Literature DB >> 22571406

Introducing the LASSO graph for compound data set representation and structure-activity relationship analysis.

Disha Gupta-Ostermann1, Ye Hu, Jürgen Bajorath.   

Abstract

A graphical method is introduced for compound data mining and structure-activity relationship (SAR) data analysis that is based upon a canonical structural organization scheme and captures a compound-scaffold-skeleton hierarchy. The graph representation has a constant layout, integrates compound activity data, and provides direct access to SAR information. Characteristic SAR patterns that emerge from the graph are easily identified. The molecular hierarchy enables "forward-backward" analysis of compound data and reveals both global and local SAR patterns. For example, in heterogeneous data sets, compound series are immediately identified that convey interpretable SAR information in isolation or in the structural context of related series, which often define SAR pathways through data sets.

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Year:  2012        PMID: 22571406     DOI: 10.1021/jm3004762

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  3 in total

1.  Systematic mining of analog series with related core structures in multi-target activity space.

Authors:  Disha Gupta-Ostermann; Ye Hu; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2013-08-24       Impact factor: 3.686

2.  Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications.

Authors:  Ye Hu; Jurgen Bajorath
Journal:  F1000Res       Date:  2012-08-14

3.  Follow up: Compound data sets and software tools for chemoinformatics and medicinal chemistry applications: update and data transfer.

Authors:  Ye Hu; Jürgen Bajorath
Journal:  F1000Res       Date:  2014-03-11
  3 in total

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