Assaf Gottlieb, Ph.D., joined the UTHealth School of Biomedical Informatics (SBMI) in January 2017 as an assistant professor and one of the core faculty members of the Center for Precision Health.

Dr. Gottlieb arrived to SBMI from IBM Research where he served as a research associate at the Machine Learning for Healthcare and Life Science group in Haifa labs. Prior to his position with IBM, Dr. Gottlieb was a postdoctoral fellow at both Stanford University and Tel-Aviv University. He has degrees in Physics and Computer Science and has also worked in software and algorithmic development in various software companies.

Dr. Gottlieb’s lab employs an integrative computational approach, combining multiple types of data and applying methodologies from systems medicine, machine learning and causal inference domains. We have long time expertise in employing, and developing, supervised and unsupervised machine learning algorithms for very diverse types of data, including various types of biological data and clinical data from electronic health records and claims data. Our primary interest is to learn how to integrate all these types of data for better health outcomes, be it early predictions of diseases like Alzheimer’s Disease, HIV risk or treatment outcomes, such as in cancer therapy.

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Cancer pharmacogenomics	HIV Risk prediction	Alzheimer's Disease	Opioid use disorder	Multiple Sclerosis

Data Sources

Genotypes	Transcriptomics	Fitness trackers	Electronic Health Records

Education

• PhD, Computational Biology, 2010, Tel Aviv University
• MSc, Physics, 2001, Tel Aviv University
• BSc, Physics and Computer Science, 1998, Tel Aviv University

Areas of Expertise

• Pharmacogenomics
• Machine Learning
• Systems Biology/Medicine
• Causal inference from observational data

Selected Publications

You can find the full set of publications in NCBI Bibliography or Google Scholar in the top right corner. Below is a selected set from recent years.

1. Dai Y, Jia P, Zhao Z, Gottlieb A. A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease. Cells. 2022 Jan;11(14):2219.
2. Lu H, Tang YC, Gottlieb A. Tissue-Specific Variations in Transcription Factors Elucidate Complex Immune System Regulation. Genes. 2022 May;13(5):929.
3. Gottlieb A, Pham HP, Lindsey JW. Brain antigens stimulate proliferation of T lymphocytes with a pathogenic phenotype in multiple sclerosis patients. Frontiers in immunology. 2022;13.
4. Gottlieb A, Bakos-Block C, Langabeer JR, Champagne-Langabeer T. Sociodemographic and Clinical Characteristics Associated with Improvements in Quality of Life for Participants with Opioid Use Disorder. Healthcare 2022 Jan 16 (Vol. 10, No. 1, p. 167).
5. Gottlieb A, Yatsco A, Bakos-Block C, Langabeer JR, Champagne-Langabeer T. Machine Learning for Predicting Risk of Early Dropout in a Recovery Program for Opioid Use Disorder. Healthcare 2022 Jan 25 (Vol. 10, No. 2, p. 223).
6. Gottlieb A, Toledano-Furman N, Prabhakara KS, Kumar A, Caplan HW, Bedi S, Cox CS, Olson SD. Time dependent analysis of rat microglial surface markers in traumatic brain injury reveals dynamics of distinct cell subpopulations. Scientific reports. 2022 Apr 15;12(1):1-0.
7. Tang YC, Gottlieb A. SynPathy: Predicting Drug Synergy through Drug-Associated Pathways Using Deep Learning. Molecular Cancer Research. 2022 May 4;20(5):762-9.
8. May SB, Giordano TP, Gottlieb A. A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study. JMIR Formative Research. 2021 Nov 25;5(11):e28620.
9. Huang T, Chu Y, Shams S, Kim Y, V Annapragada A, Subramanian D, Kakadiaris I, Gottlieb A, Jiang X. Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates. J Biomed Inform. 2021 May 19;:103818
10. Tang YC, Gottlieb A. Explainable drug sensitivity prediction through cancer pathway enrichment. Sci Rep. 2021 Feb 4;11(1):3128
11. Chandran A, Rashtak S, Patil P, Gottlieb A, Bernstam E, Guha S, Ramireddy S, Badillo R, DaVee RT, Kao LS, Thosani N. Comparing diagnostic accuracy of current practice guidelines in predicting choledocholithiasis: outcomes from a large healthcare system comprising both academic and community settings. Gastrointest Endosc. 2020 Nov 5
12. Raisaro JL, Marino F, Troncoso-Pastoriza J, Beau-Lejdstrom R, Bellazzi R, Murphy R, Bernstam EV, Wang H, Bucalo M, Chen Y, Gottlieb A, Harmanci A, Kim M, Kim Y, Klann J, Klersy C, Malin BA, Méan M, Prasser F, Scudeller L, Torkamani A, Vaucher J, Puppala M, Wong STC, Frenkel-Morgenstern M, Xu H, Musa BM, Habib AG, Cohen T, Wilcox A, Salihu HM, Sofia H, Jiang X, Hubaux JP. SCOR: A secure international informatics infrastructure to investigate COVID-19. J Am Med Inform Assoc. 2020 Nov 1;27(11):1721-1726.
13. Furman NT, Gottlieb A, Prabhakara KS, Bedi S, Caplan HW, Ruppert KA, et al. High-resolution and differential analysis of rat microglial markers in traumatic brain injury: conventional flow cytometric and bioinformatics analysis. Scientific Reports. 2020;10(1):1-14.
14. Sequeira A, Shen K, Gottlieb A, Limon A. Human brain transcriptome analysis finds region-and subject-specific expression signatures of GABA AR subunits. Communications biology. 2019;2(1):153.
15. Malec S, Gottlieb A, Bernstam E, Cohen T. Using the Literature to Construct Causal Models for Pharmacovigilance. EasyChair; 2018. Report No.: 2516-2314. W07: Data Mining for Medical Informatics (DMMI) – Causal Inference for Health Data Analytics
16. Ozery-Flato M, Yanover C, Gottlieb A, Weissbrod O, Parush Shear-Yashuv N, Goldschmidt Y. Fast and efficient feature engineering for multi-cohort analysis of EHR data. Stud Health Technol Inform. 2017;235:181-5.
17. Leung TI, Goldstein MK, Musen MA, Cronkite R, Chen JH, Gottlieb A, et al. The New HIT: Human Health Information Technology. Studies in health technology and informatics. 2017;245:768-72.
18. Gottlieb A, Yanover C, Cahan A, Goldschmidt Y. Estimating the effects of second-line therapy for type 2 diabetes mellitus: retrospective cohort study. BMJ Open Diabetes Research and Care. 2017;5(1):e000435.
19. Gottlieb A, Daneshjou R, DeGorter M, Bourgeois S, Svensson PJ, Wadelius M, et al. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans. Genome medicine. 2017;9(1):98.
20. Gottlieb A, Hoehndorf R, Dumontier M, Altman RB. Ranking adverse drug reactions with crowdsourcing. Journal of medical Internet research. 2015;17(3):e80.
21. Durruthy-Durruthy R*, Gottlieb A*, Heller S. 3D computational reconstruction of tissues with hollow spherical morphologies using single-cell gene expression data. Nature protocols. 2015;10(3):459. * equal contribution
22. Gottlieb A, Altman RB. Integrating systems biology sources illuminates drug action. Clinical Pharmacology & Therapeutics. 2014;95(6):663-9.
23. Durruthy-Durruthy R, Gottlieb A, Hartman BH, Waldhaus J, Laske RD, Altman R, et al. Reconstruction of the mouse otocyst and early neuroblast lineage at single-cell resolution. Cell. 2014;157(4):964-78.