| Transparency and reproducibility in artificial intelligence B Haibe-Kains, G Alexandru Adam, A Hosny, F Khodakarami, ... Nature 586 (2020), pages E14–E16, 2020 | 423 | 2020 |
| DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans M Chen, A Suzuki, S Thakkar, K Yu, C Hu, W Tong Drug discovery today 21 (4), 648-653, 2016 | 372 | 2016 |
| Reporting guidelines for human microbiome research: the STORMS checklist C Mirzayi, A Renson, Genomic Standards Consortium, ... Nature medicine 27 (11), 1885-1892, 2021 | 285 | 2021 |
| Regulatory landscape of dietary supplements and herbal medicines from a global perspective S Thakkar, E Anklam, A Xu, F Ulberth, J Li, B Li, M Hugas, N Sarma, ... Regulatory Toxicology and Pharmacology 114, 104647, 2020 | 229 | 2020 |
| Drug-induced liver injury severity and toxicity (DILIst): binary classification of 1279 drugs by human hepatotoxicity S Thakkar, T Li, Z Liu, L Wu, R Roberts, W Tong Drug discovery today, 2019 | 114 | 2019 |
| Development of decision forest models for prediction of drug-induced liver injury in humans using a large set of FDA-approved drugs H Hong, S Thakkar, M Chen, W Tong Scientific reports 7 (1), 17311, 2017 | 99 | 2017 |
| DeepDILI: deep learning-powered drug-induced liver injury prediction using model-level representation T Li, W Tong, R Roberts, Z Liu, S Thakkar Chemical research in toxicology 34 (2), 550-565, 2020 | 67 | 2020 |
| Synthesis and anti-cancer screening of novel heterocyclic-(2 H)-1, 2, 3-triazoles as potential anti-cancer agents NR Penthala, L Madhukuri, S Thakkar, NR Madadi, G Lamture, RL Eoff, ... MedChemComm 6 (8), 1535-1543, 2015 | 65 | 2015 |
| The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury S Thakkar, M Chen, H Fang, Z Liu, R Roberts, W Tong Expert review of gastroenterology & hepatology 12 (1), 31-38, 2018 | 64 | 2018 |
| Comprehensive assessments of RNA-seq by the SEQC consortium: FDA-led efforts advance precision medicine J Xu, B Gong, L Wu, S Thakkar, H Hong, W Tong Pharmaceutics 8 (1), 8, 2016 | 57 | 2016 |
| Structure-based design targeted at LOX-1, a receptor for oxidized low-density lipoprotein S Thakkar, X Wang, M Khaidakov, Y Dai, K Gokulan, JL Mehta, ... Scientific reports 5 (1), 1-11, 2015 | 56 | 2015 |
| Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA L Wu, T Ingle, Z Liu, A Zhao-Wong, S Harris, S Thakkar, G Zhou, J Yang, ... BMC bioinformatics 20, 129-139, 2019 | 53 | 2019 |
| DeepCarc: Deep learning-powered carcinogenicity prediction using model-level representation T Li, W Tong, R Roberts, Z Liu, S Thakkar Frontiers in artificial intelligence 4, 757780, 2021 | 37 | 2021 |
| Deep learning on high-throughput transcriptomics to predict drug-induced liver injury T Li, W Tong, R Roberts, Z Liu, S Thakkar Frontiers in bioengineering and biotechnology 8, 562677, 2020 | 37 | 2020 |
| Antioxidant tocols as radiation countermeasures (challenges to be addressed to use tocols as radiation countermeasures in humans) U Nukala, S Thakkar, KJ Krager, PJ Breen, CM Compadre, N Aykin-Burns Antioxidants 7 (2), 33, 2018 | 32 | 2018 |
| Molecular dynamics guided design of tocoflexol: a new radioprotectant tocotrienol with enhanced bioavailability CM Compadre, A Singh, S Thakkar, G Zheng, PJ Breen, S Ghosh, M Kiaei, ... Drug Development Research 75 (1), 10-22, 2014 | 32 | 2014 |
| Affinity improvement of a therapeutic antibody to methamphetamine and amphetamine through structure-based antibody engineering S Thakkar, N Nanaware-Kharade, R Celikel, EC Peterson, KI Varughese Scientific reports 4 (1), 3673, 2014 | 29 | 2014 |
| Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions B Gong, D Li, R Kusko, N Novoradovskaya, Y Zhang, S Wang, ... Genome biology 22, 1-23, 2021 | 28 | 2021 |
| Emerging technologies for food and drug safety W Slikker Jr, TA de Souza Lima, D Archella, JB de Silva Junior, ... Regulatory Toxicology and Pharmacology 98, 115-128, 2018 | 28 | 2018 |
| Artificial intelligence and real-world data for drug and food safety–a regulatory science perspective S Thakkar, W Slikker Jr, F Yiannas, P Silva, B Blais, KR Chng, Z Liu, ... Regulatory Toxicology and Pharmacology 140, 105388, 2023 | 26 | 2023 |
Weida TongNCTRE-mailová adresa ověřena na: FDA.HHS.gov
