Literature DB >> 15807518

Molecular Property eXplorer: a novel approach to visualizing SAR using tree-maps and heatmaps.

Christopher Kibbey1, Alain Calvet.   

Abstract

The tremendous increase in chemical structure and biological activity data brought about through combinatorial chemistry and high-throughput screening technologies has created the need for sophisticated graphical tools for visualizing and exploring structure-activity data. Visualization plays an important role in exploring and understanding relationships within such multidimensional data sets. Many chemoinformatics software applications apply standard clustering techniques to organize structure-activity data, but they differ significantly in their approaches to visualizing clustered data. Molecular Property eXplorer (MPX) is unique in its presentation of clustered data in the form of heatmaps and tree-maps. MPX employs agglomerative hierarchical clustering to organize data on the basis of the similarity between 2D chemical structures or similarity across a predefined profile of biological assay values. Visualization of hierarchical clusters as tree-maps and heatmaps provides simultaneous representation of cluster members along with their associated assay values. Tree-maps convey both the spatial relationship among cluster members and the value of a single property (activity) associated with each member. Heatmaps provide visualization of the cluster members across an activity profile. Unlike a tree-map, however, a heatmap does not convey the spatial relationship between cluster members. MPX seamlessly integrates tree-maps and heatmaps to represent multidimensional structure-activity data in a visually intuitive manner. In addition, MPX provides tools for clustering data on the basis of chemical structure or activity profile, displaying 2D chemical structures, and querying the data based over a specified activity range, or set of chemical structure criteria (e.g., Tanimoto similarity, substructure match, and "R-group" analysis).

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Year:  2005        PMID: 15807518     DOI: 10.1021/ci0496954

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  11 in total

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Review 4.  In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling.

Authors:  S Ekins; J Mestres; B Testa
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5.  Fragment virtual screening based on Bayesian categorization for discovering novel VEGFR-2 scaffolds.

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6.  Extracting SAR Information from a Large Collection of Anti-Malarial Screening Hits by NSG-SPT Analysis.

Authors:  Mathias Wawer; Jürgen Bajorath
Journal:  ACS Med Chem Lett       Date:  2011-01-05       Impact factor: 4.345

7.  Scaffold diversity of exemplified medicinal chemistry space.

Authors:  Sarah R Langdon; Nathan Brown; Julian Blagg
Journal:  J Chem Inf Model       Date:  2011-08-31       Impact factor: 4.956

8.  shinyheatmap: Ultra fast low memory heatmap web interface for big data genomics.

Authors:  Bohdan B Khomtchouk; James R Hennessy; Claes Wahlestedt
Journal:  PLoS One       Date:  2017-05-11       Impact factor: 3.240

9.  Statistical properties of multivariate distance matrix regression for high-dimensional data analysis.

Authors:  Matthew A Zapala; Nicholas J Schork
Journal:  Front Genet       Date:  2012-09-27       Impact factor: 4.599

10.  MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps.

Authors:  Bohdan B Khomtchouk; James R Hennessy; Claes Wahlestedt
Journal:  BMC Bioinformatics       Date:  2016-09-22       Impact factor: 3.169

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