Detalhe da pesquisa
1.
Best practice and reproducible science are required to advance artificial intelligence in real-world applications.
Brief Bioinform
; 23(4)2022 07 18.
Artigo
em Inglês
| MEDLINE | ID: mdl-35848999
2.
PLM-ARG: antibiotic resistance gene identification using a pretrained protein language model.
Bioinformatics
; 39(11)2023 11 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-37995287
3.
A framework enabling LLMs into regulatory environment for transparency and trustworthiness and its application to drug labeling document.
Regul Toxicol Pharmacol
; 149: 105613, 2024 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-38570021
4.
TransOrGAN: An Artificial Intelligence Mapping of Rat Transcriptomic Profiles between Organs, Ages, and Sexes.
Chem Res Toxicol
; 36(6): 916-925, 2023 06 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-37200521
5.
Classifying Free Texts Into Predefined Sections Using AI in Regulatory Documents: A Case Study with Drug Labeling Documents.
Chem Res Toxicol
; 36(8): 1290-1299, 2023 08 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-37487037
6.
A Weakly Supervised Deep Learning Framework for Whole Slide Classification to Facilitate Digital Pathology in Animal Study.
Chem Res Toxicol
; 36(8): 1321-1331, 2023 08 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-37540590
7.
DeepAmes: A deep learning-powered Ames test predictive model with potential for regulatory application.
Regul Toxicol Pharmacol
; 144: 105486, 2023 Oct.
Artigo
em Inglês
| MEDLINE | ID: mdl-37633327
8.
Development of benchmark datasets for text mining and sentiment analysis to accelerate regulatory literature review.
Regul Toxicol Pharmacol
; 137: 105287, 2023 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-36372266
9.
Artificial intelligence and real-world data for drug and food safety - A regulatory science perspective.
Regul Toxicol Pharmacol
; 140: 105388, 2023 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-37061083
10.
Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic Testing in Rare Diseases: Where Are We?
Trends Genet
; 35(11): 852-867, 2019 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-31623871
11.
A comprehensive rat transcriptome built from large scale RNA-seq-based annotation.
Nucleic Acids Res
; 48(15): 8320-8331, 2020 09 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-32749457
12.
R-ODAF: Omics data analysis framework for regulatory application.
Regul Toxicol Pharmacol
; 131: 105143, 2022 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-35247516
13.
Landscape of circRNAs Across 11 Organs and 4 Ages in Fischer 344 Rats.
Chem Res Toxicol
; 34(2): 240-246, 2021 02 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-32692164
14.
Impact of Sequencing Depth and Library Preparation on Toxicological Interpretation of RNA-Seq Data in a "Three-Sample" Scenario.
Chem Res Toxicol
; 34(2): 529-540, 2021 02 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-33354967
15.
DeepDILI: Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation.
Chem Res Toxicol
; 34(2): 550-565, 2021 02 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-33356151
16.
Trade-off Predictivity and Explainability for Machine-Learning Powered Predictive Toxicology: An in-Depth Investigation with Tox21 Data Sets.
Chem Res Toxicol
; 34(2): 541-549, 2021 02 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-33513003
17.
Development of a Battery of In Silico Prediction Tools for Drug-Induced Liver Injury from the Vantage Point of Translational Safety Assessment.
Chem Res Toxicol
; 34(2): 601-615, 2021 02 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-33356149
18.
Regulatory landscape of nanotechnology and nanoplastics from a global perspective.
Regul Toxicol Pharmacol
; 122: 104885, 2021 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-33617940
19.
Coordinated Regulation of UGT2B15 Expression by Long Noncoding RNA LINC00574 and hsa-miR-129-5p in HepaRG Cells.
Drug Metab Dispos
; 48(4): 297-306, 2020 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-32086297
20.
Can Transcriptomic Profiles from Cancer Cell Lines Be Used for Toxicity Assessment?
Chem Res Toxicol
; 33(1): 271-280, 2020 01 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-31808688