Representing Clusters Using a Maximum Common Edge Substructure Algorithm Applied to Reduced Graphs and Molecular Graphs
Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules a...
Saved in:
| Published in | Journal of chemical information and modeling Vol. 47; no. 2; pp. 354 - 366 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Chemical Society
01.03.2007
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1549-9596 1549-960X |
| DOI | 10.1021/ci600444g |
Cover
| Abstract | Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules are clustered using fingerprints, it may be difficult to decipher the structural commonalities which are present. Here, we seek to represent a cluster by means of a maximum common substructure based on the shared functionality of the cluster members. Previously, we have used reduced graphs, where each node corresponds to a generalized functional group, as topological molecular descriptors for virtual screening. In this work, we precluster a database using any clustering method. We then represent the molecules in a cluster as reduced graphs. By repeated application of a maximum common edge substructure (MCES) algorithm, we obtain one or more reduced graph cluster representatives. The sparsity of the reduced graphs means that the MCES calculations can be performed in real time. The reduced graph cluster representatives are readily interpretable in terms of functional activity and can be mapped directly back to the molecules to which they correspond, giving the chemist a rapid means of assessing potential activities contained within the cluster. Clusters of interest are then subject to a detailed R-group analysis using the same iterated MCES algorithm applied to the molecular graphs. |
|---|---|
| AbstractList | Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules are clustered using fingerprints, it may be difficult to decipher the structural commonalities which are present. Here, we seek to represent a cluster by means of a maximum common substructure based on the shared functionality of the cluster members. Previously, we have used reduced graphs, where each node corresponds to a generalized functional group, as topological molecular descriptors for virtual screening. In this work, we precluster a database using any clustering method. We then represent the molecules in a cluster as reduced graphs. By repeated application of a maximum common edge substructure (MCES) algorithm, we obtain one or more reduced graph cluster representatives. The sparsity of the reduced graphs means that the MCES calculations can be performed in real time. The reduced graph cluster representatives are readily interpretable in terms of functional activity and can be mapped directly back to the molecules to which they correspond, giving the chemist a rapid means of assessing potential activities contained within the cluster. Clusters of interest are then subject to a detailed R-group analysis using the same iterated MCES algorithm applied to the molecular graphs.Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules are clustered using fingerprints, it may be difficult to decipher the structural commonalities which are present. Here, we seek to represent a cluster by means of a maximum common substructure based on the shared functionality of the cluster members. Previously, we have used reduced graphs, where each node corresponds to a generalized functional group, as topological molecular descriptors for virtual screening. In this work, we precluster a database using any clustering method. We then represent the molecules in a cluster as reduced graphs. By repeated application of a maximum common edge substructure (MCES) algorithm, we obtain one or more reduced graph cluster representatives. The sparsity of the reduced graphs means that the MCES calculations can be performed in real time. The reduced graph cluster representatives are readily interpretable in terms of functional activity and can be mapped directly back to the molecules to which they correspond, giving the chemist a rapid means of assessing potential activities contained within the cluster. Clusters of interest are then subject to a detailed R-group analysis using the same iterated MCES algorithm applied to the molecular graphs. Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules are clustered using fingerprints, it may be difficult to decipher the structural commonalities which are present. Here, we seek to represent a cluster by means of a maximum common substructure based on the shared functionality of the cluster members. Previously, we have used reduced graphs, where each node corresponds to a generalized functional group, as topological molecular descriptors for virtual screening. In this work, we precluster a database using any clustering method. We then represent the molecules in a cluster as reduced graphs. By repeated application of a maximum common edge substructure (MCES) algorithm, we obtain one or more reduced graph cluster representatives. The sparsity of the reduced graphs means that the MCES calculations can be performed in real time. The reduced graph cluster representatives are readily interpretable in terms of functional activity and can be mapped directly back to the molecules to which they correspond, giving the chemist a rapid means of assessing potential activities contained within the cluster. Clusters of interest are then subject to a detailed R-group analysis using the same iterated MCES algorithm applied to the molecular graphs. Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then able to browse a few representatives of the cluster in order to interpret the shared activity of the cluster members. However, when molecules are clustered using fingerprints, it may be difficult to decipher the structural commonalities which are present. Here, we seek to represent a cluster by means of a maximum common substructure based on the shared functionality of the cluster members. Previously, we have used reduced graphs, where each node corresponds to a generalized functional group, as topological molecular descriptors for virtual screening. In this work, we precluster a database using any clustering method. We then represent the molecules in a cluster as reduced graphs. By repeated application of a maximum common edge substructure (MCES) algorithm, we obtain one or more reduced graph cluster representatives. The sparsity of the reduced graphs means that the MCES calculations can be performed in real time. The reduced graph cluster representatives are readily interpretable in terms of functional activity and can be mapped directly back to the molecules to which they correspond, giving the chemist a rapid means of assessing potential activities contained within the cluster. Clusters of interest are then subject to a detailed R-group analysis using the same iterated MCES algorithm applied to the molecular graphs. [PUBLICATION ABSTRACT] |
| Author | Gardiner, Eleanor J Gillet, Valerie J Cosgrove, David A Willett, Peter |
| Author_xml | – sequence: 1 givenname: Eleanor J surname: Gardiner fullname: Gardiner, Eleanor J – sequence: 2 givenname: Valerie J surname: Gillet fullname: Gillet, Valerie J – sequence: 3 givenname: Peter surname: Willett fullname: Willett, Peter – sequence: 4 givenname: David A surname: Cosgrove fullname: Cosgrove, David A |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/17309248$$D View this record in MEDLINE/PubMed |
| BookMark | eNptkcluFDEQhi0URBY48ALIQgKJwxC3tx4fJ0MyIBKWLBI3y-2umTjpbjdelPD2OJpJIgVOtX31q-x_F20NfgCEXlfkY0VotW-dJIRzvnqGdirB1URJ8mvrPhdKbqPdGK8IYUxJ-gJtVzUjivLpDro5hTFAhCG5YYXnXY4JQsQX8a40-MTcuj73eO773g_4sF0BPstNTCHblAPgWbfywaXLHs_GsXPQ4uTxKbTZlnQRzHgZsRlafOI7sLkzYdN8iZ4vTRfh1SbuoYujw_P558nx98WX-ex4Ylg9TRNbNSCpVKYWrZpOORekAUtlzRsFktW0VkJAI0VjSm1la7kitC3z2sCSN2wPvV_rjsH_zhCT7l200HVmAJ-jrgkjQjFawLdPwCufw1Bu07SSVMiaqQK92UC56aHVY3C9CX_0_X8W4MMasMHHGGD5iBB955V-8Kqw-09Y65JJzg8pGNf9d2Oy3nDFpdsHaROudTmvFvr8x5n-yRYH3z59Vfqg8O_WvLHx8Tn_6v4FQ3mxAg |
| CitedBy_id | crossref_primary_10_1177_1535370218755659 crossref_primary_10_1093_bioinformatics_btw523 crossref_primary_10_1002_chin_200724188 crossref_primary_10_1016_j_scib_2020_04_006 crossref_primary_10_1093_database_bat044 crossref_primary_10_1134_S1070363210120248 crossref_primary_10_1021_acs_jmedchem_7b01890 crossref_primary_10_1021_acs_jcim_5b00036 crossref_primary_10_1186_1758_2946_1_12 crossref_primary_10_1021_ci900078h crossref_primary_10_1021_ci4004464 crossref_primary_10_1186_1758_2946_5_S1_P17 crossref_primary_10_1186_1758_2946_6_S1_O18 crossref_primary_10_1186_s13321_016_0127_5 crossref_primary_10_1002_minf_201500004 crossref_primary_10_1021_jm801098a crossref_primary_10_1021_ci400442f crossref_primary_10_1021_ci8000502 crossref_primary_10_1021_ci8000887 crossref_primary_10_1016_j_wpi_2019_03_006 crossref_primary_10_1021_ci100484z crossref_primary_10_1093_nar_gkx384 crossref_primary_10_1186_1758_2946_4_S1_P44 crossref_primary_10_1021_acs_jcim_6b00174 crossref_primary_10_1186_s13321_024_00875_4 crossref_primary_10_1021_ci4007547 crossref_primary_10_1021_ci800250r |
| Cites_doi | 10.1021/ci049860f 10.1021/ci050011h 10.1021/ci025592e 10.1021/ci0496954 10.1021/ci9803381 10.1021/ci050347r 10.1021/jm049740z 10.1023/A:1008068904628 10.2174/1568026053828411 10.1021/ci0502247 10.1021/ci0255937 10.1021/ci050465e 10.1021/ci010381f 10.1093/comjnl/45.6.631 10.1021/ci00010a009 10.1021/jm049032d 10.1021/jm040213p |
| ContentType | Journal Article |
| Copyright | Copyright © 2007 American Chemical Society Copyright American Chemical Society Mar 2007 |
| Copyright_xml | – notice: Copyright © 2007 American Chemical Society – notice: Copyright American Chemical Society Mar 2007 |
| DBID | BSCLL AAYXX CITATION CGR CUY CVF ECM EIF NPM 7SC 7SR 7U5 8BQ 8FD JG9 JQ2 L7M L~C L~D 7X8 |
| DOI | 10.1021/ci600444g |
| DatabaseName | Istex CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Computer and Information Systems Abstracts Engineered Materials Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database Materials Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional MEDLINE - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Materials Research Database Engineered Materials Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest Computer Science Collection Computer and Information Systems Abstracts Solid State and Superconductivity Abstracts Advanced Technologies Database with Aerospace METADEX Computer and Information Systems Abstracts Professional MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE Materials Research Database |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Chemistry |
| EISSN | 1549-960X |
| EndPage | 366 |
| ExternalDocumentID | 1245507051 17309248 10_1021_ci600444g ark_67375_TPS_Q3GBNDK9_B h84800874 |
| Genre | Research Support, Non-U.S. Gov't Journal Article Feature |
| GroupedDBID | - 4.4 55A 5GY 5VS 7~N AABXI ABFLS ABMVS ABUCX ACGFS ACIWK ACNCT ACS AEESW AENEX AFEFF ALMA_UNASSIGNED_HOLDINGS ANTXH AQSVZ D0L DU5 EBS ED ED~ EJD F5P GNL IH9 IHE JG JG~ LG6 OHM P2P PQEST PQQKQ RNS ROL UI2 UQL VF5 VG9 W1F X --- -~X ABJNI ABQRX ADHLV AHGAQ BSCLL CUPRZ GGK AAYXX ABBLG ABLBI ACRPL ADNMO AEYZD AGQPQ ANPPW CITATION 1WB 53G CGR CUY CVF ECM EIF NPM 7SC 7SR 7U5 8BQ 8FD JG9 JQ2 L7M L~C L~D 7X8 |
| ID | FETCH-LOGICAL-a378t-c1be6269a75d9884450bec2674b9e63727955eb65ba9e6c6dc4902d6747aef4b3 |
| IEDL.DBID | ACS |
| ISSN | 1549-9596 |
| IngestDate | Fri Jul 11 14:11:08 EDT 2025 Mon Jun 30 11:01:46 EDT 2025 Wed Feb 19 01:44:08 EST 2025 Tue Jul 01 03:25:23 EDT 2025 Thu Apr 24 22:54:33 EDT 2025 Wed Oct 30 09:28:04 EDT 2024 Thu Aug 27 13:42:21 EDT 2020 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 2 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-a378t-c1be6269a75d9884450bec2674b9e63727955eb65ba9e6c6dc4902d6747aef4b3 |
| Notes | istex:215268F05471EECFFCF9B62A5C227795F5897B22 ark:/67375/TPS-Q3GBNDK9-B SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| PMID | 17309248 |
| PQID | 216256739 |
| PQPubID | 28739 |
| PageCount | 13 |
| ParticipantIDs | proquest_miscellaneous_70305932 proquest_journals_216256739 pubmed_primary_17309248 crossref_primary_10_1021_ci600444g crossref_citationtrail_10_1021_ci600444g istex_primary_ark_67375_TPS_Q3GBNDK9_B acs_journals_10_1021_ci600444g |
| ProviderPackageCode | JG~ 55A AABXI GNL VF5 7~N VG9 W1F ANTXH ACS AEESW AFEFF ABMVS ABUCX IH9 AQSVZ ED~ UI2 CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2007-03-01 |
| PublicationDateYYYYMMDD | 2007-03-01 |
| PublicationDate_xml | – month: 03 year: 2007 text: 2007-03-01 day: 01 |
| PublicationDecade | 2000 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: Washington |
| PublicationTitle | Journal of chemical information and modeling |
| PublicationTitleAlternate | J. Chem. Inf. Model |
| PublicationYear | 2007 |
| Publisher | American Chemical Society |
| Publisher_xml | – name: American Chemical Society |
| References | Echem (ci600444gb00019/ci600444gb00019_1) 2006 Stahl M. (ci600444gb00003/ci600444gb00003_1) 2005; 48 ci600444gb00021/ci600444gb00021_1 Butina D (ci600444gb00007/ci600444gb00007_1) 1999; 39 Barker E. J. (ci600444gb00013/ci600444gb00013_1) 2006; 46 Lajiness M. S. (ci600444gb00001/ci600444gb00001_1) 2004; 47 Wolohan P. R. N. (ci600444gb00005/ci600444gb00005_1) 2006; 46 ci600444gb00009/ci600444gb00009_1 Raymond J. W. (ci600444gb00002/ci600444gb00002_1) 2002; 42 Rarey M. (ci600444gb00014/ci600444gb00014_1) 1998; 12 Davis A. M. (ci600444gb00020/ci600444gb00020_1) 2005; 5 Wilkens S. J. (ci600444gb00004/ci600444gb00004_1) 2005; 48 Barker E. J. (ci600444gb00010/ci600444gb00010_1) 2003; 43 Birchall K. (ci600444gb00012/ci600444gb00012_1) 2006; 46 Raymond J. W. (ci600444gb00024/ci600444gb00024_1) 2002; 16 Takahashi Y. (ci600444gb00016/ci600444gb00016_1) 1992; 32 Harper G. (ci600444gb00015/ci600444gb00015_1) 2004; 44 Figueras J (ci600444gb00018/ci600444gb00018_1) 1996; 36 Kibbey C. (ci600444gb00027/ci600444gb00027_1) 2005; 45 Qt (ci600444gb00026/ci600444gb00026_1) 2006 Stahl M. (ci600444gb00006/ci600444gb00006_1) 2005; 45 Raymond J. W. (ci600444gb00008/ci600444gb00008_1) 2005; 45 Gillet V. J. (ci600444gb00011/ci600444gb00011_1) 2003; 43 ci600444gb00017/ci600444gb00017_1 Matlab (ci600444gb00022/ci600444gb00022_1) 2006 Raymond J. W. (ci600444gb00023/ci600444gb00023_1) 2002; 45 |
| References_xml | – volume: 44 start-page: 2156 year: 2004 ident: ci600444gb00015/ci600444gb00015_1 publication-title: J. Chem. Inf. Comput. Sci doi: 10.1021/ci049860f – volume: 45 start-page: 548 year: 2005 ident: ci600444gb00006/ci600444gb00006_1 publication-title: J. Chem. Inf. Model doi: 10.1021/ci050011h – volume: 43 start-page: 345 year: 2003 ident: ci600444gb00011/ci600444gb00011_1 publication-title: J. Chem. Inf. Comput. Sci doi: 10.1021/ci025592e – volume: 45 start-page: 532 year: 2005 ident: ci600444gb00027/ci600444gb00027_1 publication-title: J. Chem. Inf. Model doi: 10.1021/ci0496954 – volume: 39 start-page: 750 year: 1999 ident: ci600444gb00007/ci600444gb00007_1 publication-title: J. Chem. Inf. Comput. Sci doi: 10.1021/ci9803381 – volume: 46 start-page: 511 year: 2006 ident: ci600444gb00013/ci600444gb00013_1 publication-title: J. Chem. Inf. Model doi: 10.1021/ci050347r – volume: 47 start-page: 4896 year: 2004 ident: ci600444gb00001/ci600444gb00001_1 publication-title: J. Med. Chem doi: 10.1021/jm049740z – ident: ci600444gb00009/ci600444gb00009_1 – volume: 12 start-page: 490 issue: 5 year: 1998 ident: ci600444gb00014/ci600444gb00014_1 publication-title: J. Comput.-Aided Mol. Des doi: 10.1023/A:1008068904628 – volume: 5 start-page: 439 year: 2005 ident: ci600444gb00020/ci600444gb00020_1 publication-title: Curr. Top. Med. Chem doi: 10.2174/1568026053828411 – ident: ci600444gb00017/ci600444gb00017_1 – volume-title: version 4.1 year: 2006 ident: ci600444gb00026/ci600444gb00026_1 – volume: 45 start-page: 1204 year: 2005 ident: ci600444gb00008/ci600444gb00008_1 publication-title: J. Chem. Inf. Model doi: 10.1021/ci0502247 – volume-title: http://www.eyesopen.com (accessed year: 2006 ident: ci600444gb00019/ci600444gb00019_1 – ident: ci600444gb00021/ci600444gb00021_1 – volume: 43 start-page: 356 year: 2003 ident: ci600444gb00010/ci600444gb00010_1 publication-title: J. Chem. Inf. Comput. Sci doi: 10.1021/ci0255937 – volume: 46 start-page: 1193 year: 2006 ident: ci600444gb00005/ci600444gb00005_1 publication-title: J. Chem. Inf. Model – volume: 36 start-page: 991 year: 1996 ident: ci600444gb00018/ci600444gb00018_1 publication-title: J. Chem. Inf. Comput. Sci – volume: 46 start-page: 586 year: 2006 ident: ci600444gb00012/ci600444gb00012_1 publication-title: J. Chem. Inf. Model doi: 10.1021/ci050465e – volume: 42 start-page: 316 year: 2002 ident: ci600444gb00002/ci600444gb00002_1 publication-title: J. Chem. Inf. Comput. Sci doi: 10.1021/ci010381f – volume: 45 start-page: 644 year: 2002 ident: ci600444gb00023/ci600444gb00023_1 publication-title: Comput. J doi: 10.1093/comjnl/45.6.631 – volume: 32 start-page: 643 year: 1992 ident: ci600444gb00016/ci600444gb00016_1 publication-title: J. Chem. Inf. Comput. Sci doi: 10.1021/ci00010a009 – volume: 48 start-page: 3193 year: 2005 ident: ci600444gb00004/ci600444gb00004_1 publication-title: J. Med. Chem doi: 10.1021/jm049032d – volume: 16 start-page: 533 year: 2002 ident: ci600444gb00024/ci600444gb00024_1 publication-title: J. Comput.-Aided Mol. Des – volume-title: version 7.1 year: 2006 ident: ci600444gb00022/ci600444gb00022_1 – volume: 48 start-page: 4366 year: 2005 ident: ci600444gb00003/ci600444gb00003_1 publication-title: J. Med. Chem doi: 10.1021/jm040213p |
| SSID | ssj0033962 |
| Score | 1.987345 |
| Snippet | Chemical databases are routinely clustered, with the aim of grouping molecules which share similar structural features. Ideally, medicinal chemists are then... |
| SourceID | proquest pubmed crossref istex acs |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 354 |
| SubjectTerms | Algorithms Analytical chemistry Cluster Analysis Computational Biology Graphs Molecular Structure |
| Title | Representing Clusters Using a Maximum Common Edge Substructure Algorithm Applied to Reduced Graphs and Molecular Graphs |
| URI | http://dx.doi.org/10.1021/ci600444g https://api.istex.fr/ark:/67375/TPS-Q3GBNDK9-B/fulltext.pdf https://www.ncbi.nlm.nih.gov/pubmed/17309248 https://www.proquest.com/docview/216256739 https://www.proquest.com/docview/70305932 |
| Volume | 47 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV1Lb9QwEB6V9gAXaHmmLcUChLik3Ti2Ex_b7UugraAPqbfITpxl1d2k2iSi4tczdpItqC3ckngiOf7G43E88w3Axzzn6JezwBc0YD5jXPtS0NjnqciEUWEYMZuNPDoRxxfsyyW_XIIPD5zg02AnnQhHajZ-BCtUoHpZ_2d41pvbMJSuaqilGvMll6KnD_rzVbv0pNVfS8-KHcWbh_1Kt74cPoP9PkunDSu52m5qvZ3-ukva-K-ur8LTzr8ku61CrMGSKZ7D42Ff1u0F_Dx1sa_GVYggw2ljmRIq4kIHiCIjdTOZNTNiE0fKghxkY0OscXE0s83ckN3puJxP6h8z0jmwpC7JqSWAxcsjS39dEVVkZNTX3e0evoSLw4Pz4bHfVV_wVRjFtZ8G2uBuR6qIZzKOEcYB4k0FgieNCNHvkZwbLbhWeI_QpkwOaIbtkTI50-ErWC7KwrwBogZG0jjP84EWTEVCc200C_PU2LxaHniwhfAk3eypEncwToNkMX4efO6Rw4dtjIItoTG9T_T9QvS6Jey4T-iTg38hoeZXNsIt4sn5t7Pke3i0d7L_VSZ7Hmz0-nHbPRrgphGlpQfvFq2Ioj1qUYUpmypxdhRdYw9et0p12xc0qbjnjdf_980b8KT9j2zj3TZhGXE2b9EBqvWWmwC_AenZ_cE |
| linkProvider | American Chemical Society |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3db5swED9t7UP3su8P2q21pmnaC20A2-DHNGubrU20tanUN2SDyaImUAXQqv31OxtItqnT9gb4QGff-XzGd78DeJdlDP1y6rnc96hLKVOu4H7ksoSnXMsgCKnJRh6N-fCSfr5iVy1MjsmFQSZK_FJpD_HX6ALeQTLjFttseh820QnxTZmG_uCis7pBIGzxUIM45gomeIci9OurZgVKyt9WoE0zmLd_dy_tMnP8qKlXZBm00SXX-3Wl9pMff2A3_l8PHsPD1tsk_UY9nsA9nT-FrUFX5O0ZfD-3kbDa1osgg3ltcBNKYgMJiCQjeTtb1Ati0kiKnBylU02MqbGgs_VSk_58Wixn1bcFad1ZUhXk3MDB4uWJAcMuicxTMuqq8LYPn8Pl8dFkMHTbWgyuDMKochNPadz7CBmyVEQRCrWH0vc5ilJoHqAXJBjTijMl8R4FnVDR81NsD6XOqApewEZe5PoVENnTwo-yLOspTmXIFVNa0SBLtMmyZZ4Duzh8cTuXytgek_tevBo_Bz50AsSHTcSCKagxv4v07Yr0poHvuIvovdWCFYVcXpt4t5DFky8X8dfg5HD88VTEhw7sdGqyZs_3cAuJ1MKBvVUrStEcvMhcF3UZW6uKjrIDLxvdWvOCBhZ3wNH2v_q8B1vDyegsPvs0Pt2BB80fZhMJ9xo2UOb6DbpGldq1c-Inw4kGMQ |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB5BKwEX3o9QaC2EEJeUTWI78XG77bZQdil9SL1FduIsq-4m1SYRFb-esfMooCK4JfEkGnvG45l4_A3A2yxj6JdTz-W-R11KmXIF9yOXJTzlWgZBSM1p5MmUH5zRT-fsvA0UzVkYZKLEL5V2E9_M6ss0axEGvA_JnFt8s9ltWDfbdaZUw3B00lneIBC2gKhBHXMFE7xDEvr1VbMKJeVvq9C6GdCrv7uYdqkZP4AvPZM2w-Riu67UdvLjD_zG_-_FQ7jfep1k2KjJI7il88dwd9QVe3sC349tRqy2dSPIaFEb_ISS2IQCIslEXs2X9ZKY4yRFTvbSmSbG5Fjw2XqlyXAxK1bz6tuStG4tqQpybGBh8XLfgGKXROYpmXTVeNuHT-FsvHc6OnDbmgyuDMKochNPaYyBhAxZKqIIhTtALfA5ilRoHqA3JBjTijMl8R4FnlAx8FNsD6XOqAqewVpe5PoFEDnQwo-yLBsoTmXIFVNa0SBLtDltyzwHNnEI43ZOlbHdLve9uB8_B953QsSHTeaCKayxuIn0TU962cB43ET0zmpCTyFXFybvLWTx6dFJ_DXY35nuHop4x4GNTlWu2fM9DCWRWjiw1beiFM0GjMx1UZexta7oMDvwvNGva17Q0GIkHL38V5-34M7R7jj-_HF6uAH3mh_NJiHuFayhyPVr9JAqtWmnxU9OHgi0 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Representing+clusters+using+a+maximum+common+edge+substructure+algorithm+applied+to+reduced+graphs+and+molecular+graphs&rft.jtitle=Journal+of+chemical+information+and+modeling&rft.au=Gardiner%2C+Eleanor+J&rft.au=Gillet%2C+Valerie+J&rft.au=Willett%2C+Peter&rft.au=Cosgrove%2C+David+A&rft.date=2007-03-01&rft.issn=1549-9596&rft.volume=47&rft.issue=2&rft.spage=354&rft_id=info:doi/10.1021%2Fci600444g&rft_id=info%3Apmid%2F17309248&rft.externalDocID=17309248 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1549-9596&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1549-9596&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1549-9596&client=summon |