<p>Throughout my research career, my main interest is to study genetic and ecological principles using bioinformatic methods to solve pressing needs in health care, such as personalized medicine. My goal as a researcher is to i<strong>s to use and develop my bioinformatics skills in high-throughput sequencing and data analysis to develop novel computational tools in the analysis of medical and biological data</strong>. Through my past research, I gained a variety of statistical and bioinformatics skills as well as a deep understanding of evolutionary biology, ecological models and human genetics. This background provides me with a strong foundation and unique perspective to bring to current challenges in bioinformatics research aimed at improving health. My future career goal is to use bioinformatics to improve our utilization of genomic information and sequence information in order to improve human health and disease therapy.</p>
<p>I began my career in biology, studying the ecology of social insects, with the overall goal of understanding the underlying mechanisms that maintain social behavior. Statistics is central to ecology, and from the start I was intensely interested in biostatistical analysis and bioinformatics, particularly classificatory methods and inferential statistical analyses, both of which were fundamental to improving my doctoral research. During my graduate and postdoctoral work, I transitioned my research interests toward understanding the genetic basis of natural variation applied towards human disease. This led me to further broaden my computational biology and biostatistical skills, particularly as regards probabilistic graphical models (PGMs), which I am actively developing to elucidate complex genetic-clinical data interactions. I currently work in the Yandell group as a senior researcher, and function as the group’s chief biostatistician. Over the last several years this role has provided me with ample opportunities to expand upon and hone my bioinformatic skills. Examples include productive collaborations in cardiac pediatrics, nephrology and diabetes research, cancer research and metagenomics.</p>
University of Utah
University of Missouri-St. Louis
Universidad Nacional de Colombia
- Nicholas TJ, Al-Sweel N, Farrell A, Mao R, Bayrak-Toydemir P, Miller CE, Bentley D, Palmquist R, Moore B, Hernandez EJ, Cormier MJ, Fredrickson E, Noble K, Rynearson S, Holt C, Karren MA, Bonkowsky JL, Tristani-Firouzi M, Yandell M, Marth G, Quinlan AR, Brunelli L, Toydemir RM, Shayota BJ, Carey JC, Boyden SE, Malone Jenkins S (2022). Comprehensive variant calling from whole-genome sequencing identifies a complex inversion that disrupts ZFPM2 in familial congenital diaphragmatic hernia. Mol Genet Genomic Med, 10(4), e1888.
- Hu C, Beebe K, Hernandez EJ, Lazaro-Guevara JM, Revelo MP, Huang Y, Maschek JA, Cox JE, Kohan DE (2021). Multiomic identification of factors associated with progression to cystic kidney disease in mice with nephron Ift88 disruption. Am J Physiol Renal Physiol, 322(2), F175-F192.
- Wesolowski S, Lemmon G, Hernandez EJ, Henrie AR, Miller TA, Weyhrauch D, Puchalski MD, Bray, BR, Shah RU, Deshmukh VG, Delaney R, Jost HJ, Eilbeck K, Tristani-Firouzi M, Yandell M (2022). An Explainable Artificial Intelligence Approach for Predicting Cardiovascular Outcomes using Electronic Health Records. medRxiv.
- De La Vega FM, Chowdhury S, Moore B, Frise E, McCarthy J, Hernandez EJ, Wong T, James K, Guidugli L, Agrawal PB, Genetti CA, Brownstein CA, Beggs AH, Lscher BS, Franke A, Boone B, Levy SE, unap K, Pajusalu S, Huentelman M, Ramsey K, Naymik M, Narayanan V, Veeraraghavan N, Billings P, Reese MG, Yandell M, Kingsmore SF (2021). Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases. Genome Med, 13(1), 153.
- Kiser AC, Eilbeck K, Hernandez EJ, Schliep KC, Peterson CM, Yandell M (2021). Identifying anatomical regions associated with endometriosis pain using neighbor-joining clustering. Fertil Steril, 116(3), e207-8.
- Gorsi B, Hernandez EJ, Moore B, Moriwaki M, Chow C, Coelho E, Taylor E, Lu C, Walker A, Touraine P (2021). Causal and Candidate Gene Variants in a Large Cohort of Women with Primary Ovarian Insufficiency. medRxiv.
- Reisinger E, Sacristan S, Nussenzveig R, Wesolowski S, Hernandez EJ, Henrie AR, Maughan BL, Swami U, Yandell M, Grivas P (2021). Genomic predictors of response to PD-1 axis inhibitors in metastatic urothelial cancer (mUC) patients using machine learning analysis of tissue comprehensive genomic profiling (CGP). J Clin Oncol, 39(15_suppl), 4542.
- Beebe K, Robins MM, Hernandez EJ, Lam G, Horner MA, Thummel CS (2020). Drosophila estrogen-related receptor directs a transcriptional switch that supports adult glycolysis and lipogenesis. Genes Dev, 34(9-10), 701-714.
- Watkins WS, Hernandez EJ, Wesolowski S, Bisgrove BW, Sunderland RT, Lin E, Lemmon G, Demarest BL, Miller TA, Bernstein D, Brueckner M, Chung WK, Gelb BD, Goldmuntz E, Newburger JW, Seidman CE, Shen Y, Yost HJ, Yandell M, Tristani-Firouzi M (2019). De novo and recessive forms of congenital heart disease have distinct genetic and phenotypic landscapes. Nat Commun, 10(1), 4722.
- Flygare S, Hernandez EJ, Phan L, Moore B, Li M, Fejes A, Hu H, Eilbeck K, Huff C, Jorde L, G Reese M, Yandell M (2018). The VAAST Variant Prioritizer (VVP): ultrafast, easy to use whole genome variant prioritization tool. BMC Bioinformatics, 19(1), 57.
- Covey KR, Dunham KM, Hernandez EJ, Walton ML, Young DF, Zanne AE (2017). Dissecting the Effects of Diameter on Wood Decay Emphasizes the Importance of Cross-Stem Conductivity in Fraxinus americana. Ecosystems, 20, 1-13.
- Judd TM, Teal PE, Hernandez EJ, Choudhury T, Hunt JH (2015). Quantitative differences in nourishment affect caste-related physiology and development in the paper wasp Polistes metricus. PLoS One, 10(2), e0116199.
- Riveros AJ, Hernandez EJ, Wcislo W (2009). Nesting biology in a population of Euglossa dodsoni Moure (Hymenoptera: Euglossinae) in Panama. Journal of the Kansas Entomological Society, 82(2), 210-4.
- Hernandez EJ, Roubik D, Nates-Parra G (2009). Morphometric Analysis of Bees in the Trigona fulviventris Group (Hymenoptera: Apidae). Journal of the Kansas Entomological Society, 80(3), 205-12.
- Riveros A, Hernandez EJ, Nates-Parra G (2006). Morphological constraints and nectar robbing in three Andean Bumblebee species, (Hymenoptera, Apidae, Bombini). Caldasia, 28(1).
- Hernandez EJ, Nates-Parra G (2004). el subgénero Trigona s. Str. Jurine 1808 (hymenoptera: apidae: meliponinae) en Colombi. Acta biológica colombiana, 9(2).
- Reisinger R, Wesolowski S, Swami U, Barata P, Hernandez EJ, Nussenzveig R, Lemmon G, Peterson B, Hensel C, Bilen MA (2021). Differences in the genomic landscape of advanced prostate cancer (aPC) patients (pts) with BRCA1 versus BRCA2 mutations as detected by machine learning analysis of the comprehensive genomic profile (CGP) of cell-free DNA (cfDNA). American Society of Clinical Oncology, 39(6_suppl), 162.