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Tetko, I.V. ; Engkvist, O.* ; Koch, U.* ; Reymond, J.L.* ; Chen, H.*

BIGCHEM: Challenges and opportunities for big data analysis in chemistry.

Mol. Inform. 35, 615-621 (2016)
Postprint DOI PMC
Open Access Green
Creative Commons Lizenzvertrag
The increasing volume of biomedical data in chemistry and life sciences requires the development of new methods and approaches for their handling. Here, we briefly discuss some challenges and opportunities of this fast growing area of research with a focus on those to be addressed within the BIGCHEM project. The article starts with a brief description of some available resources for "Big Data" in chemistry and a discussion of the importance of data quality. We then discuss challenges with visualization of millions of compounds by combining chemical and biological data, the expectations from mining the "Big Data" using advanced machine-learning methods, and their applications in polypharmacology prediction and target de-convolution in phenotypic screening. We show that the efficient exploration of billions of molecules requires the development of smart strategies. We also address the issue of secure information sharing without disclosing chemical structures, which is critical to enable bi-party or multi-party data sharing. Data sharing is important in the context of the recent trend of "open innovation" in pharmaceutical industry, which has led to not only more information sharing among academics and pharma industries but also the so-called "precompetitive" collaboration between pharma companies. At the end we highlight the importance of education in "Big Data" for further progress of this area.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Nonlinear Dimensionality Reduction; Interference Compounds Pains; Molecule Frequent Hitters; Drug Discovery; Chemical Space; Assay Interference; Applicability Domain; Compound Libraries; Bioassay Ontology; Natural-products
ISSN (print) / ISBN 1868-1743
e-ISSN 1868-1751
Journal Molecular Informatics
Quellenangaben Volume: 35, Issue: 11-12, Pages: 615-621 Article Number: , Supplement: ,
Publisher Wiley
Publishing Place Weinheim
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Structural Biology (STB)