Can Ai Revolutionize Qspr Models for the Chemical Mixtures Hazards?
Chemical Engineering TransactionsThe physical hazards of chemical mixtures are typically characterized using experimental tools that could benefit to be prioritized by using predictive methods.
Guillaume Fayet +2 more
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Structure-efficiency relationship of access group antibiotics via SK chromatic descriptors. [PDF]
Front ChemRajambigai R, Praveen T, Ravi Sankar J.
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Biological communication via molecular surfaces [PDF]
, 2006 Byler, K., Clark, Tim, De Groot, M.
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CORAL: the prediction of biodegradation of organic compounds with optimal SMILES-based descriptors
Open Chemistry, 2012 Toropov Andrey +6 more
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From graph theory to chemoinformatics: modified bond-based indices and a hypothesis-driven multi-task QSAR/QSPR benchmark. [PDF]
Sci RepAltairi A +3 more
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Enhancing bioinformatics engineering by utilizing graph therapeutic properties for clinically approved antitoxin drugs in zoonotic diseases. [PDF]
Sci RepImran M, Aqib M, Malik MA, Jutt S.
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Machine learning-based QSPR modeling for predicting the <i>n</i>-octanol/air partition coefficient of polybrominated diphenyl ethers. [PDF]
iScienceWu W +7 more
europepmc +1 more source
Predictive modeling for physicochemical properties of β-lactam antibiotics through eigenvalue based topological indices and non linear regression techniques. [PDF]
Sci RepYuvaraj A +4 more
europepmc +1 more source
7th German Conference on Chemoinformatics: 25 CIC-Workshop : Goslar, Germany, 6 - 8 November 2011 ; meeting abstracts / Edited by Frank Oellien, Uli Fechner and Thomas Engel [PDF]
, 2012 Engel, Thomas +2 more
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