Yuji Zhang, PhD

1. Zhang Y, Zhu J, Sun X, Lu Z. A method of oligonucleotide synthesis optimization. 2002;12(4):26-28.
2. Ressom HW, Zhang Y*, Xuan J, Wang Y, Clarke R. Inferring network interactions using recurrent neural networks and swarm intelligence. Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2006 Aug 30;4241-4244. (primary author to design the experiment, perform the analysis, and write the manuscript)
3. Ressom HW, Zhang Y*, Xuan J, Wang Y, Clarke R. Inference of gene regulatory networks from time course gene expression data using neural networks and swarm intelligence. Proceedings of 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology. 2006 Sep 28;435-442. (primary author to design the experiment, perform the analysis, and write the manuscript)
4. Ressom HW, Zhang Y*, Xuan J, Wang Y, Clarke R. Integrating multi-source biological data for transcriptional regulatory module discovery. Proceedings of IEEE/NIH Life Science Systems and Applications Workshop 2007. 2007 Nov 8;184-187. (primary author to design the experiment, perform the analysis, and write the manuscript)
5. Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW. Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data. BMC Bioinformatics. 2008;9(1):203.
6. Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW. Reverse engineering module networks by PSO-RNN hybrid modeling. Proceedings of the 2008 International Conference on Bioinformatics and Computational Biology. 2008; 401–407.
7. Zhang Y, Xuan J, de Los Reyes BG, Clarke R, Ressom HW. Network motif-based identification of breast cancer susceptibility genes. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2008 Aug 20;5696-5699.
8. Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW. Reverse engineering module networks by PSO-RNN hybrid modeling. BMC Genomics. 2009 Jul 7;10(1):S15.
9. Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW. Reconstruction of gene regulatory modules in cancer cell cycle by multi-source data integration. PLOS ONE. 2010;5(4):e10268.
10. Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW. Module-based biomarker discovery for breast cancer. Proceedings of 2010 IEEE International Conference on Bioinformatics & Biomedicine. 2010;352-356.
11. Sun Z, Baheti S, Middha S, Kanwar R, Zhang Y, Li X, Beutler AS, Klee E, Asmann YW, Thompson EA, Kocher JP. SAAP-RRBS: streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing. Bioinformatics. 2012; 28(16): 2180-2181. (participated in determining analytic method, running analyses, and providing statistical interpretation)
12. Asmann YW, Middha S, Hossain A, Baheti S, Li Y, Chai HS, Sun Z, Duffy PH, Hadad AA, Nair A, Liu X, Zhang Y, Klee EW, Kalari KR, Kocher JP. TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data. Bioinformatics. 2012; 28(2):277-278. (determined analytic method, ran analyses, provided statistical interpretation)
13. Wang J, Zhang Y*, Marian C, Ressom HW. Identification of aberrant pathways and network activities from high-throughput data. Briefings in Bioinformatics. 2012;13(4):406-419. (primary author to design the experiment, perform the analysis, and write the manuscript)
14. Craig TA, Zhang Y*, McNulty MS, Middha S, Ketha H, Singh RJ, Magis AT, Funk C, Price ND. Ekker SC, Kumar R. Research resource: whole transcriptome RNA sequencing detects multiple 1alpha, 25-dihydroxyvitamin D(3)-sensitive metabolic pathways in developing zebrafish. Molecular Endocrinology. 2012;26(9):1630-1642. (primary author to design the experiment, perform the analysis, and write the manuscript)
15. Tao C, Zhang Y*, Jiang G, Bouamrane MM, Chute CG. Optimizing semantic MEDLINE for translational science studies using semantic web technologies. Proceedings of the 2nd international workshop on Managing interoperability and compleXity in health systems. 2012 Oct 29;53-58. (primary author to design the experiment, perform the analysis, and write the manuscript)
16. Zhang Y, Li D, Tao C, Shen F, Liu H. An integrative computational approach to identify disease-specific networks from PubMed literature information. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine 2013. 2013 Dec 18;72-75.
17. Leonard B, Hart SN, Burns MB, Carpenter MA, Temiz NA, Rathore A, Isaksson Vogel R, Nikas JB, Law EK, Brown WL, Li Y, Zhang Y, Maurer MJ, Oberg AL, Cunningham JM, Shridhar V, Bell DA, April C, Bently D, Bibikova M, Cheetham RK, Fan JB, Grocock R, Humphray S, Kingsbury Z, Peden J, Chien J, Swisher EM, Hartmann LC, Kalli KR, Goode EL, Sicotte H, Kaufmann SH, Harris RS. APOBEC3B upregulation and genomic mutation patterns in serous ovarian carcinoma. Cancer Research. 2013;73(24):7222-7231. (determined analytic method, ran analyses, provided statistical interpretation)
18. Hart SN, Therneau TM, Zhang Y, Poland GA, Kocher JP. Calculating sample size estimates for RNA sequencing data. Journal of Computational Biology. 2013;20(12):970-978. (determined analytic method, ran analyses, provided statistical interpretation)
19. Zhang Y, Tao C, He Y, Kanjamala P, Liu H. Network-based analysis of vaccine-related associations reveals consistent knowledge with the vaccine ontology. Journal of Biomedical Semantics. 2013;4(1):33.
20. Sun Z, Asmann YW, Nair A, Zhang Y, Wang L, Kalari KR, Bhagwate AV, Baker TR, Carr, JM, Kocher JP, Perez EA, Thompson EA. Impact of library preparation on downstream analysis and interpretation of RNA-Seq data: comparison between Illumina PolyA and NuGEN Ovation protocol. PLOS ONE. 2013;8(8):e71745. (determined analytic method, ran analyses, provided statistical interpretation)
21. Pugazhenthi S, Zhang Y*, Bouchard R, & Mahaffey G. Induction of an inflammatory loop by interleukin-1 beta and tumor necrosis factor-alpha involves NF- kappa B and STAT-1 in differentiated human neuroprogenitor cells. PLOS ONE. 2013;8(7): e69585. (primary author to design the experiment, perform the analysis, and write the manuscript)
22. Zhang Y, Tao C, He Y, Kanjamala P, Liu H. Analysis of vaccine-related networks using Semantic MEDLINE and the vaccine ontology. CEUR Workshop Proceedings, 2013; 1061:1-6.
23. Zhang Y, Xuan J, Clarke R, Ressom HW. Module-based breast cancer classification. International Journal of Data Mining and Bioinformatics. 2013;7(3):284-302.
24. Zhang Y, Tao C. Network analysis of cancer-focused association network reveals distinct network association patterns. Cancer Informatics. 2014;13(S3):45.
25. Tao C, Wu P, Zhang Y. Linked vaccine adverse event data representation from VAERS for biomedical informatics research. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014 May 13;652-661.
26. Craig, TA, Zhang Y^¥, Magisc AT, Funk CC, Price ND, Ekker, SC, Kumar R. Detection of 1,25-Dihydroxyvitamin D-regulated miRNAs in zebrafish by whole transcriptome sequencing. Zebrafish. 2014;11(3):207-218. (^¥co-first authorship)
27. Zhang Y, Tao C. Correction to “Network analysis of cancer-focused association network reveals distinct network association patterns”. Cancer Inform. 2014;13(Suppl 3):89.
28. Zhang Y, Tao C, Jiang G, Nair A, Su J, Chute CG, Liu H. Network-based analysis reveals distinct association patterns in a Semantic MEDLINE-based Drug-Disease-Gene network. Journal of Biomedical Semantics. 2014;5(1):33.
29. Zhang Y. Network-based analysis of time series RNA-seq gene expression data by integrating the interactome and gene ontology information. Proceedings of 2014 8th International Conference on Systems Biology (ISB). 2014 Oct 24;201-209.
30. Zhu Q, Liu H, Zhang Y, Wang J. Evidence based computational drug repositioning candidate screening pipeline design: case study. Proceedings of 2014 8th International Conference on Systems Biology (ISB). 2014 Oct 24;210-218. (determined analytic method, ran analyses, provided statistical interpretation)
31. Wang L, Chen J, Wang C, Uusküla-Reimand L, Chen K, Medina-Rivera A, Young E, Zimmermann M, Yan H, Sun Z, Zhang Y, Wu S, Huang H, Wilson MD, Kocher JP, Li W. MACE: model based analysis of ChIP-exo. Nucleic Acids Research. 2014;42(20):e156-e156. (determined analytic method, ran analyses, provided statistical interpretation)
32. Tao C, Yu P, Luo Y, Zhang Y. Linked vaccine adverse event data from VAERS for biomedical data analysis and longitudinal studies. BioData Mining. 2014;7(1):36.
33. Shih Y, Zhang Y*, Ding Y, Ross CA, Li H, Olson TM, Xu X. The Cardiac transcriptome and dilated cardiomyopathy genes in zebrafish. Circulation: Cardiovascular Genetics. 2015;8(2):261-269. (primary author to determine analytic method, run analyses, and provide statistical interpretation)
34. Felts SJ, Van Keulen VP, Scheid AD, Allen KS, Bradshaw RK, Jen J, Peikert T, Middha S, Zhang Y, Block MS, Markovic SN, Pease LR. Gene expression patterns in CD4+ peripheral blood cells in healthy subjects and stage IV melanoma patients. Cancer Immunology & Immunotherapy. 2015;64(11):1437-1447. (determined analytic method, ran analyses, provided statistical interpretation)
35. Zhang Y. Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge. BioData Mining. 2015;8(1):26.
36. Zhang Y, Yu P, & Tao C. Identification of sex-associated network patterns in vaccine-adverse event association network in VAERS. Journal of Biomedical Semantics. 2015;6(1):33.
37. Thibodeau SN, French AJ, McDonnell SK, Cheville J, Middha S, Tillmans L, Riska S, Baheti S, Larson MC, Fogarty Z, Zhang Y, Larson N, Nair A, O’Brien D, Wang L, Schaid DJ. Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set. Nature Communications. 2015;6:8653. (determined analytic method, ran analyses, provided statistical interpretation)
38. Zhang Y, Zhu Q, Liu H. Next generation informatics for big data in precision medicine era. BioData Mining. 2015;8(1):34.
39. Kitange GJ, Mladek AC, Schroeder MA, Pokorny JC, Carlson BL, Zhang Y, Nair AA, Lee JH, Yan H, Decker PA, Zhang Z, Sarkaria JN. Retinoblastoma binding protein 4 modulates temozolomide sensitivity in glioblastoma by regulating DNA repair proteins. Cell Reports. 2016;14(11):2587-98. (determined analytic method, ran analyses, provided statistical interpretation)
40. Fan L, Peng G, Sahgal N, Fazli L, Gleave M, Zhang Y, Hussain A, Qi J. Regulation of c-Myc expression by the histone demethylase JMJD1A is essential for prostate cancer cell growth and survival. Oncogene. 2016;35(19):2441-52. (determined analytic method, ran analyses, provided statistical interpretation)
41. Dong D, Zhang Y*, Reece EA, Wang L, Harman CR, Yang P. microRNA expression profiling and functional annotation analysis of their targets modulated by oxidative stress during embryonic heart development in diabetic mice. Reproductive Toxicology. 2016;11(65):365-374. (primary author to design the experiment, perform the analysis, and write the manuscript)
42. Jackson IL, Zhang Y*, Bentzen S, Hu J, Zhang C, Katz BP, Vujaskovic Z. Pathophysiological mechanisms underlying phenotypic differences in pulmonary radioresponse among murine strains. Scientific Reports. 2016;6:36579. (primary author to design the experiment, perform the analysis, and write the manuscript)
43. Wang L, Ma X, Xu X, Zhang Y. Systematic identification and characterization of cardiac long intergenic noncoding RNAs in zebrafish. Scientific Reports. 2017;7(1):1250.
44. Kaczanowska S, Joseph AM, Guo J, Tsai AK, Lasola JJ, Younger K, Zhang Y, Gonzales CV, Davila E. A synthetic CD8α:MyD88 coreceptor enhances CD8+ T-cell responses to weakly immunogenic and lowly expressed tumor antigens. Cancer Research. 2017; 77(24):7049-7058. (determined analytic method, ran analyses, provided statistical interpretation)
45. Jackson IL, Zhang Y*, Bentzen S, Hu J, Zhang C, Katz BP, Vujaskovic Z. Corrigendum: Pathophysiological mechanisms underlying phenotypic differences in pulmonary radioresponse. Scientific Reports. Sci Rep. 2017;7:46782. (primary author to design the experiment, perform the analysis, and write the manuscript)
46. Zhang Y, Shen F, Mojarad MR, Li D, Tao C, Yu Y, Liu S, Liu H. Systematic identification of latent disease-gene relationships from PubMed articles. PLOS ONE. 2018; 13(1): e0191568.
47. Scheid AD, Keulen V, Felts SJ, Neier SC, Middha S, Nair AA, Techentin RW, Gilbert BK, Jen J, Neuhauser C, Zhang Y^#, Pease LR. Gene expression signatures characterized by longitudinal stability and interindividual variability delineate baseline phenotypic groups with distinct responses to immune stimulation. The Journal of Immunology. 2018; 200(5):1917-1928. (^#co-senior author to oversee computational design, analyses, and results interpretation)
48. Wang L, Felts SJ, Van Keulen VP, Scheid AD, Block MS, Markovic SN, Pease LR, Zhang Y. Integrative genome-wide analysis of long noncoding RNAs in diverse immune cell types of melanoma patients. Cancer Research. 2018;78(15):4411-4423.
49. Wang J, Zhao L, Ye Y, Zhang Y. Adverse event detection by integrating Twitter data and VAERS. Journal of Biomedical Semantics. 2018; 9:19.
50. Wang L, Felts SJ, Van Keulen VP, Pease LR, Zhang Y. Exploring the effect of library preparation on RNA sequencing experiments. Genomics. 2018;111(6), 1752-1759.
51. Zandberg DP, Tallon LJ, Nagaraj S, Sadzewicz LK, Zhang Y, Strome MB, Zhao XE, Vavikolanu K, Zhang X, Papadimitriou JC, Hubbard FA, Bentzen SM, Strome SE, Fraser CM. Intratumor genetic heterogeneity in squamous cell carcinoma of the oral cavity. Head Neck. 2019;41(8):2514-2524. (determined analytic method, ran analyses, provided statistical interpretation)
52. Petri M, Fu W, Ranger A, Allaire N, Cullen P, Magder LS, Zhang Y. Association between changes in gene signatures expression and disease activity among patients with systemic lupus erythematosus. BMC Medical Genomics. 2019;12(1):1-9.
53. Ramalingam S, Ramamurthy VP, Gediya LK, Murigi FN, Purushottamachar P, Huang W, Choi EY, Zhang Y, Vasaitis TS, Kane MA, Lapidus RG, Njar VCO. The novel mnk1/2 degrader and apoptosis inducer VNLG-152 potently inhibits TNBC tumor growth and metastasis. Cancers (Basel). 2019;11(3):299. (determined analytic method, ran analyses, provided statistical interpretation)
54. Kohli M, Oberg AL, Mahoney DW, Riska SM, Sherwood R, Zhang Y, Zenka RM, Sahasrabudhe D, Qin R, Zhang S. Serum Proteomics on the basis of discovery of predictive biomarkers of response to androgen deprivation therapy in advanced prostate cancer. Clinical Genitourinary Cancer. 2019;17(4):248-253. (determined analytic method, ran analyses, provided statistical interpretation)
55. Ren JJ, Sun T, He Y, Zhang Y. A statistical analysis of vaccine-adverse event data. BMC Medical Informatics and Decision Making. 2019;19(1):101.
56. Hu G, Zhang Y*, Gupta M. RIP sequencing in mantle cell lymphoma identifies functional long non-coding RNAs associated with translation machinery. Blood Cancer Journal. 2019; 9(8):1-4. (primary author to design the experiment, perform the analysis, and write the manuscript)
57. Ding Y, Wang L, Zhang Y^#, Xu X. Haploinsufficiency of mechanistic target of rapamycin attenuates bag3 cardiomyopathy in adult zebrafish. Disease Models & Mechanisms. 2019; 12(10): dmm040154. (^#co-senior author to oversee computational design, analyses, and results interpretation)
58. Kwegyir-Afful A, Ramalingam S, Ramamurthy V, Purushottamachar P, Murigi F, Vasaitis T, Huang W, Kane M, Zhang Y, Ambulos N, Tiwari S, Srivastava P, Nnane I, Hussain A, Qiu Y, Weber D, Njar V. Galeterone and the next generation galeterone analogs, VNPP414 and VNPP433-3β exert potent therapeutic effects in castration-/drug-resistant prostate cancer preclinical models in vitro and in vivo. Cancers (Basel). 2019;11(11):1637. (determined analytic method, ran analyses, provided statistical interpretation)
59. Dorgan JF, Jung S, Dallal CM, Zhan M, Stennett CA, Zhang Y, Eckert RL, Snetselaar LG, Van Horn L. Alcohol consumption and serum metabolite concentrations in young women. Cancer Causes Control. 2020;31(2):113-126. (determined analytic method, ran analyses, provided statistical interpretation)
60. Fava A, Buyon J, Mohan C, Zhang T, Belmont HM, Izmirly P, Clancy R, Trujillo JM, Fine D, Zhang Y, Magder L, Rao DA, Arazi A, Berthier CC, Davidson A, Diamond B, Hacohen N, Wofsy D, Apruzzese W, the Accelerating Medicines Partnership in SLE network, Raychaudhuri S, Petri M. Integrated urine proteomics and renal single-cell genomics identify an IFN-γ response gradient in lupus nephritis. JCI Insight. 2020; 5(12): e138345. (determined analytic method, ran analyses, provided statistical interpretation)
61. Geng D, Ciavattone N, Lasola JJ, Shrestha R, Sanchez A, Guo J, Vlk A, Younis R, Wang L, Brown A, Zhang Y, Velasco-Gonzalez C, Tan AC, Davila E. Induction of IRAK-M in melanoma induces caspase-3 dependent apoptosis by reducing TRAF6 and calpastatin levels. Communications Biology. 2020; 3(1):1-13. (determined analytic method, ran analyses, provided statistical interpretation)
62. Barry KH, Mohanty K, Erickson P, Rose G, Cellini A, Clark K, Ambulos N, Yin J, Yan L, Poulin M, Meyer A, Zhang Y, Bentzen S, Burke A, Hussain A, Berndt S. MYC DNA methylation in prostate tumor tissue is associated with tumor aggressiveness. Genes. 2020;12(1):12. (determined analytic method, ran analyses, provided statistical interpretation)
63. Inglut CT, Gray K, Vig S, Jung J, Stabile J, Zhang Y*, Stroka KM, Huang HC. Photodynamic priming modulates endothelial cell-cell junction phenotype for light-activated remote control of drug delivery. IEEE Journal of Selected Topics in Quantum Electronics. 2021; 27(4):7200311. (^*primay author to oversee computational design, analyses, and results interpretation)
64. Serfecz JC, Saadin A, Santiago CP, Zhang Y, Bentzen SM, Vogel SN, Feldman RA. C5a activates a pro-inflammatory gene expression profile in human gaucher iPSC-derived macrophages. International Journal of Molecular Sciences. 2021; 22(18): 9912. (determined analytic method, ran analyses, provided statistical interpretation)
65. Basehore S, Bohlman S, Weber C, Swaminathan S, Zhang Y, Jang C, Arany Z, Clyne AM. Laminar flow on endothelial cells suppresses eNOS O-GlcNAcylation to promote eNOS activity. Circulation Research. 2021;129(11):1054-1066. (determined analytic method, ran analyses, provided statistical interpretation)
66. Sorrin AJ, Liu C, Cicalo J, Reader J, Najafali D, Zhang Y, Roque DM, Huang HC. Photodynamic priming improves the anti-migratory activity of prostaglandin E receptor 4 antagonist in cancer cells. Cancers. 2021;13(21): 5259. (determined analytic method, ran analyses, provided statistical interpretation)
67. Bu H, Ding Y, Li J, Zhu P, Shih YH, Wang M, Zhang Y, Lin X, Xu X. Inhibition of mTOR or MAPK ameliorates vmhcl/myh7 cardiomyopathy in zebrafish. JCI Insight. 2021;6(24):e154215. (determined analytic method, ran analyses, provided statistical interpretation)
68. Ferraris D, Lapidus R, Truong P, Bollino D, Carter-Cooper B, Lee M, Chang E, LaRossa-Garcia M, Dash S, Gartenhaus R, Choi EY, Kipe O, Lam V, Mason K, Palmer R, Williams E, Ambulos N, Kamangar F, Zhang Y, Kapadia B, Jing Y, Emadi A. Pre-clinical activity of amino-alcohol dimeric naphthoquinones as potential therapeutics for acute myeloid leukemia. Anti-Cancer Agents in Medicinal Chemistry. 2022;22(2):239-253. (determined analytic method, ran analyses, provided statistical interpretation)
69. De Castro A, Pranda MA, Gray KM, Merlo-Coyne J, Girma N, Hurwitz M, Zhang Y^#, Stroka KM. Morphological phenotyping of organotropic brain- and bone-seeking triple negative metastatic breast tumor cells. Frontiers in Cell and Developmental Biology. 2022; 10: 790410. (^#co-senior author to oversee computational design, analyses, and results interpretation)
70. Nian Y, Du J, Bu L, Li F, Hu X, Zhang Y^#, Tao C. Knowledge graph-based neurodegenerative diseases and diet relationship discovery. Proceedings of CIBB 2021. (^#co-senior author to oversee computational design, analyses, and results interpretation)
71. Thomas E, Thankan RS, Purushottamachar P, Huang W, Kane MA, Zhang Y, Ambulos N, Weber DJ, Njar VCO. Transcriptome profiling reveals that VNPP433-3β, the lead next-generation galeterone analog inhibits prostate cancer stem cells by downregulating EMT and stem cell markers. Molecular Carcinogenesis. 2022; 61: 643- 654. (determined analytic method, ran analyses, provided statistical interpretation)
72. Adebamowo CA, Adeyemo A, Ashaye A, Akpa OM, Chikowore T, Choudhury A, Fakim YJ, Fatumo S, Hanchard N, Hauser M, Mitchell B, Mulder N, Ofori-Acquah SF, Owolabi M, Ramsay M, Tayo B, Vasanth Kumar ABV, Zhang Y, Adebamowo SN. Polygenic risk scores for CARDINAL study. Nature Genetics. 2022; 54: 527–530. (Participated the literature review and data analysis design)
73. Thomas E, Thankan RS, Purushottamachar P, Huang W, Kane MA, Zhang Y, Ambulos N, Weber DJ, Njar V. Novel AR/AR-V7 and Mnk1/2 Degrader, VNPP433-3β: Molecular Mechanisms of Action and Efficacy in AR-Overexpressing Castration Resistant Prostate Cancer In Vitro and In Vivo Models. Cells. 2022; 11(17): 2699. (determined analytic method, ran analyses, provided statistical interpretation)
74. Dorgan JF, Ryan AS, LeBlanc ES, Horn LV, Magder LS, Snetselaar LG, Zhang Y, Dallal CM, Jung S, Shepherd JA. A Comparison of Associations of BMI and DXA Measured Percent Fat and Total Fat with Global Serum Metabolites in Young Women. Obesity. (in press) (determined analytic method, ran analyses, provided statistical interpretation)
75. Nian Y, Hu X, Zhang R, Feng J, Du J, Li F, Bu L, Zhang Y, Chen Y, Tao C. Mining on Alzheimer's Diseases Related Knowledge Graph to Identity Potential AD-related Semantic Triples for Drug Repurposing. BMC Bioinformatics. 2022; 23:407. (Oversaw computational design, analyses, and results interpretation)
76. Ding Y, Lang D, Yan J, Bu H, Li H, Jiao K, Yang J, Ni H, Morotti S, Le T, Clark KJ, Port J, Ekker SC, Cao H, Zhang Y, Wang J, Grandi E, Li Z, Shi Y, Li Y, Glukhov AV, Xu X. A phenotype-based forward genetic screen identifies Dnajb6 as a sick sinus syndrome gene. eLife. 2022; 11:e77327. (Oversaw computational design, analyses, and results interpretation)
77. Dorgan JF, Baer HJ, Bertrand KA, LeBlanc ES, Jung S, Magder LS, Snetselaar LG, Stevens VJ, Zhang Y, Van Horn L. Childhood adiposity, serum metabolites and breast density in young women. Breast Cancer Research. 2022; 24:91. (Oversaw computational design, analyses, and results interpretation)
78. DiCarlo AL, Cassatt DR, Rios CI, Satyamitra MM, Zhang Y, Golden TG, Taliaferro LP. Making connections: the scientific impact and mentoring legacy of Dr. John E. Moulder. International Journal of Radiation Biology. 2023;15:1-7. (Cover Story; Oversaw computational design, analyses, and results interpretation)
79. He S, Huang WY, Machiela NJ, Mitchell BD, Zhang Y, Chen S, Freeman LB, Erickson P, Freedman ND, Hofmann J, Barry KH, Berndt SI. A linear relationship between the number of cancers among first-degree relatives and the risk of multiple primary cancers. Cancer Prevention Research. 2024; OF1-OF7. (Oversaw computational design, analyses, and results interpretation)
80. Hsu H, Zanettini C, Coker M, Boudova S, Rach D, Mvula G, Divala TH, Mungwira RG, Boldrin F, Degiacomi G, Manganelli R, Laufer MK, Zhang Y, Marchionni L, Cairo C. Concomitant assessment of PD-1 and CD56 expression identifies subsets of cord blood V2 T cells with different cytotoxic potential. Cell Immunology. 2024;395-396:104797. (Oversaw computational design, analyses, and results interpretation)
81. Jung S, Flaherty S, Dallal CM, Hylton N, Klifa C, Paris K, Shepherd J, Snetselaar LG, Horn LV, Zhang Y, Dorgan JF. Untargeted serum metabolomic profiles and breast density in young women. Cancer Causes Control. 2024;35(2):323-334. (Oversaw computational design, analyses, and results interpretation)
82. Hou K, Gogarten S, Kim J, Hua X, Dias JA, Sun Q, Wang Y, Tan T, Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group, Atkinson EG, Martin A, Shortt J, Hirbo J, Li Y, Pasaniuc B, Zhang H. Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations. Bioinformatics. 2024 Mar 29;40(4):btae148. (Oversaw analyses and results interpretation)
83. Boyle J, Yau J, Slade JL, Butts DA, Zhang Y, Legesse TB, Cellini A, Clark K, Park JY, Wimbush J, Ambulos N, Jr, Yin J, Hussain A, Onukwugha E, Knott CL, Wheeler DC, Barry KH. Neighborhood disadvantage and prostate tumor RNA expression of stress-related genes. JAMA Network Open. 2024;7(7):e2421903. (Oversaw computational design, analyses, and results interpretation)
84. Thankan RS, Thomas E, Weldemariam MM, Purushottamachar P, Huang W, Kane MA, Zhang Y, Ambulos N, Wang B, Weber D, Njar VCO. Thermal proteome profiling and proteome analysis using high-definition mass spectrometry demonstrate modulation of cholesterol biosynthesis by next-generation galeterone analog VNPP433-3β in castration-resistant prostate cancer. Molecular Oncology. 2025 Feb 26. doi: 10.1002/1878-0261.70009. (Oversaw computational design, analyses, and results interpretation)
85. Midde A, Arri N, Kristian T, Mukherjee S, Gupta PSS, Zhang Y, Karbowski M, Waddell J, Maharajan N, Hassan MS, O'Hagan HM, Zalzman M, Banerjee A. Targeting mitochondrial ribosomal protein expression by andrographolide and melatonin for colon cancer treatment. Cancer Letters. 2025; Jun 1:619:217647. (Oversaw computational design, analyses, and results interpretation)
86. Onyenobi E, Zhong M, Soremekun O, Kamiza A, Boua R, Chikwore T, ACCME Research Group, Fatumo S, Choudhury A, Hazelhurst S, Adebamowo C, Ramsay M, Tayo B, Albrecht JS, O’Connor TD, Zhang Y, Mitchell BD, Adebamowo SN. Development and validation of polygenic risk scores for blood pressure traits in continental african populations. Circulation: Genomic and Precision Medicine. 2025; May 27:e005048. (Oversaw computational design, analyses, and results interpretation)
87. Khan AT, Adebamowo C, Fullerton SM, Hirbo J, Konigsberg IR, Kraft P, Martin I, Nelson SC, Ramsay M, Wojcik GL, Adebamowo SN, Conomos MP, Darst BF, Hysong MR, Li Y, Martin AR, Mathias RA, Rich SS, Sakoda LC, Schrider DR, Sharma J, Smith JL, Sun Q, Zhang Y, Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium, Gogarten SM. A data model for population descriptors in genomic research. American Journal of Human Genetics. 2025 Jul 3;112(7):1504-1514. (Oversaw computational design, analyses, and results interpretation)
88. Smith JL, Wong Q, Hornsby W, Conomos MP, Heavner BD, Kullo IJ, Psaty BM, Rich SS, Stilp AM, Tayo B, Natarajan P, Nelson SC, Adebamowo SN, Zhang Y, Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Data Sharing Working Group, Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium. Data sharing in the PRIMED consortium: design, implementation, and recommendations for future policymaking. American Journal of Human Genetics. 2025 Aug 7;112(8):1754-1768. (Led the working group and oversaw the workflow design, analyses, and results interpretation)
89. Taliaferro LP, Brenner DJ, Amundson SA, Garty G, Zhang Y, Davies EW, Carrier F, Ross JR, Cline JM, Chao NJ. Centers for Medical Countermeasures Against Radiation Consortium: past, present, and beyond. Radiation Research. 2025 Sep 1;204(3):238-252. (Oversaw computational design, analyses, and results interpretation)
90. Ding Y, Yan F, Yoon B, Wei W, Ruff DM, Zhang Y, Lin X, Xu X. An mTOR-Tfeb-Fabp7a signaling axis can be harnessed to ameliorate bag3 cardiomyopathy in adult zebrafish. Aging Cell. 2025 Sep 8:e70216. (Oversaw computational design, analyses, and results interpretation)

2012     Travel Award, the 20th Annual International Conference on Intelligence Systems for Molecular Biology
2019    Merit Scholarship, Women in AMIA Leadership Program, American Medical Informatics Association
2020    Winner of WIA (Women in AMIA) Leadership 2020 Seed Grant, American Medical Informatics Association
2025    Fellow, American Medical Informatics Association (FAMIA), Recognized for sustained professional achievement and leadership in biomedical informatics

04/01/21 – 03/31/26               (Co-Inv 2%) PI: H. Huang

“Addressing Chemoresistance in Pancreatic and Ovarian Cancers: Photodynamic Priming and Repurposing of Tetracyclines using Targeted Photo-Activable Multi-Inhibitor Liposome”

NIBIB/NIH, R01 CA260340

Annual Direct Costs: $548,466

Total Direct Costs:      $2,742,330

Lead Bioinformatician and Biostatistician

06/01/21 – 05/31/26               (Co-Inv 20%) PI: S. Adebamowo

“CARdiometabolic Disorders IN African-ancestry PopuLations (CARDINAL) Study Site”

NCI/NIH, U01 HG011717

Annual Direct Cost: $790,000

Total Direct Costs: $3,950,000

Lead Bioinformatician and Biostatistician

07/01/21 – 06/30/26               (Co-Inv 4%) PI: H. Wang

“Novel noncanonical actions of CAR in human liver”

NCI/NIH, R01 CA262084

Annual Direct Cost: $250,000

Total Direct Costs: $1,250,000

Lead Bioinformatician and Biostatistician

08/01/21 – 07/31/26               (Co-Inv 5%) PI: T. Owonikoko

“University of Maryland Comprehensive Cancer Center Support Grant”

NCI/NIH, P30 CA134274  

Annual Direct Costs: $1,500,000

Total Direct Costs:      $7,500,000

Lead Bioinformatician

07/01/22 – 06/30/26               (Co-Inv 4%) PI: J. Lin

“Co-targeting IL-6 and CDK4/6 pathways as a novel approach of preventive therapy for triple-negative breast cancer”

VA Merit Research Award

Annual Direct Costs: $150,000

Total Direct Costs:      $600,000

Lead Bioinformatician and Biostatistician

07/01/22 – 06/30/26               (Site-PI 25%) PI: X. Xu

“Genetic Studies of Sarcomere-based Cardiac Diseases”

NHLBI/NIH, R01 HL081753  

Annual Direct Costs: $ 375,626

Total Direct Costs:      $1,502,504

Lead Bioinformatician and Biostatistician

01/12/23 – 12/31/27               (Co-Inv 2%) PI: H. Huang

“Targeting Fluid Stress-induced Chemoresistance in a 3D Carcinomatosis Perfusion Model Using Mechanism-based Photo-immunoconjugate Nanoparticles”

NIBIB/NIH, R01 CA256710

Annual Direct Costs: $450,191

Total Direct Costs:      $2,250,955

Lead Bioinformatician and Biostatistician

07/01/25 – 06/30/26               (Co-Inv 20%) PI: T. Owonikoko

“Cigarette Restitution Fund Program”

                                                Maryland Department of Health and Mental Hygiene  

Annual Direct Costs: $ 10,400,000

Total Direct Costs:      $ 10,400,000

Lead Bioinformatician

05/01/25 – 02/28/29               (Site-PI 4%) PI: X. Xu

“Epicardial remodeling in cardiomyopathy and cardiac aging”

NHLBI/NIH, R01 HL107304

Annual Direct Costs: $398,610

Total Direct Costs:      $1,594,440

Lead Bioinformatician and Biostatistician

05/01/25 – 02/28/29               (Co-Inv 10%) PI: Erika Davies

“Epicardial remodeling in cardiomyopathy and cardiac aging”

NHLBI/NIH, R01 HL107304

Annual Direct Costs: $398,610

Total Direct Costs:      $1,594,440

Lead Bioinformatician and Biostatistician

04/01/26 – 03/31/30               (Co-Inv 6%) PI: Kathryn Barry

“Neighborhood disadvantage, race, prostate tumor RNA

expression of stress-related genes, and tumor aggressiveness”

American Cancer Society Research Scholar Grant

Annual Direct Costs: $215,000

Total Direct Costs:      $860,000

Lead Bioinformatician and Biostatistician

https://wie.ieee.org/tec/ieee-r2-wie-meeting-and-seminar-from-big-data-to-precision-medicine-a-data-science-perspective/

https://www.medschool.umaryland.edu/news/2021/UM-School-of-Medicine-Researchers-Awarded-5-Million-NIH-Grant-to-Improve-Use-of-Genetic-Risk-Scores-in-Diverse-Populations.html

https://sites.google.com/view/amiawomen/meet-our-scholars

https://scholar.google.com/citations?user=m_lEk-IAAAAJ&hl=en

https://www.linkedin.com/in/yuji-zhang-4a7a6716/