved
from specific columns, type:
.PP
.Vb 8
\&    % SimilaritySearchingFingerprints.pl \-\-mode IndividualReference \-\-SearchMode
\&      SimilaritySearch \-\-BitVectorComparisonMode TanimotoSimilarity
\&      \-\-ReferenceColMode ColLabel \-\-ReferenceFingerprintsCol Fingerprints
\&      \-\-ReferenceCompoundIDCol CompoundID \-\-DatabaseColMode Collabel
\&      \-\-DatabaseCompoundIDCol CompoundID \-\-DatabaseFingerprintsCol
\&      Fingerprints \-\-SimilarityCutoff 0.85 \-\-SimilarCountMode PercentSimilar
\&      \-\-PercentSimilarMolecules 2 \-o
\&      ReferenceSampleFPHex.csv DatabaseSampleFPHex.csv
.Ve
.PP
To perform similarity search  using Tanimoto coefficient by treating reference molecules as individual molecules
to find top 50 most similar database molecules for each reference molecule with application of similarity
cutoff of 0.85 to supported fingerprints strings data in \s-1SD\s0 fingerprints files present in specific data fields and
create both ReferenceFPHexSimilaritySearching.csv and ReferenceFPHexSimilaritySearching.sdf files containing
reference and database compoundIDs retrieved from specific data fields, type:
.PP
.Vb 9
\&    % SimilaritySearchingFingerprints.pl \-\-mode IndividualReference \-\-SearchMode
\&      SimilaritySearch \-\-BitVectorComparisonMode TanimotoSimilarity
\&      \-\-ReferenceFingerprintsField Fingerprints
\&      \-\-DatabaseFingerprintsField Fingerprints
\&      \-\-ReferenceCompoundIDMode DataField \-\-ReferenceCompoundIDField CmpdID
\&      \-\-DatabaseCompoundIDMode DataField \-\-DatabaseCompoundIDField CmpdID
\&      \-\-SimilarityCutoff 0.85 \-\-SimilarCountMode NumOfSimilar
\&      \-\-NumOfSimilarMolecules 50 \-\-output both \-o
\&      ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
.Ve
.PP
To perform similarity search  using Tanimoto coefficient by treating reference molecules as individual molecules
to find 1 percent of  most similar database molecules for each reference molecule with application of similarity
cutoff to supported fingerprints strings data in \s-1SD\s0 fingerprints files present in specific data field labels, and create
both ReferenceFPHexSimilaritySearching.csv ReferenceFPHexSimilaritySearching.sdf files containing reference and
database compound IDs retrieved from specific data field labels along with other specific data for database
molecules, type:
.PP
.Vb 10
\&    % SimilaritySearchingFingerprints.pl \-\-mode IndividualReference \-\-SearchMode
\&      SimilaritySearch \-\-BitVectorComparisonMode TanimotoSimilarity
\&      \-\-ReferenceFingerprintsField Fingerprints
\&      \-\-DatabaseFingerprintsField Fingerprints
\&      \-\-ReferenceCompoundIDMode DataField \-\-ReferenceCompoundIDField CmpdID
\&      \-\-DatabaseCompoundIDMode DataField \-\-DatabaseCompoundIDField CmpdID
\&      \-\-DatabaseDataFieldsMode Specify \-\-DatabaseDataFields "TPSA,SLogP"
\&      \-\-SimilarityCutoff 0.75 \-\-SimilarCountMode PercentSimilar
\&      \-\-PercentSimilarMolecules 1 \-\-output both \-\-OutDelim comma \-\-quote Yes
\&      \-\-precision 3 \-o ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
.Ve
.SH "AUTHOR"
.IX Header "AUTHOR"
Manish Sud <msud@san.rr.com>
.SH "SEE ALSO"
.IX Header "SEE ALSO"
InfoFingerprintsFiles.pl, SimilarityMatricesFingerprints.pl, AtomNeighborhoodsFingerprints.pl,
ExtendedConnectivityFingerprints.pl, MACCSKeysFingerprints.pl, PathLengthFingerprints.pl,
TopologicalAtomPairsFingerprints.pl, TopologicalAtomTorsionsFingerprints.pl,
TopologicalPharmacophoreAtomPairsFingerprints.pl, TopologicalPharmacophoreAtomTripletsFingerprints.pl
.SH "COPYRIGHT"
.IX Header "COPYRIGHT"
Copyright (C) 2015 Manish Sud. All rights reserved.
.PP
This file is part of MayaChemTools.
.PP
MayaChemTools is free software; you can redistribute it and/or modify it under
the terms of the \s-1GNU\s0 Lesser General Public License as published by the Free
Software Foundation; either version 3 of the License, or (at your option)
any later version.
author	deepakjadmin
date	Thu, 15 Dec 2016 14:18:03 -0500
parents	73ae111cf86f
children