PubChem's BioAssay Database

By Yanli Wang, Jewen Xiao, Tugba Onal Suzek, Jian Zhang, Jiyao Wang, Zhigang Zhou, Lianyi Han, Karen Karapetyan, S. Dracheva, Benjamin A. Shoemaker and 3 more. 2011

647 citations recorded by the source corpus.

PubChem (http://pubchem.ncbi.nlm.nih.gov) is a public repository for biological activity data of small molecules and RNAi reagents. The mission of PubChem is to deliver free and easy access to all deposited data, and to provide intuitive data analysis tools. The PubChem BioAssay database currently contains 500 000 descriptions of assay protocols, covering 5000 protein targets, 30 000 gene targets and providing over 130 million bioactivity outcomes. PubChem's bioassay data are integrated into the NCBI Entrez information retrieval system, thus making PubChem data searchable and accessible by Entrez queries. Also, as a repository, PubChem constantly optimizes and develops its deposition system answering many demands of both high- and low-volume depositors. The PubChem information platform allows users to search, review and download bioassay description and data. The PubChem platform also enables researchers to collect, compare and analyze biological test results through web-based and programmatic tools. In this work, we provide an update for the PubChem BioAssay resource, including information content growth, data model extension and new developments of data submission, retrieval, analysis and download tools.

Subfields: Computational Theory and Mathematics, Molecular Biology, Evaluation & Benchmarks, Computational Biology & Bioinformatics

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Citations in the corpus

Molecular graph convolutions: moving beyond fingerprints (2016, background): “Brieﬂy, there are 259 datasets divided into four groups indicating their source: PubChem BioAs-say (Wang et al., 2012)”
Learning Graph-Level Representation for Drug Discovery (2017, background): “When biological researches yield evidence that a particular molecule could modulate essential pathways to achieve therapeutic activity, the discovered molecule often fails as a potential drug for a number of reasons including toxicity, low activity, and low solubility(Waring et al. 2015).”
Modeling Industrial ADMET Data with Multitask Networks (2016, methodology): “We used public data from PubChem BioAssay (PCBA) [Wang et al., 2012] and the enhanced directory of useful decoys (DUD-E) [Mysinger et al., 2012], similar to the approach taken by Ramsundar et al. [2015].”
Massively Multitask Networks for Drug Discovery (2015, methodology): “The PCBA group contained 128 experiments in the PubChem BioAssay database (Wang et al., 2012).”
AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery (2015, methodology): “That work was followed by Untherhiner et al. [11, 12] and Ramsundar et al. [13] that demonstrated the MT-DNN technique scales to large biochemical databases such as PubChem Bioassays [14] and ChEMBL [15].”
The ChEMBL bioactivity database: an update (2013, background): “In addition to literature-extracted information, ChEMBL also integrates deposited screening results and bioactivity data from other key public databases [e.g. PubChem BioAssay (8)], and information about approved drugs from resources such as the U.S. Food and Drug Administration (FDA) Orange Book (9”
SMILES-BERT: Large Scale Unsupervised Pre-Training for Molecular Property Prediction (2019, background): “PCBA [26] is a group of public available dataset containing 128 datasets from PubChem [36].”
Computational Drug Repositioning: From Data to Therapeutics (2013, background): “A public resource that facilitates such screening is PubChem, 44 which contains results from thousands of screens, many of them being phenotypic ones.”
Graph convolutional networks for computational drug development and discovery (2019, methodology): “The authors evaluated their methods for biological activities from 259 datasets, which are composed of PCBA [54], the ‘maximum unbiased validation’ datasets constructed by Rohrer and Baumann [55],the enhanced directory of useful decoys [56] and the training set for the Tox21 challenge [57], in a…”
FireDB: a compendium of biological and pharmacologically relevant ligands (2013, methodology): “And finally we used PubChem (29,30) because it is one of the most complete databases of small molecules information.”
PubChem structure–activity relationship (SAR) clusters (2015, methodology): “, Sets A, B, and C) of compounds that were tested to be “non-inactive” in at least one assay archived in the PubChem BioAssay database [4] (as of September 2010).”
ChEMBL web services: streamlining access to drug discovery data and utilities (2015, methodology): “Additionally ChEMBL data is also available via other resources that integrate ChEMBL data, such as BindingDB (6) and PubChem BioAssay (7,8).”
The CompTox Chemistry Dashboard: a community data resource for environmental chemistry (2017, background): “The Bioassays tab contains two sub-tabs, one that displays Toxcast and Tox21 HTS data, if available, and the other that displays available PubChem Bioassay Data [96].”