1. Ciallella H, Russo D, Aleksunes L M, Grimm F, Zhu H* Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach. Environ. Sci. Technol., 2021, In press

 

  1. Mansouri K. and other 102 co-authors including Zhu H CATMoS: Collaborative Acute Toxicity Modeling Suite. Environ. Health Perspect. 2021, (129) 47013

 

  1. Jia X; Ciallella H; Russo D; Zhao L; James M; Zhu H* Construction of a Virtual Opioid Bioprofile: a Data-driven QSAR Modeling Study to Identify New Analgesic Opioids. ACS Sustainable Chem. Eng. 2021, (9) 3909-3919

 

  1. Ciallella H, Russo D, Aleksunes L M, Grimm F, Zhu H* Predictive Modeling of Estrogen Receptor Agonism, Antagonism, and Binding Activities Using Machine and Deep Learning Approaches. Lab Invest., 2021, (101) 490–502

 

  1. Yan X, Zhang J, Russo D, Zhu H*, Yan B Prediction of Nano–Bio Interactions through Convolutional Neural Network Analysis of Nanostructure Images. ACS Sustainable Chem. Eng. 2020, (8) 19096–19104

 

  1. Russo D, Yan X, Shende S, Huang H, Yan B, Zhu H* Virtual molecular projections and convolutional neural networks for end-to-end modeling of nanoparticle activities and properties. Anal. Chem., 2020; (92) 13971-13979.

 

  1. Wang Y, Russo D, Liu C, Zhou Q, Zhu H*, Zhang Y Predictive modeling of angiotensin I-converting enzyme (ACE) inhibitory peptides using various machine learning approaches. J. Agric. Food Chem., 2020; (68):12132-12140.

 

  1. Zhao L, Ciallella H, Aleksunes L M, Zhu H* Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling. Drug Discov Today, 2020 (25) 1624-1638. PMCID: PMC7572559 (Editor Invited Keynote Review)

 

  1. Gao R, Guan N, Huang M, Foreman J, Kung M, Rong Z, Su Y, Sweet L, Zhu B, Zhu H, Zou H, Li B, Wang Y, Yin H, Yin Z, Zhang X Read-across: Principle, case study and its potential regulatory application in China. Regul. Toxicol. Pharmacol., 2020; (116) 104728.

 

  1. Yan X, Sedykh A, Wang W, Yan B, Zhu H* Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations. Nat. Commun, 2020; (11) 2519. (NIEHS Extramural Paper of the Month)

 

  1. Zhou C, Shi W, Zhu H, Yu H, Liu J, Song M, Xia P, Chen Q, Wei S, Zhang X, Wang X Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials. Sci. Total Environ., 2020, (728) 138854.

 

  1. Qi X, Li X, Yao H, Huang Y, Cai X, Chen J, Zhu H Predicting plant cuticle-water partition coefficients for organic pollutants using pp-LFER model. Sci. Total Environ., 2020, (725) 138455.

 

  1. Liu G, Yan X, Sedykh A, Pan X, Zhao X, Yan B, Zhu H* Analysis of model PM2.5-induced inflammation and cytotoxicity by the combination of a virtual carbon nanoparticle library and computational modeling. Ecotoxicol. Environ. Saf., 2020; (191) 110216. PMCID: PMC7018436.

 

  1. Liu Y, Wei Y, Zhang S, Yan X, Zhu H, Xu L, Zhao B, Xie H, Yan B Regulation of aryl hydrocarbon receptor signaling pathway and dioxin toxicity by novel agonists and antagonists. Chem. Res. Toxicol., 2020; (33) 614-624.

 

  1. Bai X, Wang S, Yan X, Zhou H, Zhan J, Liu S, Sharma V, Jiang G, Zhu H, Yan B Regulation of Cell Uptake and Cytotoxicity by Nanoparticle Core under the Controlled Shape, Size, and Surface Chemistries. ACS Nano, 2020; (14):289-302.

 

  1. Zhao L, Russo D P, Wang W, Aleksunes L M, Zhu H* Mechanism-driven Read-Across of Chemical Hepatotoxicants Based on Chemical Structures and Biological Data. Toxicol. Sci., 2020; (174) 178-188. PMCID: PMC7098374. (Featured by Society of Toxicology as monthly highlighted paper)

 

  1. Zhu H* Big Data and Artificial Intelligence Modeling for Drug Discovery. Annual Rev. Pharm. Tox., 2020; (20) 573-589. PMCID: PMC7010403. (Editor Invited Review)

 

  1. Wang Y, Li B, Xu X, Ren H, Yin J, Zhu H, Zhang Y FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners. Food Chem., 2020; (303) 125404.

 

  1. Guo Y, Zhao L, Zhang X, Zhu H* Using a Hybrid Read-Across Method to Evaluate Chemical Toxicity Based on Chemical Structure and Biological Data. Ecotox. Environ. Saf., 2019; (178) 178-187. PMCID: PMC6508079.

 

  1. Yan X, Sedykh A, Wang W, Zhao X, Yan B, Zhu H* In silico profiling nanoparticles: predictive nanomodeling using universal nanodescriptors and various machine learning approaches. Nanoscale, 2019; (11) 8352–8362.

 

  1. Russo D P, Strickland, J, Karmaus A L, Wang W, Shende S, Hartung T, Aleksunes L M, Zhu H* Non-animal models for acute toxicity evaluations: applying data-driven profiling and read-across. Environ. Health Perspect., 2019; (127) 47001. PMCID: PMC6785238. (NIEHS Extramural Paper of the Month. Featured by over 10 public medias. See details in “Media Reports”)

 

  1. Ciallella, H, Zhu H* Advancing Computational Toxicology in the Big Data Era by Artificial Intelligence: Data-Driven and Mechanism-Driven Modeling for Chemical Toxicity. Chem. Res. Tox., 2019; (32) 536−547. PMCID: PMC6688471. (Editor invited perspective and featured as Chemical Research in Toxicology cover paper)

 

  1. Wang W, Yan X, Zhao L, Russo D P, Wang S, Liu Y, Sedykh A, Zhao X, Yan B, Zhu H* Universal nanohydrophobicity predictions using virtual nanoparticle library. J. Cheminform., 2019, (11) 6. PMCID: PMC6689884

 

  1. Russo D P, Zorn K M, Clark A M, Zhu H, Ekins S Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction. Mol. Pharm., 2018; (15) 4361-4370. PMCID: PMC6181119

 

  1. Wang W, Sedykh A, Sun H, Zhao L, Russo D P, Zhou H, Yan B, Zhu H* Predicting Nano-bio Interactions by Integrating Nanoparticle Libraries and Quantitative Nanostructure Activity Relationship Modeling. ACS Nano, 2017; (11) 12641-12649. PMCID: PMC5772766

 

  1. Zhang L, Tan J, Han D, Zhu H* From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug Discov. Today, 2017; (22) 1680-1685. (Featured as Drug Discovery Today top citation paper of the year)

 

  1. Liu Y, Su G, Wang F, Jia J, Li S, Zhao L, Shi Y, Cai Y, Zhu H, Zhao B, Jiang G, Zhou H, Yan B Elucidation of the Molecular Determinants for Optimal Perfluorooctanesulfonate Adsorption Using a Combinatorial Nanoparticle Library Approach. Environ. Sci. Technol., 2017; (51) 7120-7127. PMCID: PMC5784263

 

  1. Zhao L, Wang W, Sedykh A, Zhu H* Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do. ACS Omega, 2017; (2) 2805-2812. PMCID: PMC5494643

 

  1. Bai X, Liu F, Liu Y, Li C, Wang S, Zhou H, Wang W, Zhu H, Winkler D, Yan B Toward A Systematic Exploration of Nano-Bio Interactions. Toxicol. Appl. Pharmacol. 2017; (323) 66-73. PMCID: PMC5581002

 

  1. Hamm J, Sullivan K, Clippinger A J, Strickland J, Bell S, Bhhatarai B, Blaauboer B, Casey W, Dorman D, Forsby A, Garcia-Reyero N, Gehen S, Graepel R, Hotchkiss J, Lowit A, Matheson J, Reaves E, Scarano L, Sprankle C, Tunkel J, Wilson D, Xia M, Zhu H, Allen D Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing. Toxicol. In Vitro, 2017; (41) 245-259. PMCID: PMC5479748

 

  1. Russo D P, Kim M, Wang W, Pinolini D, Shende S, Strickland J, Hartung T, Zhu H* CIIPro: A new read-across portal to fill data gaps using public large scale chemical and biological data. Bioinformatics, 2017; (33) 464-466. PMCID: PMC6075082

 

  1. Xiang J, Zhang Z, Mu Y, Xu X, Guo S, Liu Y, Russo D, Zhu H, Yan B, Bai X Discovery of Novel Tricyclic Thiazepine Derivatives as Anti-Drug-Resistant Cancer Agents by Combining Diversity-Oriented Synthesis and Converging Screening Approach. ACS Comb. Sci. 2016; (18) 230–235.

 

  1. Ribay K, Kim M, Wang W, Pinolini D, Zhu H* Hybrid Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data. Front. Environ. Sci. 2016; (4) 12. PMCID: PMC5023020

 

  1. Kim M, Huang R, Sedykh A, Zhang J, Xia M, Zhu H* Mechanism profiling liver toxicants by using antioxidant response element assay data model and public big data. Environ. Health Perspect. 2016; (124) 634-641. PMCID: PMC4858396

 

  1. Mu Y, Liu Y, Xiang J, Zhang Q, Zhai S, Russo D P, Zhu H, Bai X, Yan B From fighting depression to conquering tumors: a novel tricyclic thiazepine compound as a tubulin polymerization inhibitor Cell Death and Disease 2016; (7) e2143.

 

  1. Zhu H, Bouhifd M, Kleinstreuer N, Kroese ED, Liu Z, Luechtefeld T, Pamies D, Shen J, Strauss V, Wu S, Hartung T Supporting read-across using biological data. ALTEX., 2016; (33) 167-182. PMCID: PMC4834201 (ALTEX cover paper. Featured together with following 5 ALTEX papers by Science Feb 12, 2016 “A crystal ball for chemical safety” and Nature Feb 11, 2016 “Legal tussle delays launch of huge toxicity database”)

 

  1. Ball N, Cronin M T, Shen J, Adenuga M D, Blackburn K, Booth E D, Bouhifd M, Donley E, Egnash L, Freeman J J, Hastings C, Juberg D R, Kleensang A, Kleinstreuer N, Kroese E D, Luechtefeld T, Maertens A, Marty S, Naciff J M, Palmer J, Pamies D, Penman M, Richarz A N, Russo D P, Stuard S B, Patlewicz G, van Ravenzwaay B, Wu S, Zhu H, Hartung T Toward Good Read-Across Practice (GRAP) guidance. ALTEX., 2016; (33) 149-166. PMCID: PMC5581000

 

  1. Luechtefeld T, Maertens A, Russo D P, Rovida C, Zhu H, Hartung T Analysis of publically available skin sensitization data from REACH registrations 2008-2014. ALTEX., 2016; (33) 135-148.

 

  1. Luechtefeld T, Maertens A, Russo D P, Rovida C, Zhu H, Hartung T Analysis of Draize eye irritation testing and its prediction by mining publicly available 2008-2014 REACH data. ALTEX., 2016; (33) 123-134.

 

  1. Luechtefeld T, Maertens A, Russo D P, Rovida C, Zhu H, Hartung T Analysis of public oral toxicity data from REACH registrations 2008-2014. ALTEX. 2016; (33) 111-122.

 

  1. Luechtefeld T, Maertens A, Russo D P, Rovida C, Zhu H, Hartung T Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008-2014. ALTEX., 2016; (33) 95-109.

 

  1. Zhang Y, Wang Y, Liu A, Xu S L, Zhao B, Zhang Y, Zou H, Wang W, Zhu H, Yan B Modulation of Carbon Nanotube’s Perturbation to the Metabolic Activity of CYP3A4 in the Liver. Adv. Funct. Mater., 2016; (26) 841-850. (Advanced Functional Materials cover paper)

 

  1. Wang W, Kim M, Sedykh A, Zhu H* Developing enhanced blood-brain barrier permeability models: Integrating external bio-assay data in QSAR modeling. Pharm. Res. 2015; (32) 3055-3065. PMCID: PMC4529363

 

  1. Liu Y, Li F, Wu L, Wang W, Zhu H, Zhang Q, Zhou H, Yan B Improving both aqueous solubility and anti-cancer activity by assessing progressive lead optimization libraries. Bioorg. Med. Chem. Lett. 2015; (25) 1971-1975.

 

  1. Li S, Zhai S, Liu Y, Zhou H, Wu J, Jiao Q, Zhang B, Zhu H*, Yan B Experimental modulation and computational model of nano-hydrophobicity. Biomaterials, 2015; (52) 312-317. PMCID: PMC5586105

 

  1. Zhu H*, Zhang J, Kim M, Boison A, Sedykh A, Moran K Big data in chemical toxicity research: The use of high-throughput screening assays to identify potential toxicants. Chem. Res. Tox. 2014; (27) 1643-1651. PMCID: PMC4203392 (Featured together with the following PLoS One paper by Chemical Watch Sept 18, 2014 “Trial data mining project flags up Qsar issues”)

 

  1. Zhang J, Hsieh J-H, Zhu H* Profiling animal toxicants by automatically mining public bioassay data: A big data approach for computational toxicology. PLoS One, 2014; (9) e99863. PMCID: PMC4064997

 

  1. Sprague B, Shi Q, Kim M, Zhang L, Sedykh A, Ichiishi E, Tokuda H, Lee K H, Zhu H* Design, synthesis and experimental validation of novel potential chemopreventive agents using random forest and support vector machine binary classifiers. J. Comput. Aided Mol. Des. 2014; (28) 631-646.

 

  1. Wu L, Zhang Y, Zhang C, Cui X, Zhai S, Liu Y, Li C, Zhu H, Qu G, Jiang G, Yan B Tuning cell autophagy by diversifying carbon nanotube surface chemistry. ACS Nano, 2014, (8), 2087–2099. PMCID: PMC5586106

 

  1. Kim M, Sedykh A, Chakravarti S K, Saiakhov R D, Zhu H* Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches. Pharm. Res., 2014; (31) 1002-1014. PMCID: PMC3955412

 

  1. Zhang L, Sedykh A, Tripathi A, Zhu H, Afantitis A, Mouchlis VD, Melagraki G, Rusyn I, Tropsha A Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches. Toxicol. Appl. Pharmacol. 2013; (272) 67-76.

 

  1. Zhu XW, Sedykh A, Zhu H, Liu SS, Tropsha A The use of pseudo-equilibrium constant affords improved QSAR models of human plasma protein binding. Pharm. Res. 2013; (30) 1790-1798.

 

  1. Sedykh A, Fourches D, Duan J, Hucke O, Garneau M, Zhu H, Bonneau P, Tropsha A Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions. Pharm. Res. 2013; (30) 996-1007.

 

  1. Zhang L, Fourches D, Sedykh A, Zhu H, Golbraikh A, Ekins S, Clark J, Connelly M C, Sigal M, Hodges D, Guiguemde W A, Guy R K, Tropsha A The discovery of novel antimalarial compounds enabled by QSAR-based virtual screening. J. Chem. Inf. Model. 2013; (53) 475-492.

 

  1. Solimeo R, Zhang J, Kim M, Sedykh A, Zhu H* Predicting chemical ocular toxicity using a combinatorial QSAR approach. Chem. Res. Tox. 2012; (25) 2763−2769.

 

  1. Martin T M, Harten P, Young D M, Muratov E N, Golbraikh A, Zhu H, Tropsha A Does rational selection of training and test sets improve the outcome of QSAR modeling? J. Chem. Inf. Model. 2012; (52):2570-2578.

 

  1. Kang C, Zhu H, Wright F A, Zou F, Kosorok M R The interactive decision committee for chemical toxicity analysis. J. Stat Res. 2012; (46) 157-186.

 

  1. Ye D, Shi Q, Leung C H, Kim S W, Park S Y, Gullen E A, Jiang ZL, Zhu H, Morris-Natschke S L, Cheng Y C, Lee K H Antitumor agents 294. Novel E-ring-modified camptothecin-4β-anilino-4′-O-demethyl-epipodophyllotoxin conjugates as DNA topoisomerase I inhibitors and cytotoxic agents. Bioorg. Med. Chem. 2012; (20): 4489-4494.

* indicates that I served as the corresponding author