Edgar J. Hernandez

Edgar J. Hernandez, PhD

Languages spoken: Spanish, English

Academic Information

Departments Primary - Biomedical Informatics

I am a multidisciplinary researcher with a passion for bridging genomics and clinical outcomes. My journey began with a Bachelor’s degree in Biology from Universidad Nacional de Colombia, followed by a Ph.D. in Ecology, Systematics, and Evolution from the University of Missouri. Currently, I am a Research Assistant Professor in the Department of Biomedical Informatics at the University of Utah.

My expertise lies at the intersection of biostatistics, artificial intelligence (AI), and predictive tools. During my time at the Yandell lab, I contributed to the development of innovative methods that leverage electronic health record (EHR) data for personalized risk predictions. Collaborating with consortia and industry partners, I have successfully applied probabilistic graphical models and machine learning approaches to quantify risk and classify clinical outcomes. My research thrives on a multidisciplinary collaborative approach, enriching tool and methods development across diverse areas of human health, from cancer research to pediatric cardiology. I contribute to cutting-edge tools for diagnosing rare genetic diseases using whole exome sequencing (WES) and whole genome sequencing (WGS). Furthermore, I am actively involved in multi-omics research, particularly transcriptomics and metagenomics analysis, aiming to uncover molecular signatures during acute phases of multisystem inflammatory syndrome in children (MIS-C).

Research Statement

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 is 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. 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.

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.

Education History

Undergraduate Universidad Nacional de Colombia
 BS
Professional Medical University of Missouri-St. Louis
 PhD
Fellowship University of Utah
 Postdoctoral Fellow

Selected Publications

Journal Article

  1. 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, Löscher BS, Franke A, Boone B, Levy SE, Õunap 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. Reisinger E, Sacristan S, Nussenzveig R, Wesolowski S, Hernandez EJ, Henrie AR, Maughan BL, Swami U, Yandell M, Grivas (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). Journal of clinical oncology, 39(15_suppl), 4542.
  7. 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 (2022). An Explainable Artificial Intelligence Approach for Predicting Cardiovascular Outcomes using Electronic Health Records. medRxiv,
  8. Covey KR, Dunham KM, Hernandez EJ, Walton ML, Young DF, Zanne A (2017). Dissecting the Effects of Diameter on Wood Decay Emphasizes the Importance of Cross-Stem Conductivity in Fraxinus americana. Ecosystems (New York, N.Y.), 20, 1-13.
  9. Riveros AJ, Hernandez EJ, Wcislo (2009). Nesting biology in a population of Euglossa dodsoni Moure (Hymenoptera: Euglossinae) in Panama. Journal of the Kansas Entomological Society, 82(2), 210-4.
  10. Hernandez EJ, Roubik D, Nates-Parra (2009). Morphometric Analysis of Bees in the Trigona fulviventris Group (Hymenoptera: Apidae). Journal of the Kansas Entomological Society, 80(3), 205-12.
  11. Riveros A, Hernandez EJ, Nates-Parra (2006). Morphological constraints and nectar robbing in three Andean Bumblebee species, (Hymenoptera, Apidae, Bombini). Caldasia, 28(1),
  12. Hernandez EJ, Nates-Parra (2004). el subgénero Trigona s. Str. Jurine 1808 (hymenoptera: apidae: meliponinae) en Colombi. Acta biológica colombiana, 9(2),
  13. Hu C, Beebe K, Hernandez EJ, Lazaro-Guevara JM, Revelo MP, Huang Y, Maschek JA, Cox JE, Kohan D (2022). Multiomic identification of factors associated with progression to cystic kidney disease in mice with nephron Ift88 disruption. American journal of physiology. Renal physiology, 322(2), F175-F192.
  14. Kiser AC, Schliep KC, Hernandez EJ, Peterson CM, Yandell M, Eilbeck (2024). An artificial intelligence approach for investigating multifactorial pain-related features of endometriosis. PloS one, 19(2), e0297998.
  15. Puckelwartz MJ, Pesce LL, Hernandez EJ, Webster G, Dellefave-Castillo LM, Russell MW, Geisler SS, Kearns SD, Karthik F, Etheridge SP, Monroe TO, Pottinger TD, Kannankeril PJ, Shoemaker MB, Fountain D, Roden DM, Faulkner M, MacLeod HM, Burns KM, Yandell M, Tristani-Firouzi M, George AL Jr, McNally E (2024). The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young. Genome medicine, 16(1), 13.
  16. Miller TA, Hernandez EJ, Gaynor JW, Russell MW, Newburger JW, Chung W, Goldmuntz E, Cnota JF, Zyblewski SC, Mahle WT, Zak V, Ravishankar C, Kaltman JR, McCrindle BW, Clarke S, Votava-Smith JK, Graham EM, Seed M, Rudd N, Bernstein D, Lee TM, Yandell M, Tristani-Firouzi (2023). Genetic and clinical variables act synergistically to impact neurodevelopmental outcomes in children with single ventricle heart disease. Communications medicine, 3(1), 127.
  17. Zimmerman RM, Hernandez EJ, Watkins WS, Blue N, Tristani-Firouzi M, Yandell M, Steinberg B (2023). An Explainable Artificial Intelligence Approach for Discovering Social Determinants of Health and Risk Interactions for Stroke in Patients With Atrial Fibrillation. The American journal of cardiology, 201, 224-226.
  18. Peterson B, Hernandez EJ, Hobbs C, Malone Jenkins S, Moore B, Rosales E, Zoucha S, Sanford E, Bainbridge MN, Frise E, Oriol A, Brunelli L, Kingsmore SF, Yandell (2023). Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning. Genome medicine, 15(1), 18.
  19. Srygley RB, Dudley R, Hernandez EJ, Kainz F, Riveros AJ, Ellington C (2023). Quantifying the Aerodynamic Power Required for Flight and Testing for Adaptive Wind Drift in Passion-Vine Butterflies Heliconius sara (Lepidoptera: Nymphalidae). Insects, 14(2),
  20. Malone-Jenkins, Sabrina and Shayota, Brian and Solorzano, Chelsea and Palmquist, Rachel and Boyden, Steven and Moore, Barry and Nicholas, Thomas and Mao, Rong and Bayrak-Toydemir, Pinar and Noble, Katherine and other (2023). P243: the Utah NeoSeq Project: developing and implementing genomic sequencing in acute neonatal care. Genetics in Medicine Open, 1(1),
  21. Moore, Barry and Nicholas, Thomas and Mao, Rong and Shayota, Brian and Boyden, Steven and Solorzano, Chelsea and Palmquist, Rachel and Bayrak-Toydemir, Pinar and Noble, Katherine and Farrell, Andrew and other (2023). P516: RNASeq analysis identifies the pathogenicity of inherited synonymous splice-region variant in NEB, confirming a diagnosis of neonatal nemaline myopathy 2. Genetics in Medicine Open, 1(1),
  22. Zimmerman, Raquel M and Hernandez, Edgar Javier and Tristani-Firouzi, Martin and Silver, Robert M and Yandell, Mark and Blue, Nathan (2023). A personalized risk stratification tool for perinatal morbidity and mortality using explainable artificial intelligence (AI). American Journal of Obstetrics \& Gynecology, 228(1), S565--S566.
  23. Gorsi, Bushra and Hernandez, Edgar and Moore, Marvin Barry and Moriwaki, Mika and Chow, Clement Y and Coelho, Emily and Taylor, Elaine and Lu, Claire and Walker, Amanda and Touraine, Philippe and other (2022). Causal and candidate gene variants in a large cohort of women with primary ovarian insufficiency. The Journal of Clinical Endocrinology \& Metabolism, 107(3), 685--714.
  24. Nicholas, Thomas J and Al-Sweel, Najla and Farrell, Andrew and Mao, Rong and Bayrak-Toydemir, Pinar and Miller, Christine E and Bentley, Dawn and Palmquist, Rachel and Moore, Barry and Hernandez, Edgar J and other (2022). Comprehensive variant calling from whole-genome sequencing identifies a complex inversion that disrupts ZFPM2 in familial congenital diaphragmatic hernia. Molecular Genetics \& Genomic Medicine, 10(4), e1888.
  25. Thomas, V Mathew and Chigarira, B and Sayegh, Nicolas and Hernandez, EJ and Tripathi, N and Kumar, S Adidam and Goel, D and Tandar, C and Mcfarland, TR and Yandell, M and other (2022). 1413P Tumor transcriptomic profiling of patients (pts) with metastatic castration-sensitive prostate cancer (mCSPC) who do not achieve optimal PSA response to intensified androgen deprivation therapy (ADT-I). Annals of Oncology, 33, S1191.
  26. Simeone CA, Wilkerson JL, Poss AM, Banks JA, Varre JV, Guevara JL, Hernandez EJ, Gorsi B, Atkinson DL, Turapov T, Frodsham SG, Morales JCF, O'Neil K, Moore B, Yandell M, Summers SA, Krolewski AS, Holland WL, Pezzolesi M (2022). A dominant negative ADIPOQ mutation in a diabetic family with renal disease, hypoadiponectinemia, and hyperceramidemia. NPJ genomic medicine, 7(1), 43.
  27. Swami U, Zimmerman RM, Nussenzveig RH, Hernandez EJ, Jo Y, Sayegh N, Wesolowski S, Kiedrowski LA, Barata PC, Lemmon GH, Bilen MA, Heath EI, Nandagopal L, Babiker HM, Pal SK, Lilly M, Maughan BL, Haaland B, Yandell M, Sartor O, Agarwal (2022). Genomic landscape of advanced prostate cancer patients with BRCA1 versus BRCA2 mutations as detected by comprehensive genomic profiling of cell-free DNA. Frontiers in oncology, 12, 966534.
  28. Zimmerman RM, Hernandez EJ, Yandell M, Tristani-Firouzi M, Silver RM, Grobman W, Haas D, Saade G, Steller J, Blue N (2025). AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios. BMC pregnancy and childbirth, 25(1), 80.
  29. Watkins WS, Hernandez EJ, Miller T, Blue N, Zimmerman R, Griffiths E, Frise E, Bernstein D, Boskovski M, Brueckner M, Chung W, Gaynor JW, Gelb B, Goldmuntz E, Gruber P, Newburger J, Roberts A, Morton S, Mayer J, Seidman C, Seidman J, Shen Y, Wagner M, Yost HJ, Yandell M, Tristani-Firouzi (2024). Genome Sequencing is Critical for Forecasting Outcomes Following Congenital Cardiac Surgery.
  30. Olsen BB, Tristani-Firouzi M, Eilbeck K, Yandell M, Hernandez E (2025). Quantifying lifetime risk for 1,401 infectious diseases across the diabetes spectrum using a Bayesian approach.
  31. Watkins WS, Hernandez EJ, Miller TA, Blue NR, Zimmerman RM, Griffiths ER, Frise E, Bernstein D, Boskovski MT, Brueckner M, Chung WK, Gaynor JW, Gelb BD, Goldmuntz E, Gruber PJ, Newburger JW, Roberts AE, Morton SU, Mayer JE Jr, Seidman CE, Seidman JG, Shen Y, Wagner M, Yost HJ, Yandell M, Tristani-Firouzi (2025). Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery. Nature communications, 16(1), 6365.
  32. Peterson B, Juarez EF, Moore B, Hernandez EJ, Frise E, Li J, Lussier Y, Tristani-Firouzi M, Reese MG, Malone Jenkins S, Kingsmore SF, Bainbridge MN, Yandell (2025). MPSE identifies newborns for whole genome sequencing within 48¿h of NICU admission. NPJ genomic medicine, 10(1), 47.
  33. Malone Jenkins S, Palmquist RN, Moore B, Boyden SE, Nicholas TJ, Bayrak-Toydemir P, Mao R, Farrell JAR, Holt CH, Rynearson SG, Solorzano CM, Ward A, Best DH, Al-Sweel N, Bentley DL, Brunelli L, Chow CY, Close DW, Cormier MJ, Deshotel MJ, Durtschi J, Eide EJ, Floyd L, Fredrickson EK, Fulmer ML, Hernandez EJ, Kapron AL, Karren MA, Lewis RG, Miller CE, Murtaugh LC, Nicholson KE, Noble K, O'Fallon BD, O'Shea JM, Pattison DC, Pedersen BS, Petersen BJ, Peterson BD, Pizzo L, Reynolds HM, Rindler P, Torr CB, Wen T, Yost HJ, Zhao J, Yandell M, Marth GT, Quinlan AR, Carey JC, Shayota BJ, Tristani-Firouzi M, Bonkowsky J (2025). The Utah NeoSeq Project: a collaborative multidisciplinary program to facilitate genomic diagnostics in the neonatal intensive care unit. NPJ genomic medicine, 10(1), 26.

Review

  1. Zimmerman RM, Hernandez EJ, Tristani-Firouzi M, Yandell M, Steinberg B (2025). Explainable artificial intelligence for stroke risk stratification in atrial fibrillation. European heart journal. Digital health, 6(3), 317-325.

Conference Proceedings

  1. Reisinger R, Wesolowski S, Swami U, Barata P, Hernandez EJ, Nussenzveig R, Lemmon G, Peterson B, Hensel C, Bilen M (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). 39(6_suppl), 162.

Other

  1. Sayegh, Nicolas and Chigarira, Beverly and Hernandez, Edgar Javier and McFarland, Taylor Ryan and Li, Haoran and Sahu, Kamal Kant and Tripathi, Nishita and Kumar, Shruti Adidam and Nordblad, Blake and Goel, Divyam and other (2022). Transcriptomic profiling of patients (pts) with de-novo metastatic castration-sensitive prostate cancer (DN-mCSPC) versus those with mCSPC that have relapsed from prior localized therapy (PLT-mCSPC).