Jurgen Bajorath
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Explore the profile of Jurgen Bajorath including associated specialties, affiliations and a list of published articles.
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580
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7023
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Recent Articles
11.
12.
Panzarella G, Gallo A, Coecke S, Querci M, Ortuso F, Hofmann-Apitius M, et al.
Eur J Med Chem
. 2024 May;
273:116522.
PMID: 38801799
The growing number of scientific papers and document sources underscores the need for methods capable of evaluating the quality of publications. Researchers who are looking for relevant papers for their...
13.
Lamens A, Bajorath J
RSC Med Chem
. 2024 May;
15(5):1547-1555.
PMID: 38784468
Most machine learning (ML) methods produce predictions that are hard or impossible to understand. The black box nature of predictive models obscures potential learning bias and makes it difficult to...
14.
Chen H, Bajorath J
J Cheminform
. 2024 May;
16(1):55.
PMID: 38778425
Deep learning models adapted from natural language processing offer new opportunities for the prediction of active compounds via machine translation of sequential molecular data representations. For example, chemical language models...
15.
Xerxa E, Bajorath J
Eur J Med Chem
. 2024 Apr;
271:116413.
PMID: 38636127
The continued growth of data from biological screening and medicinal chemistry provides opportunities for data-driven experimental design and decision making in early-phase drug discovery. Approaches adopted from data science help...
16.
Mastropietro A, Bajorath J
STAR Protoc
. 2024 Apr;
5(2):103010.
PMID: 38607924
Shapley values from cooperative game theory are adapted for explaining machine learning predictions. For large feature sets used in machine learning, Shapley values are approximated. We present a protocol for...
17.
Mobasher M, Vogt M, Xerxa E, Bajorath J
Biomolecules
. 2024 Mar;
14(3).
PMID: 38540679
Protein kinases (PKs) are involved in many intracellular signal transduction pathways through phosphorylation cascades and have become intensely investigated pharmaceutical targets over the past two decades. Inhibition of PKs using...
18.
Roth J, Bajorath J
Sci Rep
. 2024 Mar;
14(1):6536.
PMID: 38503823
The assessment of prediction variance or uncertainty contributes to the evaluation of machine learning models. In molecular machine learning, uncertainty quantification is an evolving area of research where currently no...
19.
Bajorath J
Mol Inform
. 2023 Nov;
43(1):e202300288.
PMID: 38010610
In drug discovery, chemical language models (CLMs) originating from natural language processing offer new opportunities for molecular design. CLMs have been developed using recurrent neural network (RNN) or transformer architectures....
20.
Lamens A, Bajorath J
ChemMedChem
. 2023 Nov;
19(3):e202300586.
PMID: 37983655
The use of black box machine learning models whose decisions cannot be understood limits the acceptance of predictions in interdisciplinary research and camouflages artificial learning characteristics leading to predictions for...