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Publications

28 peer-reviewed publications (11 first author). * co-first author.

Peer-reviewed articles

  1. L. Dreano, A. Legehar, M. Briand, K. Variskallio, A. Borrel, H. Xhaard. Assessing Molecular Contacts Using Atom Environments Described by Ranked Lists. J. Chem. Inf. Model., 2026. https://doi.org/10.1021/acs.jcim.6c00694

  2. S. L. Smith-Roe, M. J. DeVito, C. Co, S. C. Ramaiahgari, M. Easterling, J. R. Rice, P. E. Dunlap, D. M. Crizer, Z. Zhou, B. A. Merrick, G. Xie, S. F. Harris, K. R. Shockley, A. Tandon, A. Oktay, D. Mav, R. Shah, A. Borrel, V. Gombar, S. A. Masten, R. S. Paules, S. S. Ferguson. Comparative investigation of the potential of glyphosate and glyphosate-based formulations to cause oxidative stress and DNA damage in human skin and liver cell systems. Toxicol. Sci., 2026. https://doi.org/10.1093/toxsci/kfag029

  3. A. Ross, V. Gombar, A. Sedykh, A. J. Green, A. Borrel, B. Kidd, J. Phillips, M. Shah, D. Phadke, D. Mav, M. Balik-Meisner, B. Howard, R. Shah, N. C. Kleinstreuer, W. M. Casey. OrbiTox: a visualization platform for NAMs and read-across exploration of multi-domain data. Front. Pharmacol., 2025. https://doi.org/10.3389/fphar.2025.1710864

  4. Y. Gao, Z. Mughal, J. A. Jaramillo-Villegas, M. Corradi, A. Borrel, B. Lieberman, S. Sharif, J. Shaffer, K. Fecho, A. Chatrath, A. Maertens, M. A. T. Teunis, N. Kleinstreuer, T. Hartung, T. Luechtefeld. BioBricks.ai: a versioned data registry for life sciences data assets. Front. Artif. Intell., 2025. https://doi.org/10.3389/frai.2025.1599412

  5. M. Behl, A. Karmaus, M. Rao, T. Lane, J. Harris, C. Sachs, A. Borrel, O. Oyetade, A. Unnikrishnan, J. Hamm, H. T. Hogberg. De-risking seizure liability: integrating adverse outcome pathways (AOPs), new approach methodologies (NAMs), and in silico approaches while highlighting knowledge gaps. Toxicol. Sci., 2025. https://doi.org/10.1093/toxsci/kfaf109

  6. K. To, J. Strickland, E. Reinke, A. Borrel, J. Truax, H. Maldonado, D. Allen, N. Kleinstreuer. Computational application of internationally harmonized defined approaches to skin sensitization: DASS App. BMC Bioinformatics, 2024. https://doi.org/10.1186/s12859-023-05617-1

  7. T. M. Whitehead, J. Strickland, G. J. Conduit, A. Borrel, D. Mucs, I. Baskerville-Abraham. Quantifying the Benefits of Imputation over QSAR Methods in Toxicology Data Modelling. J. Chem. Inf. Model., 2023. https://doi.org/10.1021/acs.jcim.3c01695

  8. A. Borrel, M. Conway, S. Z. Nolte, A. Unnikrishnan, C. P. Schmitt, N. C. Kleinstreuer. ChemMaps.com v2.0: exploring the environmental chemical universe. Nucleic Acids Res., 2023, 51(W1), W78–W82. https://doi.org/10.1093/nar/gkad380

  9. A. Borrel, R. A. Rudel. Cheminformatics analysis of chemicals that increase estrogen and progesterone synthesis for a breast cancer hazard assessment. Scientific Reports, 2022, 12(1). https://doi.org/10.1038/s41598-022-24889-w

  10. R. A. Rudel, B. Cardona, A. Borrel, J. E. Kay. Response to “Comment on ‘Application of an in Vitro Assay to Identify Chemicals That Increase Estradiol and Progesterone Synthesis and Are Potential Breast Cancer Risk Factors.’” Environmental Health Perspectives, 2022, 130(5). https://doi.org/10.1289/EHP11400

  11. S. Krishna*, A. Borrel*, R. Huang, J. Zhao, M. Xia, N. Kleinstreuer. High-Throughput Chemical Screening and Structure-Based Models to Predict hERG Inhibition. Biology, 2022, 11(2), 209. https://doi.org/10.3390/biology11020209

  12. A. L. Hagstrom, P. Anastas, A. Boissevain, et al. Yale School of Public Health Symposium: An overview of the challenges and opportunities associated with per- and polyfluoroalkyl substances (PFAS). Sci. Total Environ., 2021, 778, 146192. https://doi.org/10.1016/j.scitotenv.2021.146192

  13. A. Borrel, C. Melander, D. Fourches. Cheminformatics Analysis of Fluoroquinolones and their Inhibition Potency Against Four Pathogens. Mol. Inform., 2021, 40(5), 2000215. https://doi.org/10.1002/minf.202000215

  14. P. P. Kyaw Zin, A. Borrel, D. Fourches. Benchmarking 2D/3D/MD-QSAR Models for Imatinib Derivatives: How Far Can We Predict? J. Chem. Inf. Model., 2020, 60(7), 3342–3360. https://doi.org/10.1021/acs.jcim.0c00200

  15. A. Borrel, K. Mansouri, S. Nolte, et al. InterPred: a webtool to predict chemical autofluorescence and luminescence interference. Nucleic Acids Res., 2020, 48(W1), W586–W590. https://doi.org/10.1093/nar/gkaa378

  16. A. Borrel, S. S. Auerbach, K. A. Houck, N. C. Kleinstreuer. Tox21BodyMap: a webtool to map chemical effects on the human body. Nucleic Acids Res., 2020, 50, 1–5. https://doi.org/10.1093/nar/gkaa433 — NIEHS article of the year 2020

  17. M. T. Smith, K. Z. Guyton, N. Kleinstreuer, et al. The Key Characteristics of Carcinogens: Relationship to the Hallmarks of Cancer, Relevant Biomarkers, and Assays to Measure Them. Cancer Epidemiol. Biomarkers Prev., 2020, 29(10), 1887–1903. https://doi.org/10.1158/1055-9965.EPI-19-1346

  18. A. Borrel, R. Huang, S. Sakamuru, et al. High-Throughput Screening to Predict Chemical-Assay Interference. Sci. Rep., 2020, 10(1), 3986. https://doi.org/10.1038/s41598-020-60747-3 — Top 100 chemistry 2020

  19. A. Borrel, N. C. Kleinstreuer, D. Fourches. Exploring drug space with ChemMaps.com. Bioinformatics, 2018, 34(21), 3773–3775. https://doi.org/10.1093/bioinformatics/bty412

  20. A. Borrel, A.-C. Camproux, H. Xhaard. Characterization of Ionizable Groups’ Environments in Proteins and Protein–Ligand Complexes through a Statistical Analysis of the Protein Data Bank. ACS Omega, 2017, 2(10), 7359–7374. https://doi.org/10.1021/acsomega.7b00739

  21. A. Borrel, D. Fourches. RealityConvert: a tool for preparing 3D models of biochemical structures for augmented and virtual reality. Bioinformatics, 2017, 33(23), 3816–3818. https://doi.org/10.1093/bioinformatics/btx485

  22. G. Caumes, A. Borrel, H. Abi Hussein, A.-C. Camproux, L. Regad. Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification. Mol. Inform., 2017, 36(9), 1700025. https://doi.org/10.1002/minf.201700025

  23. Y. Zhang*, A. Borrel*, L. Ghemtio, et al. Structural Isosteres of Phosphate Groups in the Protein Data Bank. J. Chem. Inf. Model., 2017, 57(3), 499–516. https://doi.org/10.1021/acs.jcim.6b00519

  24. H. Abi Hussein, C. Geneix, M. Petitjean, A. Borrel, D. Flatters, A. Camproux. Global vision of druggability issues: applications and perspectives. Drug Discov. Today, 2017, 22(2), 404–415. https://doi.org/10.1016/j.drudis.2016.11.021

  25. A. Turku, A. Borrel, T. O. Leino, L. Karhu, J. P. Kukkonen, H. Xhaard. Pharmacophore Model To Discover OX1 and OX2 Orexin Receptor Ligands. J. Med. Chem., 2016, 59(18), 8263–8275. https://doi.org/10.1021/acs.jmedchem.6b00333

  26. H. A. Hussein, A. Borrel, C. Geneix, M. Petitjean, L. Regad, A.-C. Camproux. PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins. Nucleic Acids Res., 2015, 1–7. https://doi.org/10.1093/nar/gkv462

  27. A. Borrel, L. Regad, H. Xhaard, M. Petitjean, A.-C. Camproux. PockDrug: A Model for Predicting Pocket Druggability That Overcomes Pocket Estimation Uncertainties. J. Chem. Inf. Model., 2015, 55(4), 882–895. https://doi.org/10.1021/ci5006004

  28. M. Francescatto, S. M. Hermans, S. Babaei, E. Vicedo, A. Borrel, P. Meysman. Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014. BMC Bioinformatics, 2014, 16(Suppl 3), A3. https://doi.org/10.1186/1471-2105-16-S3-A

  29. S. Ménigaud, L. Mallet, G. Picord, C. Churlaud, A. Borrel, P. Deschavanne. GOHTAM: a website for “Genomic Origin of Horizontal Transfers, Alignment and Metagenomics”. Bioinformatics, 2012, 28(9), 1270–1271. https://doi.org/10.1093/bioinformatics/bts118

Book chapters and thesis

  1. A. Borrel. Chapter 2 — Modern modeling approaches for data gap filling. In Cheminformatic Modeling and Data Gap Filling for a Green and Sustainable Environment, Elsevier, 2026. https://doi.org/10.1016/B978-0-443-36474-7.00004-1

  2. A. Green, A. Tandon, A. Oktay, A. Borrel, B. Howard. Chapter 3 — Aquatic toxicology: Computational approaches and innovations. In Cheminformatic Modeling and Data Gap Filling for a Green and Sustainable Environment, Elsevier, 2026. https://doi.org/10.1016/B978-0-443-36474-7.00002-8

  3. V. Gombar, A. Sedykh, A. Borrel. Chapter 20 — Emerging advances in modeling chemical mutagenicity and carcinogenicity. In Cheminformatic Modeling and Data Gap Filling for a Green and Sustainable Environment, Elsevier, 2026. https://doi.org/10.1016/B978-0-443-36474-7.00030-2

  4. H. A. Hussein, A. Borrel, L. Regad, et al. Systems Biology. In The Practice of Medicinal Chemistry, Elsevier, 2015, 409–425. https://doi.org/10.1016/B978-0-12-417205-0.00017-1

  5. A. Borrel. Development of Computational Methods to Predict Protein Pocket Druggability and Profile Ligands using Structural Data. Ph.D. thesis, 2016. http://hdl.handle.net/10138/162202