Edgar J. Hernandez

Edgar J. Hernandez, PhD

Languages spoken: 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.

In addition to my academic roles, I serve as a consultant at Fabric Genomics, where I contribute to cutting-edge tools for diagnosing rare genetic diseases using whole exome sequencing (WES) and whole genome sequencing (WGS). Our AI-based tool, GEM, enables rapid and scalable diagnosis of seriously ill children in neonatal and pediatric intensive care units. 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

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

Selected Publications

Journal Article

  1. Watkins WS, Hernandez EJ, Miller TA, Blue NR, Zimmerman R, 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, Seidman CE, Seidman JG, Shen Y, Wagner M, Yost HJ, Yandell M, Tristani-Firouzi M (2024). Genome Sequencing is Critical for Forecasting Outcomes following Congenital Cardiac Surgery. (Read full article)
  2. Horvath ERB, Stein MG, Mulvey MA, Hernandez EJ, Winter JM (2024). Resistance Gene Association and Inference Network (ReGAIN): A Bioinformatics Pipeline for Assessing Probabilistic Co-Occurrence Between Resistance Genes in Bacterial Pathogens. (Read full article)
  3. Kiser AC, Schliep KC, Hernandez EJ, Peterson CM, Yandell M, Eilbeck K (2024). An artificial intelligence approach for investigating multifactorial pain-related features of endometriosis. PLoS One, 19(2), e0297998. (Read full article)
  4. 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 EM (2024). The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young. Genome Med, 16(1), 13. (Read full article)
  5. 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 others (2023). P243: the Utah NeoSeq Project: developing and implementing genomic sequencing in acute neonatal care. Genetics in Medicine Open, 1(1).
  6. 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 M (2023). Genetic and clinical variables act synergistically to impact neurodevelopmental outcomes in children with single ventricle heart disease. Commun Med (Lond), 3(1), 127. (Read full article)
  7. Zimmerman RM, Hernandez EJ, Watkins WS, Blue N, Tristani-Firouzi M, Yandell M, Steinberg BA (2023). An Explainable Artificial Intelligence Approach for Discovering Social Determinants of Health and Risk Interactions for Stroke in Patients With Atrial Fibrillation. Am J Cardiol, 201, 224-226. (Read full article)
  8. 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 M (2023). Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning. Genome Med, 15(1), 18. (Read full article)
  9. Srygley RB, Dudley R, Hernandez EJ, Kainz F, Riveros AJ, Ellington CP (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). (Read full article)
  10. Zimmerman, Raquel M and Hernandez, Edgar Javier and Tristani-Firouzi, Martin and Silver, Robert M and Yandell, Mark and Blue, Nathan R (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.
  11. 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 others (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).
  12. 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 N (2022). Genomic landscape of advanced prostate cancer patients with BRCA1 versus BRCA2 mutations as detected by comprehensive genomic profiling of cell-free DNA. Front Oncol, 12, 966534. (Read full article)
  13. 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 others (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.
  14. Simeone CA, Wilkerson JL, Poss AM, Banks JA, Varre JV, Guevara JL, Hernandez EJ, Gorsi B, Atkinson DL, Turapov T, Frodsham SG, Morales JCF, ONeil K, Moore B, Yandell M, Summers SA, Krolewski AS, Holland WL, Pezzolesi MG (2022). A dominant negative ADIPOQ mutation in a diabetic family with renal disease, hypoadiponectinemia, and hyperceramidemia. NPJ Genom Med, 7(1), 43. (Read full article)
  15. 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 others (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.
  16. 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 others (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.
  17. 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. (Read full article)
  18. 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. (Read full article)
  19. 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.
  20. 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. (Read full article)
  21. 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.
  22. 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.
  23. 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.
  24. 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. (Read full article)
  25. 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. (Read full article)
  26. 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. (Read full article)
  27. 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.
  28. 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. (Read full article)
  29. 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.
  30. 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.
  31. Riveros A, Hernandez EJ, Nates-Parra G (2006). Morphological constraints and nectar robbing in three Andean Bumblebee species, (Hymenoptera, Apidae, Bombini). Caldasia, 28(1).
  32. Hernandez EJ, Nates-Parra G (2004). el subgénero Trigona s. Str. Jurine 1808 (hymenoptera: apidae: meliponinae) en Colombi. Acta biológica colombiana, 9(2).

Conference Proceedings

  1. 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.

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 others (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).