| Opportunities and obstacles for deep learning in biology and medicine T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ... Journal of the royal society interface 15 (141), 20170387, 2018 | 2745 | 2018 |
| Graph kernels for chemical informatics L Ralaivola, SJ Swamidass, H Saigo, P Baldi Neural networks 18 (8), 1093-1110, 2005 | 644 | 2005 |
| A survey of current trends in computational drug repositioning J Li, S Zheng, B Chen, AJ Butte, SJ Swamidass, Z Lu Briefings in bioinformatics 17 (1), 2-12, 2016 | 630 | 2016 |
| Open source drug discovery with the malaria box compound collection for neglected diseases and beyond WC Van Voorhis, JH Adams, R Adelfio, V Ahyong, MH Akabas, P Alano, ... PLoS pathogens 12 (7), e1005763, 2016 | 330 | 2016 |
| XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks J Zaretzki, M Matlock, SJ Swamidass Journal of chemical information and modeling 53 (12), 3373-3383, 2013 | 266 | 2013 |
| Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity SJ Swamidass, J Chen, J Bruand, P Phung, L Ralaivola, P Baldi ISMB (Supplement of Bioinformatics), 359-368, 2005 | 266 | 2005 |
| ChemDB: a public database of small molecules and related chemoinformatics resources J Chen, SJ Swamidass, Y Dou, J Bruand, P Baldi Bioinformatics 21 (22), 4133-4139, 2005 | 242 | 2005 |
| Modeling epoxidation of drug-like molecules with a deep machine learning network TB Hughes, GP Miller, SJ Swamidass ACS central science 1 (4), 168-180, 2015 | 240 | 2015 |
| Deep learning global glomerulosclerosis in transplant kidney frozen sections JN Marsh, MK Matlock, S Kudose, TC Liu, TS Stappenbeck, JP Gaut, ... IEEE transactions on medical imaging 37 (12), 2718-2728, 2018 | 189 | 2018 |
| ChemDB update—full-text search and virtual chemical space JH Chen, E Linstead, SJ Swamidass, D Wang, P Baldi Bioinformatics 23 (17), 2348-2351, 2007 | 168 | 2007 |
| A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval SJ Swamidass, CA Azencott, K Daily, P Baldi Bioinformatics 26 (10), 1348-1356, 2010 | 146 | 2010 |
| Mining small-molecule screens to repurpose drugs SJ Swamidass Briefings in bioinformatics 12 (4), 327-335, 2011 | 144 | 2011 |
| Structure-based inhibitor design of AccD5, an essential acyl-CoA carboxylase carboxyltransferase domain of Mycobacterium tuberculosis TW Lin, MM Melgar, D Kurth, SJ Swamidass, J Purdon, T Tseng, G Gago, ... Proceedings of the National Academy of Sciences 103 (9), 3072-3077, 2006 | 136 | 2006 |
| Mathematical correction for fingerprint similarity measures to improve chemical retrieval SJ Swamidass, P Baldi Journal of chemical information and modeling 47 (3), 952-964, 2007 | 132 | 2007 |
| Modeling reactivity to biological macromolecules with a deep multitask network TB Hughes, NL Dang, GP Miller, SJ Swamidass ACS central science 2 (8), 529-537, 2016 | 120 | 2016 |
| XenoSite server: a web-available site of metabolism prediction tool MK Matlock, TB Hughes, SJ Swamidass Bioinformatics 31 (7), 1136-1137, 2015 | 120 | 2015 |
| Site of reactivity models predict molecular reactivity of diverse chemicals with glutathione TB Hughes, GP Miller, SJ Swamidass Chemical research in toxicology 28 (4), 797-809, 2015 | 116 | 2015 |
| Bounds and algorithms for fast exact searches of chemical fingerprints in linear and sublinear time SJ Swamidass, P Baldi Journal of chemical information and modeling 47 (2), 302-317, 2007 | 111 | 2007 |
| Deep learning to predict the formation of quinone species in drug metabolism TB Hughes, SJ Swamidass Chemical research in toxicology 30 (2), 642-656, 2017 | 108 | 2017 |
| Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples EK Barnell, P Ronning, KM Campbell, K Krysiak, BJ Ainscough, LM Sheta, ... Genetics in Medicine 21 (4), 972-981, 2019 | 100 | 2019 |
Pierre BaldiProfessor, University of California, IrvineVerified email at ics.uci.edu
