Impact of high-throughput screening in biomedical research

By R. Macarron, M. Banks, D. Bojanic, David J. Burns, D. A. Cirovic, T. Garyantes, D. Green, R. Hertzberg, W. Janzen, J. Paslay and 2 more. Nature reviews. Drug discovery, 2011

1,226 citations recorded by the source corpus.

Subfields: Biophysics, Computational Theory and Mathematics, Immunology

View Paper: https://www.semanticscholar.org/paper/5d511943840188d090868d8b74a027983e051da3

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Citations in the corpus

Structure-based drug screening for G-protein-coupled receptors. (2012, background): “Gribbon P, Sewing A. High-throughput drug discovery: what can we expect from HTS?”
NATURAL PRODUCTS: A CONTINUING SOURCE OF NOVEL DRUG LEADS (2013, background): “, (also from GSK) when looking at different disease targets [247].”
Machine learning approaches to drug response prediction: challenges and recent progress (2020, background): “Since then, high-throughput in vitro drug screens of cancer cell lines (CCLs) derived by immortalization of human cancer cells became popular experimental bases for discovery of multi-omic underpinnings of drug sensitivity and resistance 16 .”
Small-Molecule Library Subset Screening as an Aid for Accelerating Lead Identification (2014, background): “Compounds in the library fall into three main categories: (1) individual compounds from commercial sources, (2) groups of commercial compounds synthesized around specific chemical scaffolds (these sets number from tens of compounds to more than a thousand compounds), and (3) compounds synthesized fo”
Open Graph Benchmark: Datasets for Machine Learning on Graphs (2020, neutral): “…protein associations that are measured experimentally by a high-throughput technology ( e.g. , cost-effective, automated experiments that make large scale repetition feasible (Macarron et al., 2011; Bajorath, 2002; Younger et al., 2017)) or are obtained computationally ( e.g. , via text-mining).”
Ferroptosis: an iron-dependent form of nonapoptotic cell death. (2012, methodology): “To overcome the inherent limitations of many individual small-molecule collections (Macarron et al., 2011), we assembled a custom screening library of 9,517 small molecules derived from a starting pool of 3,372,615 commercially available compounds that were filtered in silico on the basis of drug…”
Role of computer-aided drug design in modern drug discovery (2015, background): “…to be a big part of the drug discovery process in the pharmaceutical industry due to its high success rate, lack of primary understanding of the molecular mechanism behind the activity of the identiﬁed hits can hamper the search of promising candidates (Macarron et al. 2011; Lionta et al. 2014).”