Matt Might

Matthew Might, PhD

Senior Lecturer on Biomedical Informatics, Part-time

Matt Might  has been the Director of the Hugh Kaul Precision Medicine Institute at the University of Alabama at Birmingham (UAB) since 2017. At UAB, he is the Hugh Kaul Kaul Endowed Chair of Personalized Medicine, a Professor of Internal Medicine and a Professor of Computer Science. His research at UAB focuses on precision prevention, diagnosis and therapeutics across rare disease, cancer and common/chronic conditions. A principal theme in his research is the use of computer and data science to enhance clinical and academic medicine.

From 2016 to 2018, Might was a Strategist in the Executive Office of the President in The White House. At The White House, he worked primarily on President Obama's Precision Medicine Initiative with both the NIH and the Department of Veterans Affairs.

In 2015, Might joined the faculty of the Department of Biomedical Informatics at Harvard Medical School. At DBMI, his research focuses on rare disease discovery and diagnosis, and on the development of personalized therapeutics for rare disease.

Might is co-founder and Chief Scientific Officer of NGLY1.org, a non-profit dedicated to finding treatments for NGLY1 deficiency, and he was a co-founder and Scientific Advisor to Pairnomix, a start-up which identifies potential patient-specific therapies for rare disorders. Q State Biosciences acquired Pairnomix in October 2018, and Might remains a Scientific Advisor.

Water-soluble tocopherol derivatives inhibit SARS-CoV-2 RNA-dependent RNA polymerase.
Authors: Pacl HT, Tipper JL, Sevalkar RR, Crouse A, Crowder C, Ahmad S, Ahmad A, Holder GD, Kuhlman CJ, Chinta KC, Nadeem S, Green TJ, Petit CM, Steyn AJC, Might M, Harrod KS.
bioRxiv
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Hormonal intervention for the treatment of veterans with COVID-19 requiring hospitalization (HITCH): a multicenter, phase 2 randomized controlled trial of best supportive care vs best supportive care plus degarelix: study protocol for a randomized cont…
Authors: Nickols NG, Goetz MB, Graber CJ, Bhattacharya D, Soo Hoo G, Might M, Goldstein DB, Wang X, Ramoni R, Myrie K, Tran S, Ghayouri L, Tsai S, Geelhoed M, Makarov D, Becker DJ, Tsay JC, Diamond M, George A, Al-Ajam M, Belligund P, Montgomery RB, Mostaghel EA, Sulpizio C, Mi Z, Dematt E, Tadalan J, Norman LE, Briones D, Clise CE, Taylor ZW, Huminik JR, Biswas K, Rettig MB.
Trials
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An induced pluripotent stem cell line (NCATS-CL9075) from a patient carrying compound heterozygote mutations, p.R390P and p.L318P, in the NGLY1 gene.
Authors: Pradhan M, Farkhondeh A, Cheng YS, Xu M, Beers J, Zou J, Liu C, Might M, Rodems S, Baumgärtel K, Zheng W.
Stem Cell Res
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Genotype-phenotype correlations and novel molecular insights into the DHX30-associated neurodevelopmental disorders.
Authors: Mannucci I, Dang NDP, Huber H, Murry JB, Abramson J, Althoff T, Banka S, Baynam G, Bearden D, Beleza-Meireles A, Benke PJ, Berland S, Bierhals T, Bilan F, Bindoff LA, Braathen GJ, Busk ØL, Chenbhanich J, Denecke J, Escobar LF, Estes C, Fleischer J, Groepper D, Haaxma CA, Hempel M, Holler-Managan Y, Houge G, Jackson A, Kellogg L, Keren B, Kiraly-Borri C, Kraus C, Kubisch C, Le Guyader G, Ljungblad UW, Brenman LM, Martinez-Agosto JA, Might M, Miller DT, Minks KQ, Moghaddam B, Nava C, Nelson SF, Parant JM, Prescott T, Rajabi F, Randrianaivo H, Reiter SF, Schuurs-Hoeijmakers J, Shieh PB, Slavotinek A, Smithson S, Stegmann APA, Tomczak K, Tveten K, Wang J, Whitlock JH, Zweier C, McWalter K, Juusola J, Quintero-Rivera F, Fischer U, Yeo NC, Kreienkamp HJ, Lessel D.
Genome Med
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Rare disease patient matchmaking: development and outcomes of an internet case-finding strategy in the Undiagnosed Diseases Network.
Authors: LeBlanc K, Glanton E, Nagy A, Bater J, Berro T, McGuinness MA, Studwell C, Might M.
Orphanet J Rare Dis
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A state-based approach to genomics for rare disease and population screening.
Authors: East KM, Kelley WV, Cannon A, Cochran ME, Moss IP, May T, Nakano-Okuno M, Sodeke SO, Edberg JC, Cimino JJ, Fouad M, Curry WA, Hurst ACE, Bowling KM, Thompson ML, Bebin EM, Johnson RD, Cooper GM, Might M, Barsh GS, Korf BR.
Genet Med
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cdev: a ground-truth based measure to evaluate RNA-seq normalization performance.
Authors: Tran DT, Might M.
PeerJ
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The case for open science: rare diseases.
Authors: Rubinstein YR, Robinson PN, Gahl WA, Avillach P, Baynam G, Cederroth H, Goodwin RM, Groft SC, Hansson MG, Harris NL, Huser V, Mascalzoni D, McMurry JA, Might M, Nellaker C, Mons B, Paltoo DN, Pevsner J, Posada M, Rockett-Frase AP, Roos M, Rubinstein TB, Taruscio D, van Enckevort E, Haendel MA.
JAMIA Open
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METFORMIN USE IS ASSOCIATED WITH REDUCED MORTALITY IN A DIVERSE POPULATION WITH COVID-19 AND DIABETES.
Authors: Crouse A, Grimes T, Li P, Might M, Ovalle F, Shalev A.
medRxiv
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A graph-based algorithm for RNA-seq data normalization.
Authors: Tran DT, Bhaskara A, Kuberan B, Might M.
PLoS One
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