Journal Article

ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics

Ashby, Thomas J., Georgiev, Ivan, Jeliazkov, Vedrin, Kochev, Nikolay, Golib-Dzib, Jose-Felipe, Chupakhin, Vladimir, Carlsson, Lars, Engkvist, Ola, Ceulemans, Hugo, Jeliazkova, Nina, Chen, Hongming, Sun, Jiangming, Wegner, Jörg

2017

Overview

Chemogenomics data generally refers to the activity data of chemical compounds on an array of protein targets and represents an important source of information for building in silico target prediction models. The increasing volume of chemogenomics data offers exciting opportunities to build models based on Big Data. Preparing a high quality data set is a vital step in realizing this goal and this work aims to compile such a comprehensive chemogenomics dataset. This dataset comprises over 70 million SAR data points from publicly available databases (PubChem and ChEMBL) including structure, target information and activity annotations. Our aspiration is to create a useful chemogenomics resource reflecting industry-scale data not only for building predictive models of in silico polypharmacology and off-target effects but also for the validation of cheminformatics approaches in general.

• Publisher: Springer International Publishing,BioMed Central Ltd,Springer Nature B.V
• Subject: Annotations / Big Data / Chemical compounds / Chemistry / Chemistry and Materials Science / Chemogenomics / Computational Biology/Bioinformatics / Computational chemistry / Computer Applications in Chemistry / Data analysis / Data management / Data points / Data processing / Datasets / Documentation and Information in Chemistry / Informatics / Management / Mathematical models / Observations / Prediction models / Protein arrays / Protein-protein interactions / Technology application / Theoretical and Computational Chemistry