Exploiting drug-disease relationships for computational drug repositioning

By Joel T. Dudley, Tarangini Deshpande, Atul J. Butte. 2011

491 citations recorded by the source corpus.

Subfields: Biophysics, Computational Theory and Mathematics, Molecular Biology

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In Computational Theory and Mathematics

In Molecular Biology

Citations in the corpus

SWEETLEAD: an In Silico Database of Approved Drugs, Regulated Chemicals, and Herbal Isolates for Computer-Aided Drug Discovery (2013, neutral): “promising new therapeutic strategies[15-20].”
A review of connectivity map and computational approaches in pharmacogenomics (2017, methodology): “Therefore, the CMap approach can be used as a method of screening chemicals by matching the gene signature of a novel pertubagen against the reference profile [18, 19].”
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper (2020, background): “…usually refers to the studies that reinvestigate existing drugs that failed approval for new therapeutic indications [10], while drug repurposing suggests the application of already approved drugs and compounds to treat a different disease [11, 12].”
Computational Drug Repositioning: From Data to Therapeutics (2013, methodology): “13,14 However, because this is a rapidly developing field, we highlight (i) some of the newer methods; (ii) advances in some of the key methods that we believe are the closest to delivering benefit to patients, generally based on the extent of experimental validation and support; and (iii)methods…”
Clinical Natural Language Processing in languages other than English: opportunities and challenges (2018, methodology): “Computational methods enable clinical research and have shown great success in advancing clinical research in areas such as drug repositioning [2].”
Similarity-based machine learning methods for predicting drug-target interactions: a brief review (2014, background): “Interactions between drugs and targets (proteins) are of importance in drug research, such as facilitating the process of drug discovery [1], drug side-effect prediction [2, 3] and drug repurposing [4–6].”
A survey of current trends in computational drug repositioning (2016, background): “Depending on where the discovery comes from, these newly proposed computational methods can be categorized as either ‘drug based’ or ‘disease based’ [10].”