Positions
- Cullen Chair and Professor
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Molecular and Human Genetics
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- Professor
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Biochemistry & Molecular Biology
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- Professor
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Pharmacology
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- Cullen Foundation Chair and Director
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Computational and Integrative Biomedical Research Center
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- Co-Director
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Program in Structural & Computational Biology and Molecular Biophysics
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- Member
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Dan L Duncan Comprehensive Cancer Center
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Houston, Texas, United States
Education
- BS from McGill University
- 01/1980 - Montreal, Quebec, Canada
- PhD from Stanford University
- 01/1987 - Stanford, California, United States
- MD from Stanford University School Of Medicine
- 01/1990 - Stanford, California, United States
- Residency at University Of California, San Francisco Affiliate Hospitals
- 01/1993 - San Francisco, California, United States
- Internal Medicine
- Fellowship at University Of California, San Francisco Affiliate Hospitals
- 01/1996 - San Francisco, CA, United States
- Endocrinology
- Post-Doctoral Fellowship at University Of California, San Francisco
- 01/1997 - San Francisco, California, United States
Honors & Awards
- Fellow, American Association for the Advancement of Science
- (11/2019)
- Michael E. DeBakey Excellence in Research Award
- (07/2015)
- Raymond and Beverley Sackler Fellowship, IHES
- France (01/2005)
- Basil O’Connor Award, March of Dimes
- (01/2001)
- American Heart Association Faculty Development Award
- (01/1999)
- American Heart Association Postdoctoral Fellowship
- (01/1997)
- Dorothy Penrose Stout Fellowship Award, American Heart Association
- California Affiliate (01/1995)
Professional Interests
- Cognitive computing towards multi-scale data integration and rational design of multi-drug therapies.
Professional Statement
Our lab marries computation with experiments to understand the molecular evolution of genes and pathways—how their functions may become corrupted by genetic mistakes or how they may be re-engineered to new designs. Technically, we draw upon a wide range of disciplines to address fundamental questions in structural biology, clinical genomics and precision medicine. Over the long-term, we hope to discover new therapeutic paths and improve screening and early detection to preserve health and also to harness the synthetic potential of organisms for biotechnology. In the short-term we seek to interpret the mutational action of human genome variations and pinpoint the genes that drive complex diseases.
Starting from structural bioinformatics, our algorithms broadly merge mathematical and evolutionary principles. They enable multi-scale data integration and, in favorable conditions, precise control of molecular functions. This has led to discoveries across diverse systems, including G protein signaling, malaria, cancer and neurological disorders. Newer interests include network theory, text-mining and cognitive computing. Specific examples include a network compression scheme that made tractable the diffusion of information across nearly 400 species. This approach uncovered a possible mechanism for the best drug against malaria. Other network studies, reasoned over the entire PubMed literature to discover new kinases and protein interactions for p53.
A recent promising line of research quantifies the evolutionary action (EA) of mutations on fitness to make a bridge between molecular biology and population genetics. EA correlates with experimental loss of function in proteins; with morbidity and mortality in people; and with purifying gene selection in populations. In head and neck cancer patients, EA stratifies outcomes and suggests alternate therapy for some patients. In autism, the mutational EA burden correlated with the depth of cognitive harm (IQ). In the future, we hope to unite these different approaches into a coherent path to compute precision therapy and personalized risk based on each patient’s unique profile of genome variations.
Starting from structural bioinformatics, our algorithms broadly merge mathematical and evolutionary principles. They enable multi-scale data integration and, in favorable conditions, precise control of molecular functions. This has led to discoveries across diverse systems, including G protein signaling, malaria, cancer and neurological disorders. Newer interests include network theory, text-mining and cognitive computing. Specific examples include a network compression scheme that made tractable the diffusion of information across nearly 400 species. This approach uncovered a possible mechanism for the best drug against malaria. Other network studies, reasoned over the entire PubMed literature to discover new kinases and protein interactions for p53.
A recent promising line of research quantifies the evolutionary action (EA) of mutations on fitness to make a bridge between molecular biology and population genetics. EA correlates with experimental loss of function in proteins; with morbidity and mortality in people; and with purifying gene selection in populations. In head and neck cancer patients, EA stratifies outcomes and suggests alternate therapy for some patients. In autism, the mutational EA burden correlated with the depth of cognitive harm (IQ). In the future, we hope to unite these different approaches into a coherent path to compute precision therapy and personalized risk based on each patient’s unique profile of genome variations.
Selected Publications
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Koire A, Katsonis P, Kim YW, Buchovecky C, Wilson SJ, Lichtarge O. " A method to delineate de novo missense variants across pathways prioritizes genes linked to autism.. " Sci Transl Med.. 2021 ; 13 : eabc1739.
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Kim YW, Al-Ramahi I, Koire A, Wilson SJ, Konecki DM, Mota S, Soleimani S, Botas J, Lichtarge O. " Harnessing the paradoxical phenotypes of APOE ɛ2 and APOE ɛ4 to identify genetic modifiers in Alzheimer’s disease.. " Alzheimers Dement.. 2021 ; 17 : 831-846.
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Choi BK, Dayaram T, Parikh N, Wilkins A, Nagarajan M, Novikov I, (…), Lichtarge O. " Literature-Based Automated Discovery of Tumor Suppressor p53 Phosphorylation and Inhibition by NEK2. " PNAS. 2021 ; 115 : 10666-10671.
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Cancer Genome Atlas Research Network. " Comprehensive and Integrative Genomics Characterization of Hepatocellular Carcinoma.. " Cell. 2017 ; 169 : 1327-41.
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