BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Pawar G, Madden JC, Ebbrell D, Firman JW, Cronin MTD. In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR. Front Pharmacol 2019;10:561. [PMID: 31244651 DOI: 10.3389/fphar.2019.00561] [Cited by in Crossref: 23] [Cited by in F6Publishing: 16] [Article Influence: 7.7] [Reference Citation Analysis]
Number Citing Articles
1 Rogiers V, Benfenati E, Bernauer U, Bodin L, Carmichael P, Chaudhry Q, Coenraads PJ, Cronin MT, Dent M, Dusinska M, Ellison C, Ezendam J, Gaffet E, Galli CL, Goebel C, Granum B, Hollnagel HM, Kern PS, Kosemund-meynen K, Ouédraogo G, Panteri E, Rousselle C, Stepnik M, Vanhaecke T, von Goetz N, Worth A. The way forward for assessing the human health safety of cosmetics in the EU - Workshop proceedings. Toxicology 2020;436:152421. [DOI: 10.1016/j.tox.2020.152421] [Cited by in Crossref: 18] [Cited by in F6Publishing: 9] [Article Influence: 9.0] [Reference Citation Analysis]
2 Thompson CV, Firman JW, Goldsmith MR, Grulke CM, Tan YM, Paini A, Penson PE, Sayre RR, Webb S, Madden JC. A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage. Altern Lab Anim 2021;49:197-208. [PMID: 34836462 DOI: 10.1177/02611929211060264] [Reference Citation Analysis]
3 Stingone JA, Triantafillou S, Larsen A, Kitt JP, Shaw GM, Marsillach J. Interdisciplinary data science to advance environmental health research and improve birth outcomes. Environ Res 2021;197:111019. [PMID: 33737076 DOI: 10.1016/j.envres.2021.111019] [Reference Citation Analysis]
4 Hernandez-Jerez AF, Adriaanse P, Aldrich A, Berny P, Coja T, Duquesne S, Focks A, Marinovich M, Millet M, Pelkonen O, Pieper S, Tiktak A, Topping CJ, Widenfalk A, Wilks M, Wolterink G, Gundert-Remy U, Louisse J, Rudaz S, Testai E, Lostia A, Dorne JL, Parra Morte JM; EFSA Panel on Plant Protection Products and their Residues (EFSA PPR Panel). Scientific Opinion of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on testing and interpretation of comparative in vitro metabolism studies. EFSA J 2021;19:e06970. [PMID: 34987623 DOI: 10.2903/j.efsa.2021.6970] [Reference Citation Analysis]
5 Yahya FA, Hashim NFM, Israf Ali DA, Chau Ling T, Cheema MS. A brief overview to systems biology in toxicology: The journey from in to vivo, in-vitro and –omics. Journal of King Saud University - Science 2021;33:101254. [DOI: 10.1016/j.jksus.2020.101254] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Alexander-White C, Bury D, Cronin M, Dent M, Hack E, Hewitt NJ, Kenna G, Naciff J, Ouedraogo G, Schepky A, Mahony C, Europe C. A 10-step framework for use of read-across (RAX) in next generation risk assessment (NGRA) for cosmetics safety assessment. Regul Toxicol Pharmacol 2022;:105094. [PMID: 34990780 DOI: 10.1016/j.yrtph.2021.105094] [Reference Citation Analysis]
7 Jenkinson S, Schmidt F, Rosenbrier Ribeiro L, Delaunois A, Valentin JP. A practical guide to secondary pharmacology in drug discovery. J Pharmacol Toxicol Methods 2020;105:106869. [PMID: 32302774 DOI: 10.1016/j.vascn.2020.106869] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
8 Madden JC, Enoch SJ, Paini A, Cronin MTD. A Review of In Silico Tools as Alternatives to Animal Testing: Principles, Resources and Applications. Altern Lab Anim 2020;48:146-72. [PMID: 33119417 DOI: 10.1177/0261192920965977] [Cited by in Crossref: 10] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
9 Hemmerich J, Ecker GF. In silico toxicology: From structure–activity relationships towards deep learning and adverse outcome pathways. WIREs Comput Mol Sci 2020;10. [DOI: 10.1002/wcms.1475] [Cited by in Crossref: 8] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
10 Kostal J, Plugge H, Raderman W. Quantifying Uncertainty in Ecotoxicological Risk Assessment: MUST, a Modular Uncertainty Scoring Tool. Environ Sci Technol 2020;54:12262-70. [DOI: 10.1021/acs.est.0c02224] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
11 Singh N, Chaput L, Villoutreix BO. Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace. Brief Bioinform 2021;22:1790-818. [PMID: 32187356 DOI: 10.1093/bib/bbaa034] [Cited by in Crossref: 18] [Cited by in F6Publishing: 17] [Article Influence: 9.0] [Reference Citation Analysis]
12 Vishnoi S, Matre H, Garg P, Pandey SK. Artificial intelligence and machine learning for protein toxicity prediction using proteomics data. Chem Biol Drug Des 2020;96:902-20. [DOI: 10.1111/cbdd.13701] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
13 Ball N, Madden J, Paini A, Mathea M, Palmer AD, Sperber S, Hartung T, van Ravenzwaay B. Key read across framework components and biology based improvements. Mutation Research/Genetic Toxicology and Environmental Mutagenesis 2020;853:503172. [DOI: 10.1016/j.mrgentox.2020.503172] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
14 Asai T, Takeshita JI, Shimizu Y, Tochikubo Y, Shizu R, Hosaka T, Kanno Y, Yoshinari K. Chemical characterization of anemia-inducing aniline-related substances and their application to the construction of a decision tree-based anemia prediction model. Food Chem Toxicol 2021;157:112548. [PMID: 34509582 DOI: 10.1016/j.fct.2021.112548] [Reference Citation Analysis]
15 Pestana CB, Firman JW, Cronin MT. Incorporating lines of evidence from New Approach Methodologies (NAMs) to reduce uncertainties in a category based read-across: A case study for repeated dose toxicity. Regulatory Toxicology and Pharmacology 2021;120:104855. [DOI: 10.1016/j.yrtph.2020.104855] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
16 Imami AS, McCullumsmith RE, O'Donovan SM. Strategies to identify candidate repurposable drugs: COVID-19 treatment as a case example. Transl Psychiatry 2021;11:591. [PMID: 34785660 DOI: 10.1038/s41398-021-01724-w] [Reference Citation Analysis]
17 Xu T, Wu L, Xia M, Simeonov A, Huang R. Systematic Identification of Molecular Targets and Pathways Related to Human Organ Level Toxicity. Chem Res Toxicol 2021;34:412-21. [PMID: 33251791 DOI: 10.1021/acs.chemrestox.0c00305] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
18 Chang X, Tan Y, Allen DG, Bell S, Brown PC, Browning L, Ceger P, Gearhart J, Hakkinen PJ, Kabadi SV, Kleinstreuer NC, Lumen A, Matheson J, Paini A, Pangburn HA, Petersen EJ, Reinke EN, Ribeiro AJS, Sipes N, Sweeney LM, Wambaugh JF, Wange R, Wetmore BA, Mumtaz M. IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making. Toxics 2022;10:232. [DOI: 10.3390/toxics10050232] [Reference Citation Analysis]
19 Paini A, Tan YM, Sachana M, Worth A. Gaining acceptance in next generation PBK modelling approaches for regulatory assessments - An OECD international effort. Comput Toxicol 2021;18:100163. [PMID: 34027244 DOI: 10.1016/j.comtox.2021.100163] [Reference Citation Analysis]
20 Green AJ, Mohlenkamp MJ, Das J, Chaudhari M, Truong L, Tanguay RL, Reif DM. Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology. PLoS Comput Biol 2021;17:e1009135. [PMID: 34214078 DOI: 10.1371/journal.pcbi.1009135] [Reference Citation Analysis]
21 Vichare AS, Kamath SU, Leist M, Hayes AW, Mahadevan B. Application of the 3Rs principles in the development of pharmaceutical generics. Regul Toxicol Pharmacol 2021;125:105016. [PMID: 34302895 DOI: 10.1016/j.yrtph.2021.105016] [Reference Citation Analysis]