Part of the book series:Methods in Molecular Biology ((MIMB,volume 1939))
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Abstract
Bioactivity data is a valuable scientific data type that needs to be findable, accessible, interoperable, and reusable (FAIR) (Wilkinson et al. Sci Data 3:160018, 2016). However, results from bioassay experiments often exist in formats that are difficult to interoperate across and reuse in follow-up research, especially when attempting to combine experimental records from many different sources. This chapter details common issues associated with the processing of large bioactivity data and methods for handling these issues in a post-processing scenario. Specifically described are observations from a recent effort (Harris,http://www.scrubchem.org, 2017) to post-process massive amounts of bioactivity data from the NIH’s PubChem Bioassay repository (Wang et al., Nucleic Acids Res 42:1075–1082, 2014).
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Authors and Affiliations
Collaborative Drug Discovery (CDD), Inc., Burlingame, CA, USA
Jason Bret Harris
- Jason Bret Harris
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Editor information
Editors and Affiliations
Department of Pathology, University of New Mexico, Albuquerque, NM, USA
Richard S. Larson
Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
Tudor I. Oprea
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Harris, J.B. (2019). Post-processing of Large Bioactivity Data. In: Larson, R., Oprea, T. (eds) Bioinformatics and Drug Discovery. Methods in Molecular Biology, vol 1939. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9089-4_3
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