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Title: Russ B. Altman's Profile | Stanford Profiles
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Texto: Russ B. Altman's Profile | Stanford Profiles Stanford Profiles Browse Sign In Edit My Profile Russ B. Altman Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science and, by courtesy, of Computer Science Web page: https://rbaltman.people.stanford.edu Print Profile Email Profile View Stanford-only Profile Tab Menu Bio Research & Scholarship Teaching Publications Bio Russ Biagio Altman is a professor of bioengineering, genetics, medicine, and biomedical data science (and of computer science, by courtesy) and past chairman of the Bioengineering Department at Stanford University. His primary research interests are in the application of computing and informatics technologies to problems relevant to medicine. He is particularly interested in methods for understanding drug action at molecular, cellular, organism and population levels. His lab studies how human genetic variation impacts drug response (e.g., http://www.pharmgkb.org/). Other work focuses on the analysis of biological molecules to understand the actions, interactions and adverse events of drugs (e.g., http://feature.stanford.edu/). He helps lead an FDA-supported Center of Excellence in Regulatory Science & Innovation.Dr. Altman holds an AB from Harvard College, and an MD from Stanford Medical School, and a PhD in Medical Information Sciences from Stanford. He received the U.S. Presidential Early Career Award for Scientists and Engineers and a National Science Foundation CAREER Award. He is a fellow of the American College of Physicians (ACP), the American College of Medical Informatics (ACMI), the American Institute of Medical and Biological Engineering (AIMBE), and the American Association for the Advancement of Science (AAAS). He is a member of the National Academy of Medicine (formerly the Institute of Medicine, IOM). He is a past-president, founding board member, and a fellow of the International Society for Computational Biology (ISCB), and a past-president of the American Society for Clinical Pharmacology & Therapeutics (ASCPT). He has chaired the Science Board advising the FDA commissioner, currently serves on the NIH Director’s Advisory Committee, and is cochair of the IOM Drug Forum. He is an organizer of the annual Pacific Symposium on Biocomputing, and a founder of Personalis, Inc. Dr. Altman is board certified in Internal Medicine and in Clinical Informatics. He received the Stanford Medical School graduate teaching award in 2000 and mentorship award in 2014. Academic Appointments Professor, Bioengineering Professor, Genetics Professor, Medicine - Biomedical Informatics Research Professor, Biomedical Data Science Professor (By courtesy), Computer Science Member, Bio-X Member, Cardiovascular Institute Member, Maternal & Child Health Research Institute (MCHRI) Member, Stanford Cancer Institute Member, Wu Tsai Neurosciences Institute Administrative Appointments Faculty Director, SPADA (Stanford Predictives & Diagnostics Accelerator) (2016 - Present) Faculty Director, 100 Year Study of Artificial Intelligence (2015 - Present) Associate Director, Human-Centered Artificial Intelligence Institute (2018 - Present) Member, Biomedical Library and Informatics Research Commitee Study Section (NIH) (2002 - 2005) President, International Society for Computational Biology (2000 - 2001) President, American Society for Clinical Pharmacology and Therapeutics (2013 - 2014) Director, Biomedical Informatics Training Program (2000 - 2018) Chairman, Department of Bioengineering (2007 - 2012) Chair, FDA Science Board (2013 - 2014) Member, Advisory Committee to the Director (ACD), NIH (2013 - 2016) Honors & Awards Fellow, American Association for the Advancement of Science (2014) Stanford Medical School Mentorship Award, Stanford Medical School (2014) Fellow, International Society for Computational Biology (2010) Member, Institute of Medicine of the National Academies (2009) Fellow, American Institute for Medical and Biological Engineering (2007) Award for Excellence in Graduate Teaching, Stanford Medical School (2000) Fellow, American College of Medical Informatics (1998) Fellow, American College of Physicians (1998) U.S. Presidential Early Career Award for Scientists & Engineers, NIH (1997) Post-Doctoral Fellowship, Howard Hughes Medical Institute (1991) Boards, Advisory Committees, Professional Organizations Co-Founder, Personalis.com (2013 - Present) Editor-in-Chief, Annual Reviews of Biomedical Data Science (2016 - Present) Board of Directors, YouScript.com (2018 - Present) Advisor, Vanderbilt University Medical School (2014 - Present) Advisor, NIH Advisory Committee to the Director (ACD) (2013 - 2017) Member, FDA Commissioner Science Board (2011 - 2014) Co-Organizer, Pacific Symposium on Biocomputing (psb.stanford.edu) (1995 - Present) Program Affiliations Symbolic Systems Program Professional Education AB, Harvard College, Biochemistry & Molecular Biology (1983) PhD, Stanford University, Medical Information Sciences (1989) MD, Stanford University, Medicine (1990) Community and International Work Host, "The Future of Everything with Russ Altman" SiriusXM 121 Topic Science & Technology Interviews Partnering Organization(s) Stanford Communications, SiriusXM Populations Served General Public Location International Ongoing Project Yes Opportunities for Student Involvement No Physician, Pharmacogenomics Consult Service , Stanford Clinics, CA Topic Providing genetic advice about drug response Partnering Organization(s) Stanford Health Care Populations Served Local population Location International Ongoing Project Yes Opportunities for Student Involvement No Patents Nicholas Tatonetti, Russ B. Altman, Guy Haskin Fernald. "United States Patent 9305267 Signal detection algorithms to identify drug effects and drug interactions", The Board of Trustees of the Leland Stanford Junior University, Apr 5, 2016 Kathleen A. Thompson, Russ B. Altman, Oliver M. Duschka. "United States Patent 6178416 Method and apparatus for knowledgebase searching", Jan 23, 2001 Ramon M. Felciano, Russ B. Altman. "United States Patent 6052730 Method for monitoring and/or modifying web browsing sessions", The Board of Trustees of the Leland Stanford Junior University, Apr 18, 2000 Contact Academic Russ.Altman@stanford.edu University - Faculty Department:&nbspBioengineering Position: Professor Department of Bioengineering Shriram Center, 443 Via Ortega, Room 209 Altman Lab, MC: 4245 Stanford,  California  94305-4145  (650) 725-3394 (office) (650) 725-0659 (office) (650) 725-3863 (fax) Alternate Contact Tiffany Murray Administrative Associate tiffany.murray@stanford.edu 650-725-0659 (office) Additional Info Mail Code: 5444 Profile: The med school faculty profile page is: http://med.stanford.edu/profiles/Russ_Altman/ Links Curriculum Vitae PDF NIH Biosketch PDF Helix Group Website Personal home page Current Research and Scholarly Interests I am interested in the application of computational technologies to problems in molecular biology of relevance to medicine. In particular, my laboratory focuses on drug response at the molecular level, working in three areas. First, we are building a comprehensive pharmacogenomics knowledge base (http://www.pharmgkb.org/) that provides access to information relating genotype to phenotype (in particular, how variation in genetics leads to variation in response to drugs). We are interested in collaboratively discovering and applying new pharmacogenomics knowledge. Second, we are interested in the analysis of three dimensional biological structures. We have methods for analyzing protein structures to recognize and annotate active sites and binding sites, particularly in the context of interactions with small molecule drugs. We are also interested in physics-based simulation of biological structures to understand how their dynamics impact their function (http://simbios.stanford.edu/). Finally, we are interested in computational methods for analyzing functional genomics information. We use natural language processing techniques for extracting and summarizing information in the literature, chemoinformatics methods for understanding small molecule function, and machine learning & data mining techniques to understand the molecular responses to drugs. 2018-19 Courses Ethics in Bioengineering BIOE 131, ETHICSOC 131X (Spr) Frontiers in Reproductive Technology CS 17SI (Spr) Introduction to Biomedical Informatics Research Methodology BIOE 212, BIOMEDIN 212, CS 272, GENE 212 (Spr) Principles of Pharmacogenomics BIOMEDIN 224, GENE 224 (Aut, Win, Spr) Representations and Algorithms for Computational Molecular Biology BIOE 214, BIOMEDIN 214, CS 274, GENE 214 (Aut) Representations and Algorithms for Molecular Biology: Lectures BIOMEDIN 216 (Aut) Independent Studies (37) Advanced Reading and Research CS 499 (Aut, Win, Spr, Sum) Advanced Reading and Research CS 499P (Aut, Win, Spr, Sum) Bioengineering Problems and Experimental Investigation BIOE 191 (Aut, Win, Spr, Sum) Biomedical Informatics Teaching Methods BIOMEDIN 290 (Aut, Win, Spr, Sum) Computer Laboratory CS 393 (Aut, Win, Spr, Sum) Curricular Practical Training CS 390A (Aut, Win, Spr, Sum) Curricular Practical Training CS 390B (Aut, Win, Spr, Sum) Curricular Practical Training CS 390C (Aut, Win, Spr, Sum) Directed Investigation BIOE 392 (Aut, Win, Spr, Sum) Directed Reading and Research BIOMEDIN 299 (Aut, Win, Spr, Sum) Directed Reading in Biophysics BIOPHYS 399 (Aut, Win, Spr, Sum) Directed Reading in Genetics GENE 299 (Aut, Win, Spr, Sum) Directed Study BIOE 391 (Aut, Win, Spr, Sum) Graduate Research BIOPHYS 300 (Aut, Win, Spr, Sum) Graduate Research GENE 399 (Aut, Win, Spr, Sum) Graduate Research IMMUNOL 399 (Aut, Win, Spr, Sum) Independent Database Project CS 395 (Aut, Win, Spr, Sum) Independent Project CS 399 (Aut, Win, Spr, Sum) Independent Project CS 399P (Aut, Win, Spr, Sum) Independent Work CS 199 (Aut, Win, Spr, Sum) Independent Work CS 199P (Aut, Win, Spr, Sum) Medical Scholars Research BIOMEDIN 370 (Aut, Win, Spr, Sum) Medical Scholars Research GENE 370 (Aut, Win, Spr, Sum) Part-Time CPT CS 390S (Aut) Part-Time CPT CS 390T (Win) Part-Time Curricular Practical Training CS 390Q (Win, Spr) Part-Time Curricular Practical Training CS 390U (Spr) Part-time Curricular Practical Training CS 390D (Aut) Part-time Curricular Practical Training CS 390P (Win, Spr) Programming Service Project CS 192 (Aut, Win, Spr, Sum) Research PHYSICS 490 (Win, Spr) Senior Project CS 191 (Aut, Win, Spr, Sum) Special Studies in Engineering ENGR 199 (Win, Spr) Supervised Study GENE 260 (Aut, Win, Spr, Sum) Undergraduate Research GENE 199 (Aut, Win, Spr, Sum) Writing Intensive Senior Project (WIM) CS 191W (Aut, Win, Spr) Writing of Original Research for Engineers ENGR 199W (Aut, Win, Spr) Prior Year Courses 2017-18 Courses Ethics in Bioengineering BIOE 131, ETHICSOC 131X (Spr) Introduction to Biomedical Informatics Research Methodology BIOE 212, BIOMEDIN 212, CS 272, GENE 212 (Spr) Principles of Pharmacogenomics BIOMEDIN 224, GENE 224 (Aut, Win, Spr, Sum) Representations and Algorithms for Computational Molecular Biology BIOE 214, BIOMEDIN 214, CS 274, GENE 214 (Aut) Representations and Algorithms for Molecular Biology: Lectures BIOMEDIN 216 (Aut) 2016-17 Courses Ethics in Bioengineering BIOE 131 (Spr) Introduction to Biomedical Informatics Research Methodology BIOE 212, BIOMEDIN 212, CS 272, GENE 212 (Spr) Principles of Pharmacogenomics BIOMEDIN 224, GENE 224 (Aut, Win, Spr, Sum) Representations and Algorithms for Computational Molecular Biology BIOE 214, BIOMEDIN 214, CS 274, GENE 214 (Aut) Representations and Algorithms for Molecular Biology: Lectures BIOMEDIN 216 (Aut) 2015-16 Courses Ethics in Bioengineering BIOE 131 (Spr) Introduction to Biomedical Informatics Research Methodology BIOE 212, BIOMEDIN 212, CS 272, GENE 212 (Spr) Principles of Pharmacogenomics BIOMEDIN 224 (Win, Spr, Sum) Representations and Algorithms for Computational Molecular Biology BIOE 214, BIOMEDIN 214, CS 274, GENE 214 (Aut) Representations and Algorithms for Molecular Biology: Lectures BIOMEDIN 216 (Aut) Stanford Advisees Doctoral Dissertation Reader (AC) Ragini Phansalkar , Kevin Raines Postdoctoral Faculty Sponsor Jake Lever , Ben Lo , Sheng Wang Doctoral Dissertation Advisor (AC) Lichy Han , Adam Lavertu Master's Program Advisor Clara McCreery , Abraham Starosta Undergraduate Major Advisor Marilu Bravo , Paulina Chamely Doctoral (Program) Diego Calderon , Stephanie Schmidt , Erica Schwarz , Artem Trotsyuk Postdoctoral Research Mentor Ben Lo Graduate and Fellowship Programs Bioengineering (Phd Program) Biomedical Informatics (Masters Program) Biomedical Informatics (Phd Program) Biophysics (Phd Program) Genetics (Phd Program) All Publications A research roadmap for next-generation sequencing informatics SCIENCE TRANSLATIONAL MEDICINE Altman, R. B., Prabhu, S., Sidow, A., Zook, J. M., Goldfeder, R., Litwack, D., Ashley, E., Asimenos, G., Bustamante, C. D., Donigan, K., Giacomini, K. M., Johansen, E., Khuri, N., Lee, E., Liang, X. S., Salit, M., Serang, O., Tezak, Z., Wall, D. P., Mansfield, E., Kass-Hout, T. 2016 ; 8 (335) Abstract Next-generation sequencing technologies are fueling a wave of new diagnostic tests. Progress on a key set of nine research challenge areas will help generate the knowledge required to advance effectively these diagnostics to the clinic. View details for DOI 10.1126/scitranslmed.aaf7314 View details for Web of Science ID 000374412300003 View details for PubMedID 27099173 Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach. Journal of chemical information and modeling Liu, T., Altman, R. B. 2015 ; 55 (7) : 1483-1494 Abstract The molecular mechanism of many drug side-effects is unknown and difficult to predict. Previous methods for explaining side-effects have focused on known drug targets and their pathways. However, low affinity binding to proteins that are not usually considered drug targets may also drive side-effects. In order to assess these alternative targets, we used the 3D structures of 563 essential human proteins systematically to predict binding to 216 drugs. We first benchmarked our affinity predictions with available experimental data. We then combined singular value decomposition and canonical component analysis (SVD-CCA) to predict side-effects based on these novel target profiles. Our method predicts side-effects with good accuracy (average AUC: 0.82 for side effects present in


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150 https://dx.doi.org/10.3389/fphar.2018.01093
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155 https://dx.doi.org/10.1097/FPC.0000000000000347
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157 www.ncbi.nlm.nih.gov/pubmed/30134346



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