Erich Senin Huang
Assistant Professor in Biostatistics & Bioinformatics
Chief Data Officer for Quality, Duke Health
Director of Duke Forge
Director of Duke Crucible
Assistant Dean for Biomedical Informatics
Dr. Huang’s research interests span applied machine learning, research provenance and data infrastructure. Projects include building data provenance tools funded by the NIH’s Big Data to Knowledge program, regulatory science funded by the Burroughs Wellcome Foundation. Applied machine learning applications include “Deep Care Management” a highly interdisciplinary project with Duke Connected Care, Duke’s Accountable Care Organization, that integrates claims and EHR data for predicting unplanned admissions and risk stratifying patients for case management; CALYPSO, a collaboration with the Department of Surgery for utilizing machine learning to predict surgical complications. My team is also building the data platform for the Department of Surgery's "1000 Patients Project" an intensive biospecimen and biomarker study based around patients undergoing the controlled injury of surgery.
As Director of Duke Forge, Dr. Huang is working to build a data science culture and infrastructure across Duke University that focuses on actionable health data science. The Forge emphasizes scientific rigor, awareness that technology does not supersede clinicians’ responsibilities and human relationship with their patients, and the role of data science in society.
Current Appointments & Affiliations
- Assistant Professor in Biostatistics & Bioinformatics, Biostatistics & Bioinformatics, Basic Science Departments 2021
- Assistant Dean, Biomedical Informatics, Biostatistics & Bioinformatics, Basic Science Departments 2016
- Co-Director, Duke Forge, Biostatistics & Bioinformatics, Basic Science Departments 2017
- Assistant Professor in Surgery, Surgery, Clinical Science Departments 2020
Contact Information
- 2424 Erwin Road, 9022 Hock Plaza, Durham, NC 27705
- Duke Box 2721, Durham, NC 27710
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erich.huang@duke.edu
(919) 668-2814
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ORCID profile
- Background
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Education, Training, & Certifications
- M.D., Duke University 2003
- Ph.D., Duke University 2002
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Previous Appointments & Affiliations
- Core Faculty in Innovation & Entrepreneurship, Duke Innovation & Entrepreneurship, Initiatives 2018 - 2021
- Assistant Professor in Biostatistics & Bioinformatics, Biostatistics & Bioinformatics, Basic Science Departments 2014 - 2020
- Assistant Professor in Surgery, Surgery, Clinical Science Departments 2014 - 2020
- Adjunct Assistant Professor in the Department of Surgery, Surgical Oncology, Surgery 2012 - 2013
- Assistant Professor of Surgery, Surgical Oncology, Surgery 2011 - 2012
- Assistant Professor of Surgery, Surgery, Clinical Science Departments 2008 - 2010
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Leadership & Clinical Positions at Duke
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Chief Data Officer for Quality, Duke Health
Director of Duke Forge, Duke University School of Medicine
Director of Duke Crucible, Duke University School of Medicine
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Chief Data Officer for Quality, Duke Health
- Recognition
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In the News
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MAY 14, 2020 MIT Tech Review -
MAY 7, 2020 MIT Tech Review -
MAR 12, 2020 StatNews -
SEP 28, 2018 -
NOV 9, 2017 Duke Research Blog -
MAR 8, 2016 Duke Translational Medicine Institute / DukeCTSA
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Awards & Honors
- Expertise
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Global Scholarship
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Research
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- Research
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Selected Grants
- Clinical and Mechanistic Factors Impacting Transplant Outcomes (U01) awarded by National Institutes of Health 2022 - 2027
- Medical Scientist Training Program awarded by National Institutes of Health 2022 - 2027
- mHealth Tympanometer: A Digital Innovation to Address Childhood Hearing Loss in Low- and Middle-Income Countries awarded by National Institutes of Health 2021 - 2023
- Postdoctoral Training in Genomic Medicine Research awarded by National Institutes of Health 2017 - 2023
- Bridging the Gap to Enhance Clinical Research Program (BIGGER) awarded by National Institutes of Health 2016 - 2022
- Duke RDS2 (Respondent-Driven Sampling, Respiratory Disease Surveillance) the SNOWBALL Sampling Study awarded by Centers for Disease Control and Prevention 2020 - 2022
- Medical Scientist Training Program awarded by National Institutes of Health 1997 - 2022
- NSF Convergence Accelerator Track D: A Trusted Integrative Model and Data Sharing Platform for Accelerating AI-Driven Health Innovation awarded by National Science Foundation 2020 - 2022
- Understanding Bias in AI-enabled Health Care Products awarded by Pew Charitable Trusts 2021 - 2022
- Infrastructure for Research Provenance & Reproducibility to Support Auditable Regulatory Scientic Workflows awarded by Burroughs Wellcome Fund 2015 - 2021
- Flexible & Executable Provenance in Data-Intensive Biomedical Research: A Flexible Research Data Service awarded by National Institutes of Health 2015 - 2020
- SC2i awarded by Henry M. Jackson Foundation 2014 - 2020
- Prototype Development of CANARIUS - a Flexible, Dynamic, Scaleable, and Low-cost Platform for Surveiling Population Health awarded by North Carolina Biotechnology Center 2019 - 2020
- A Dialog about AI Safety and Transparency in Health Care awarded by Gordon & Betty Moore Foundation 2018 - 2020
- Machine Learning Platform for Surgical Risk Prediction and Modification awarded by kelaHealth, Inc 2017 - 2018
- Duke/NIDDK Functional Genomics Center awarded by National Institutes of Health 2000 - 2003
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External Relationships
- Clinetic (formerly MedBlue Data)
- Stratus Medicine
- Valo Health
- Verily LIfe Sciences
- kelaHealth
- Publications & Artistic Works
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Selected Publications
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Academic Articles
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Huang, Jingtong, Andrea M. Yeung, Leslie A. Eiland, Erich S. Huang, Jennifer K. Raymond, and David C. Klonoff. “Telehealth Fatigue: Is It Real? What Should Be Done?” J Diabetes Sci Technol, October 7, 2022, 19322968221127252. https://doi.org/10.1177/19322968221127253.Full Text Link to Item
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Eckhoff, Austin M., Ashton A. Connor, Julie K. M. Thacker, Dan G. Blazer, Harvey G. Moore, Randall P. Scheri, Sandhya A. Lagoo-Deenadayalan, et al. “A Multidimensional Bioinformatic Platform for the Study of Human Response to Surgery.” Ann Surg 275, no. 6 (June 1, 2022): 1094–1102. https://doi.org/10.1097/SLA.0000000000005429.Full Text Link to Item
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Huang, Erich S. “The User Experience of AI.” Med (N Y) 3, no. 4 (April 8, 2022): 228–32. https://doi.org/10.1016/j.medj.2022.03.005.Full Text Link to Item
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Firouzi, Farshad, Bahar Farahani, Mahmoud Daneshmand, Kathy Grise, Jaeseung Song, Roberto Saracco, Lucy Lu Wang, et al. “Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World.” Ieee Internet Things J 8, no. 16 (August 15, 2021): 12826–46. https://doi.org/10.1109/JIOT.2021.3073904.Full Text Link to Item
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Chang, Bora, Zhifei Sun, Prabath Peiris, Erich S. Huang, Ehsan Benrashid, and Ellen D. Dillavou. “Deep Learning-Based Risk Model for Best Management of Closed Groin Incisions After Vascular Surgery.” J Surg Res 254 (October 2020): 408–16. https://doi.org/10.1016/j.jss.2020.02.012.Full Text Link to Item
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Woody, Stephen K., David Burdick, Hilmar Lapp, and Erich S. Huang. “Publisher Correction: Application programming interfaces for knowledge transfer and generation in the life sciences and healthcare.” Npj Digit Med 3, no. 1 (April 9, 2020): 56. https://doi.org/10.1038/s41746-020-0271-1.Full Text Link to Item
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Arges, Kristine, Themistocles Assimes, Vikram Bajaj, Suresh Balu, Mustafa R. Bashir, Laura Beskow, Rosalia Blanco, et al. “The Project Baseline Health Study: a step towards a broader mission to map human health.” Npj Digit Med 3 (2020): 84. https://doi.org/10.1038/s41746-020-0290-y.Full Text Open Access Copy Link to Item
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Woody, Stephen K., David Burdick, Hilmar Lapp, and Erich S. Huang. “Application programming interfaces for knowledge transfer and generation in the life sciences and healthcare.” Npj Digit Med 3 (2020): 24. https://doi.org/10.1038/s41746-020-0235-5.Full Text Open Access Copy Link to Item
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Woody, Stephen K., David Burdick, Hilmar Lapp, and Erich S. Huang. “Erratum: Publisher Correction: Application programming interfaces for knowledge transfer and generation in the life sciences and healthcare.” Npj Digit Med 3 (2020): 56. https://doi.org/10.1038/s41746-020-0271-1.Full Text Open Access Copy Link to Item
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Cobb, Adrienne N., Andrew J. Benjamin, Erich S. Huang, and Paul C. Kuo. “Big data: More than big data sets.” Surgery 164, no. 4 (October 2018): 640–42. https://doi.org/10.1016/j.surg.2018.06.022.Full Text Link to Item
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Poore, Gregory D., Emily R. Ko, Ashlee Valente, Ricardo Henao, Kelsey Sumner, Christopher Hong, Thomas W. Burke, et al. “A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies.” Front Microbiol 9 (2018): 2957. https://doi.org/10.3389/fmicb.2018.02957.Full Text Open Access Copy Link to Item
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Cheng, Skye H., Chen-Fang Horng, Tzu-Ting Huang, Erich S. Huang, Mei-Hua Tsou, Li-Sun Shi, Ben-Long Yu, Chii-Ming Chen, and Andrew T. Huang. “An Eighteen-Gene Classifier Predicts Locoregional Recurrence in Post-Mastectomy Breast Cancer Patients.” Ebiomedicine 5 (March 2016): 74–81. https://doi.org/10.1016/j.ebiom.2016.02.022.Full Text Link to Item
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Wangaryattawanich, Pattana, Masumeh Hatami, Jixin Wang, Ginu Thomas, Adam Flanders, Justin Kirby, Max Wintermark, et al. “Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival.” Neuro Oncol 17, no. 11 (November 2015): 1525–37. https://doi.org/10.1093/neuonc/nov117.Full Text Link to Item
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Guinney, Justin, Charles Ferté, Jonathan Dry, Robert McEwen, Gilles Manceau, K. J. Kao, Kai-Ming Chang, et al. “Modeling RAS phenotype in colorectal cancer uncovers novel molecular traits of RAS dependency and improves prediction of response to targeted agents in patients.” Clin Cancer Res 20, no. 1 (January 1, 2014): 265–72. https://doi.org/10.1158/1078-0432.CCR-13-1943.Full Text Link to Item
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Ferté, Charles, Andrew D. Trister, Erich Huang, Brian M. Bot, Justin Guinney, Frederic Commo, Solveig Sieberts, et al. “Impact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology.” Clin Cancer Res 19, no. 16 (August 15, 2013): 4315–25. https://doi.org/10.1158/1078-0432.CCR-12-3937.Full Text Link to Item
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Gutman, David A., Lee A. D. Cooper, Scott N. Hwang, Chad A. Holder, Jingjing Gao, Tarun D. Aurora, William D. Dunn, et al. “MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set.” Radiology 267, no. 2 (May 2013): 560–69. https://doi.org/10.1148/radiol.13120118.Full Text Link to Item
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Margolin, Adam A., Erhan Bilal, Erich Huang, Thea C. Norman, Lars Ottestad, Brigham H. Mecham, Ben Sauerwine, et al. “Systematic analysis of challenge-driven improvements in molecular prognostic models for breast cancer.” Sci Transl Med 5, no. 181 (April 17, 2013): 181re1. https://doi.org/10.1126/scitranslmed.3006112.Full Text Link to Item
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Guinney, Justin, Charles Ferte, Erich Huang, Jonathan Derry, and Stephen Friend. “Abstract 2409: A model of RAS pathway in colorectal cancer elucidates molecular traits and drug sensitivity: an integrated analysis of gene expression from human tumors, mouse xenografts and the Cancer Cell Line Encyclopedia (CCLE).” Cancer Research 73, no. 8_Supplement (April 15, 2013): 2409–2409. https://doi.org/10.1158/1538-7445.am2013-2409.Full Text
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Trister, A. D., and E. S. Huang. “A network-heuristic approach to improve the impact of genomic data on drug discovery.” Clin Pharmacol Ther 93, no. 4 (April 2013): 295–97. https://doi.org/10.1038/clpt.2012.246.Full Text Link to Item
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LaBreche, Heather G., Joseph R. Nevins, and Erich Huang. “Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.” Bmc Med Genomics 4 (July 22, 2011): 61. https://doi.org/10.1186/1755-8794-4-61.Full Text Link to Item
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Huang, E. S., and A. T. Huang. “Genomics in the Diagnosis and Management of Breast Cancer,” December 1, 2010, 446–56. https://doi.org/10.1016/B978-0-12-374934-5.00035-0.Full Text
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Huang, E. S., and A. T. Huang. “Breast Cancer and Genomic Medicine,” December 1, 2009, 869–78. https://doi.org/10.1016/B978-0-12-369420-1.00072-X.Full Text
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Cheng, Skye H., Cheng-Fang Horng, Mike West, Erich Huang, Jennifer Pittman, Mei-Hua Tsou, Holly Dressman, et al. “Genomic prediction of locoregional recurrence after mastectomy in breast cancer.” J Clin Oncol 24, no. 28 (October 1, 2006): 4594–4602. https://doi.org/10.1200/JCO.2005.02.5676.Full Text Link to Item
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Pittman, Jennifer, Erich Huang, Joseph Nevins, Quanli Wang, and Mike West. “Bayesian analysis of binary prediction tree models for retrospectively sampled outcomes.” Biostatistics 5, no. 4 (October 2004): 587–601. https://doi.org/10.1093/biostatistics/kxh011.Full Text Link to Item
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Huang, Erich S., Joseph R. Nevins, Mike West, and Paul C. Kuo. “An overview of genomic data analysis.” Surgery 136, no. 3 (September 2004): 497–99. https://doi.org/10.1016/j.surg.2004.05.037.Full Text Link to Item
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Pittman, Jennifer, Erich Huang, Holly Dressman, Cheng-Fang Horng, Skye H. Cheng, Mei-Hua Tsou, Chii-Ming Chen, et al. “Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes.” Proc Natl Acad Sci U S A 101, no. 22 (June 1, 2004): 8431–36. https://doi.org/10.1073/pnas.0401736101.Full Text Link to Item
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Nevins, Joseph R., Erich S. Huang, Holly Dressman, Jennifer Pittman, Andrew T. Huang, and Mike West. “Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction.” Hum Mol Genet 12 Spec No 2 (October 15, 2003): R153–57. https://doi.org/10.1093/hmg/ddg287.Full Text Link to Item
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Huang, E., S. Ishida, J. Pittmann, H. Dressman, A. Bild, M. Kloos, M. D’Amico, R. G. Pestell, M. West, and J. R. Nevins. “Erratum: Gene expression phenotypic models that predict the activity of oncogenic pathways (Nature Genetics (2003) 34 (226-230)).” Nature Genetics 34, no. 4 (August 1, 2003): 465. https://doi.org/10.1038/ng0803-465.Full Text
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Black, Esther P., Erich Huang, Holly Dressman, Rachel Rempel, Nina Laakso, Sylvia L. Asa, Seiichi Ishida, Mike West, and Joseph R. Nevins. “Distinct gene expression phenotypes of cells lacking Rb and Rb family members.” Cancer Res 63, no. 13 (July 1, 2003): 3716–23.Link to Item
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Huang, Erich, Seiichi Ishida, Jennifer Pittman, Holly Dressman, Andrea Bild, Mark Kloos, Mark D’Amico, Richard G. Pestell, Mike West, and Joseph R. Nevins. “Gene expression phenotypic models that predict the activity of oncogenic pathways.” Nat Genet 34, no. 2 (June 2003): 226–30. https://doi.org/10.1038/ng1167.Full Text Link to Item
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Huang, Erich, Skye H. Cheng, Holly Dressman, Jennifer Pittman, Mei Hua Tsou, Cheng Fang Horng, Andrea Bild, et al. “Gene expression predictors of breast cancer outcomes.” Lancet 361, no. 9369 (May 10, 2003): 1590–96. https://doi.org/10.1016/S0140-6736(03)13308-9.Full Text Link to Item
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Huang, Erich S., Esther P. Black, Holly Dressman, Mike West, and Joseph R. Nevins. “Gene expression phenotypes of oncogenic signaling pathways.” Cell Cycle 2, no. 5 (2003): 415–17.Link to Item
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Huang, Erich, Mike West, and Joseph R. Nevins. “Gene expression profiling for prediction of clinical characteristics of breast cancer.” Recent Prog Horm Res 58 (2003): 55–73. https://doi.org/10.1210/rp.58.1.55.Full Text Link to Item
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West, M., C. Blanchette, H. Dressman, E. Huang, S. Ishida, R. Spang, H. Zuzan, J. A. Olson, J. R. Marks, and J. R. Nevins. “Predicting the clinical status of human breast cancer by using gene expression profiles.” Proc Natl Acad Sci U S A 98, no. 20 (September 25, 2001): 11462–67. https://doi.org/10.1073/pnas.201162998.Full Text Link to Item
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Ishida, S., E. Huang, H. Zuzan, R. Spang, G. Leone, M. West, and J. R. Nevins. “Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis.” Mol Cell Biol 21, no. 14 (July 2001): 4684–99. https://doi.org/10.1128/MCB.21.14.4684-4699.2001.Full Text Link to Item
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Leone, G., R. Sears, E. Huang, R. Rempel, F. Nuckolls, C. H. Park, P. Giangrande, et al. “Myc requires distinct E2F activities to induce S phase and apoptosis.” Mol Cell 8, no. 1 (July 2001): 105–13. https://doi.org/10.1016/s1097-2765(01)00275-1.Full Text Link to Item
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Book Sections
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Huang, E. S., and A. T. Huang. “Breast Cancer and Genomic Medicine.” In Genomic and Personalized Medicine: V1-2, 869–78, 2008. https://doi.org/10.1016/B978-0-12-369420-1.00072-X.Full Text
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Conference Papers
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Moore, Carrie C., Oliver Jawitz, Mary B. Aschenbrenner, Carlos Ramirez, Matthew Small, Robert Overton, Tony Leiro, et al. “Large-scale Database Integration and Analytical Evaluation of Medical Data: Building a Clinical Repository for Extracorporeal Membrane Oxygenation Therapy in Critically Ill Patients.” In Amia. AMIA, 2019.
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Ferte, Charles, Justin Guinney, Jonathan Derry, erich H. huang, Benjamin Besse, and Jean-Charles Soria. “Abstract 1199: NSCLC KRAS G12C and G12V mutations drive different pathways and display specific drug sensitivity patterns.” In Cancer Research, 73:1199–1199. American Association for Cancer Research (AACR), 2013. https://doi.org/10.1158/1538-7445.am2013-1199.Full Text
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Trister, Andrew Daniel, Brian Bot, Andrea Hawkins-Daarud, Kellie Fontes, Carly Bridge, Anne Baldock, Russ Rockne, Erich Huang, and Kristin Swanson. “Use of a novel patient-specific model of glioma growth kinetics to elucidate underlying biology as measured by gene expression microarray.” In Journal of Clinical Oncology, 30:71–71. American Society of Clinical Oncology (ASCO), 2012. https://doi.org/10.1200/jco.2012.30.30_suppl.71.Full Text
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Trister, Andrew D., Brian Bot, Kellie Fontes, Carly Bridge, Anne L. Baldock, Jason K. Rockhill, Maciej M. Mrugala, Russ R. Rockne, Erich Huang, and Kristin R. Swanson. “A NOVEL PATIENT-SPECIFIC MODEL OF GLIOMA GROWTH KINETICS ELUCIDATES UNDERLYING BIOLOGY AS MEASURED BY GENE EXPRESSION MICROARRAY.” In Neuro Oncology, 14:99–99. OXFORD UNIV PRESS INC, 2012.Link to Item
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Pittman, J. L., C. L. Tebbit, E. P. Black, H. K. Dressman, E. S. Huang, J. A. Olson, J. R. Marks, et al. “Predictive models that combine multiple forms of genomic and clinical data to achieve personalized prediction of outcomes in breast cancer.” In Breast Cancer Research and Treatment, 88:S21–22. SPRINGER, 2004.Link to Item
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