Jessica Dale Tenenbaum | Scholars@Duke

Jessica Dale Tenenbaum
Assistant Professor of Biostatistics & Bioinformatics

Dr. Tenenbaum is a faculty member in the Division of Translational Biomedical Informatics in the Department of Biostatistics and Bioinformatics. Her primary research interests are 1. Informatics to enable precision medicine; 2. Mental health informatics; 3. Infrastructure and standards to enable research collaboration and integrative data analysis; and 4. Ethical, legal, and social issues that arise in translational research, direct to consumer genetic testing, and data sharing. Current research projects focus on analyzing electronic health record data to better understand mental illness, target resource allocation, guide treatment, and develop targeted therapeutic interventions.

Nationally, Dr. Tenenbaum plays a leadership role in the American Medical Informatics Association, serving as Chair of the Mental Health Informatics Working Group and as an elected member of the Board of Directors. She is an Associate Editor for the Journal of Biomedical Informatics and served on the advisory panel for Nature Publishing Group's Scientific Data initiative. After earning her bachelor’s degree in biology from Harvard, Dr. Tenenbaum worked as a program manager at Microsoft Corporation in Redmond, WA for six years before pursuing a PhD in biomedical informatics at Stanford University.

Current Appointments & Affiliations

Assistant Professor of Biostatistics & Bioinformatics, Biostatistics & Bioinformatics, Basic Science Departments 2015
Associate Director for Bioinformatics in the Duke Translational Medicine Institute, Biostatistics & Bioinformatics, Basic Science Departments 2015
Associate of the Duke Initiative for Science & Society, Duke Science & Society, Initiatives 2017

Contact Information

2424 Erwin Road Ste 902, 9024 Hock Plaza, Durham, NC 27705
Duke Box 2721, Durham, NC 27710
jessie.tenenbaum@duke.edu (919) 684-7308
Tenenbaum Group website

Background
Education, Training, & Certifications
- Ph.D., Stanford University School of Medicine 2007
Expertise
Subject Headings
Research
Selected Grants
- Gut Liver Brain Biochemical Axis in Alzheimer's Disease awarded by National Institutes of Health 2018 - 2023
- Metabolic Networks and Pathways Predictive of Sex Differences in AD Risk and Responsiveness to Treatment awarded by National Institutes of Health 2018 - 2023
- Metabolic Network Analysis of Biochemical Trajectories in Alzheimer's Disease awarded by National Institutes of Health 2017 - 2020
- A hands-on, integrative next-generation sequencing course: design, experiment, and analysis awarded by National Institutes of Health 2016 - 2020
- Metabolic Signatures Underlying Vascular Risk Factors for Alzheimer-type Dementias awarded by National Institutes of Health 2015 - 2020
- AMP AD Project B Biomarker Pilot Study: An integrated biomarker discovery pilot study (Broad/Rush-Emory-Duke) 2016 - 2019
- Metabolic Networks and Pathways in Alzheimer's Disease awarded by National Institutes of Health 2014 - 2019
- Improved Disease Stratification Using Electronic Health Records awarded by National Institutes of Health 2017 - 2019
- Duke CTSA (UL1) awarded by National Institutes of Health 2013 - 2018
- NIH BD2K Standards Coordination Center (SCC) - NIH-BD2K-03 2015 - 2016
- Measuring and Talking to Patients about the Accuracy of Data used in Patient Outcomes Research awarded by Patient Centered Outcomes Research Institute 2015 - 2016
- CTSA UL awarded by National Institutes of Health 2006 - 2012
- Duke Clinical and Translational Science Institute awarded by National Institutes of Health 2006 - 2011
External Relationships
- Apple
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Rockhold, Frank W., Jessica D. Tenenbaum, Rachel Richesson, Keith A. Marsolo, and Emily C. O’Brien. “Design and analytic considerations for using patient-reported health data in pragmatic clinical trials: report from an NIH Collaboratory roundtable.” J Am Med Inform Assoc 27, no. 4 (April 1, 2020): 634–38. https://doi.org/10.1093/jamia/ocz226.
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  - Arnold, Matthias, Kwangsik Nho, Alexandra Kueider-Paisley, Tyler Massaro, Kevin Huynh, Barbara Brauner, Siamak MahmoudianDehkordi, et al. “Sex and APOE ε4 genotype modify the Alzheimer's disease serum metabolome.” Nat Commun 11, no. 1 (March 2, 2020): 1148. https://doi.org/10.1038/s41467-020-14959-w.
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  - St John-Williams, Lisa, Siamak Mahmoudiandehkordi, Matthias Arnold, Tyler Massaro, Colette Blach, Gabi Kastenmüller, Gregory Louie, et al. “Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts.” Sci Data 6, no. 1 (October 17, 2019): 212. https://doi.org/10.1038/s41597-019-0181-8.
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  - Liu, Qi, Myung Woo, Xue Zou, Avee Champaneria, Cecilia Lau, Mohammad Imtiaz Mubbashar, Charlotte Schwarz, Jane P. Gagliardi, and Jessica D. Tenenbaum. “Symptom-based patient stratification in mental illness using clinical notes.” J Biomed Inform 98 (October 2019): 103274. https://doi.org/10.1016/j.jbi.2019.103274.
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  - Tenenbaum, Jessica D., Krithika Bhuvaneshwar, Jane P. Gagliardi, Kate Fultz Hollis, Peilin Jia, Liang Ma, Radhakrishnan Nagarajan, et al. “Translational bioinformatics in mental health: open access data sources and computational biomarker discovery.” Brief Bioinform 20, no. 3 (May 21, 2019): 842–56. https://doi.org/10.1093/bib/bbx157.
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  - Embi, Peter J., Rachel Richesson, Jessica Tenenbaum, Joseph Kannry, Charles Friedman, Indra Neil Sarkar, Jeff Smith, and Jeff members of 2016 AMIA Policy Invitational Planning Committee. “Reimagining the research-practice relationship: policy recommendations for informatics-enabled evidence-generation across the US health system.” Jamia Open 2, no. 1 (April 2019): 2–9. https://doi.org/10.1093/jamiaopen/ooy056.
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  - MahmoudianDehkordi, Siamak, Matthias Arnold, Kwangsik Nho, Shahzad Ahmad, Wei Jia, Guoxiang Xie, Gregory Louie, et al. “Altered bile acid profile associates with cognitive impairment in Alzheimer's disease-An emerging role for gut microbiome.” Alzheimers Dement 15, no. 1 (January 2019): 76–92. https://doi.org/10.1016/j.jalz.2018.07.217.
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  - Hong, Julian C., Donna Niedzwiecki, Manisha Palta, and Jessica D. Tenenbaum. “Predicting Emergency Visits and Hospital Admissions During Radiation and Chemoradiation: An Internally Validated Pretreatment Machine Learning Algorithm.” Jco Clin Cancer Inform 2 (December 2018): 1–11. https://doi.org/10.1200/CCI.18.00037.
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  - Barupal, Dinesh Kumar, Sili Fan, Benjamin Wancewicz, Tomas Cajka, Michael Sa, Megan R. Showalter, Rebecca Baillie, et al. “Generation and quality control of lipidomics data for the alzheimer's disease neuroimaging initiative cohort.” Sci Data 5 (November 20, 2018): 180263. https://doi.org/10.1038/sdata.2018.263.
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  - St John-Williams, Lisa, Colette Blach, Jon B. Toledo, Daniel M. Rotroff, Sungeun Kim, Kristaps Klavins, Rebecca Baillie, et al. “Targeted metabolomics and medication classification data from participants in the ADNI1 cohort.” Scientific Data 4 (October 17, 2017): 170140. https://doi.org/10.1038/sdata.2017.140.
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  - Toledo, Jon B., Matthias Arnold, Gabi Kastenmüller, Rui Chang, Rebecca A. Baillie, Xianlin Han, Madhav Thambisetty, et al. “Metabolic network failures in Alzheimer's disease: A biochemical road map.” Alzheimers Dement 13, no. 9 (September 2017): 965–84. https://doi.org/10.1016/j.jalz.2017.01.020.
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  - Tenenbaum, Jessica D., and Kenneth W. Goodman. “Beyond the Genetic Information Nondiscrimination Act: ethical and economic implications of the exclusion of disability, long-term care and life insurance.” Per Med 14, no. 2 (March 2017): 153–57. https://doi.org/10.2217/pme-2016-0078.
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  - Garza, Maryam, Guilherme Del Fiol, Jessica Tenenbaum, Anita Walden, and Meredith Nahm Zozus. “Evaluating common data models for use with a longitudinal community registry.” J Biomed Inform 64 (December 2016): 333–41. https://doi.org/10.1016/j.jbi.2016.10.016.
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  - Tenenbaum, Jessica D., Paul Avillach, Marge Benham-Hutchins, Matthew K. Breitenstein, Erin L. Crowgey, Mark A. Hoffman, Xia Jiang, et al. “An informatics research agenda to support precision medicine: seven key areas.” J Am Med Inform Assoc 23, no. 4 (July 2016): 791–95. https://doi.org/10.1093/jamia/ocv213.
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  - Embi, Peter J., and Jessica D. Tenenbaum. “More on Data Sharing.” N Engl J Med 374, no. 19 (May 12, 2016): 1896. https://doi.org/10.1056/NEJMc1602586.
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  - Hall, Jennifer L., John J. Ryan, Bruce E. Bray, Candice Brown, David Lanfear, L Kristin Newby, Mary V. Relling, et al. “Merging Electronic Health Record Data and Genomics for Cardiovascular Research: A Science Advisory From the American Heart Association.” Circ Cardiovasc Genet 9, no. 2 (April 2016): 193–202. https://doi.org/10.1161/HCG.0000000000000029.
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  - Tenenbaum, Jessica D. “Translational Bioinformatics: Past, Present, and Future.” Genomics Proteomics Bioinformatics 14, no. 1 (February 2016): 31–41. https://doi.org/10.1016/j.gpb.2016.01.003.
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  - Zozus, Meredith N., Rachel L. Richesson, Anita Walden, Jessie D. Tenenbaum, and W. E. Hammond. “Research Reproducibility in Longitudinal Multi-Center Studies Using Data from Electronic Health Records.” Amia Jt Summits Transl Sci Proc 2016 (2016): 279–85.
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  - Tenenbaum, Jessica D., Susanna-Assunta Sansone, and Melissa Haendel. “A sea of standards for omics data: sink or swim?” J Am Med Inform Assoc 21, no. 2 (March 2014): 200–203. https://doi.org/10.1136/amiajnl-2013-002066.
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  - Bernstam, Elmer V., Jessica D. Tenenbaum, and Gilad J. Kuperman. “Preserving an integrated view of informatics.” J Am Med Inform Assoc 21, no. e1 (February 2014): e178–79. https://doi.org/10.1136/amiajnl-2013-002262.
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  - Blach, Colette, Guilherme Del Fiol, Chandel Dundee, Julie Frund, Rachel Richesson, Michelle Smerek, Anita Walden, and Jessica D. Tenenbaum. “Use of RxNorm and NDF-RT to normalize and characterize participant-reported medications in an i2b2-based research repository.” Amia Jt Summits Transl Sci Proc 2014 (2014): 35–40.
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  - Tenenbaum, Jessica D., Andra James, and Kristin Paulyson-Nuñez. “An Altered Treatment Plan Based on Direct to Consumer (DTC) Genetic Testing: Personalized Medicine from the Patient/Pin-cushion Perspective.” J Pers Med 2, no. 4 (October 30, 2012): 192–200. https://doi.org/10.3390/jpm2040192.
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  - MacKenzie, Sandra L., Matt C. Wyatt, Robert Schuff, Jessica D. Tenenbaum, and Nick Anderson. “Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.” J Am Med Inform Assoc 19, no. e1 (June 2012): e119–24. https://doi.org/10.1136/amiajnl-2011-000508.
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  - Shah, Nigam H., and Jessica D. Tenenbaum. “The coming age of data-driven medicine: translational bioinformatics' next frontier.” J Am Med Inform Assoc 19, no. e1 (June 2012): e2–4. https://doi.org/10.1136/amiajnl-2012-000969.
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  - Bhattacharya, Sayanti, Ashley A. Dunham, Melissa A. Cornish, Victoria A. Christian, Geoffrey S. Ginsburg, Jessica D. Tenenbaum, Meredith L. Nahm, et al. “The Measurement to Understand Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) Study Community Registry and Biorepository.” Am J Transl Res 4, no. 4 (2012): 458–70.
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  - Tenenbaum, Jessica D., Victoria Christian, Melissa A. Cornish, Rowena J. Dolor, Ashley A. Dunham, Geoffrey S. Ginsburg, Virginia B. Kraus, et al. “The MURDOCK Study: a long-term initiative for disease reclassification through advanced biomarker discovery and integration with electronic health records.” Am J Transl Res 4, no. 3 (2012): 291–301.
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  - Tenenbaum, Jessica D., Patricia L. Whetzel, Kent Anderson, Charles D. Borromeo, Ivo D. Dinov, Davera Gabriel, Beth Kirschner, et al. “The Biomedical Resource Ontology (BRO) to enable resource discovery in clinical and translational research.” J Biomed Inform 44, no. 1 (February 2011): 137–45. https://doi.org/10.1016/j.jbi.2010.10.003.
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  - Tenenbaum, Jessica D., Michael G. Walker, Paul J. Utz, and Atul J. Butte. “Expression-based Pathway Signature Analysis (EPSA): mining publicly available microarray data for insight into human disease.” Bmc Med Genomics 1 (October 20, 2008): 51. https://doi.org/10.1186/1755-8794-1-51.
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  - Balboni, Imelda, Cindy Limb, Jessica D. Tenenbaum, and Paul J. Utz. “Evaluation of microarray surfaces and arraying parameters for autoantibody profiling.” Proteomics 8, no. 17 (September 2008): 3443–49. https://doi.org/10.1002/pmic.200800146.
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  - Lee, Thomas J., Yannick Pouliot, Valerie Wagner, Priyanka Gupta, David W. J. Stringer-Calvert, Jessica D. Tenenbaum, and Peter D. Karp. “BioWarehouse: a bioinformatics database warehouse toolkit.” Bmc Bioinformatics 7 (March 23, 2006): 170. https://doi.org/10.1186/1471-2105-7-170.
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  - Balboni, Imelda, Steven M. Chan, Michael Kattah, Jessica D. Tenenbaum, Atul J. Butte, and Paul J. Utz. “Multiplexed protein array platforms for analysis of autoimmune diseases.” Annu Rev Immunol 24 (2006): 391–418. https://doi.org/10.1146/annurev.immunol.24.021605.090709.
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- Book Sections
  - Tenenbaum, J. D. “Personalized medicine.” In Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare, 35–60, 2015. https://doi.org/10.1007/978-1-4471-4646-9_3.
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  - Mooney, S. D., J. D. Tenenbaum, and R. B. Altman. “Bioinformatics.” In Biomedical Informatics: Computer Applications in Health Care and Biomedicine: Fourth Edition, 695–719, 2014. https://doi.org/10.1007/978-1-4471-4474-8_24.
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  - Tenenbaum, J. D., N. H. Shah, and R. B. Altman. “Translational bioinformatics.” In Biomedical Informatics: Computer Applications in Health Care and Biomedicine: Fourth Edition, 721–54, 2014. https://doi.org/10.1007/978-1-4471-4474-8_25.
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- Conference Papers
  - Hong, J. C., J. Tanksley, D. Niedzwiecki, M. Palta, and J. D. Tenenbaum. “Accuracy of a Natural Language Processing Pipeline to Identify Patient Symptoms during Radiation Therapy.” In International Journal of Radiation Oncology*Biology*Physics, 105:S70–S70. Elsevier BV, 2019. https://doi.org/10.1016/j.ijrobp.2019.06.522.
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  - Hong, J. C., D. Niedzwiecki, M. Palta, and J. D. Tenenbaum. “Predicting Emergency Visits and Hospital Admissions in Radiation and Chemoradiation: Performance of a Pre-Treatment Machine Learning Algorithm on Different Disease Sites in an Internal Validation Cohort.” In International Journal of Radiation Oncology*Biology*Physics, 102:S59–60. Elsevier BV, 2018. https://doi.org/10.1016/j.ijrobp.2018.06.168.
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  - Payne, Philip R. O., Nigam H. Shah, Jessica D. Tenenbaum, and Lara Mangravite. “Democratizing Health Data for Translational Research.” In Pac Symp Biocomput, 23:240–46, 2018.
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  - Tenenbaum, Jessica D., and Colette Blach. “Best practices and lessons learned from reuse of 4 patient-derived metabolomics datasets in Alzheimer's disease.” In Pac Symp Biocomput, 23:280–91, 2018.
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  - Payne, Philip R. O., Kun Huang, Nigam H. Shah, and Jessica Tenenbaum. “OPEN DATA FOR DISCOVERY SCIENCE.” In Pac Symp Biocomput, 22:649–52, 2017. https://doi.org/10.1142/9789813207813_0061.
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  - Zozus, M. N., A. Walden, M. Byers, T. Powell, P. Wang, M. Garza, G. Del Fiol, J. Tenenbaum, M. Nix, and C. Pieper. “Assessing the quality of electronic health record data and patient self-report data.” In Proceedings of the 22nd Mit International Conference on Information Quality, Iciq 2017, 2017.
  - Zozus, M. N., A. Walden, M. Byers, T. Powell, P. Wang, M. Garza, G. Del Fiol, J. Tenenbaum, M. Nix, and C. Pieper. “Assessing the quality of electronic health record data and patient self-report data.” In Proceedings of the 22nd Mit International Conference on Information Quality, Iciq 2017, 2017.
  - Zozus, M. N., A. Walden, M. Byers, T. Powell, P. Wang, M. Garza, G. Del Fiol, J. Tenenbaum, M. Nix, and C. Pieper. “Assessing the quality of electronic health record data and patient self-report data.” In Proceedings of the 22nd Mit International Conference on Information Quality, Iciq 2017, 2017.
  - Tenenbaum, J. D., S. Madhavan, R. R. Freimuth, J. C. Denny, and L. Frey. “Translational bioinformatics 101.” In Pacific Symposium on Biocomputing, 552–56, 2016. https://doi.org/10.1142/9789814749411_0050.
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  - Balboni, Imelda, Cindy Limb, Jessica Tenenbaum, and Paul Utz. “Sa.21. Evaluation of Microarray Surfaces and Arraying Parameters for Autoantibody Profiling.” In Clinical Immunology, 127:S87–S87. Elsevier BV, 2008. https://doi.org/10.1016/j.clim.2008.03.242.
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Scholarly, Clinical, & Service Activities
Outreach & Engaged Scholarship
- Bass Connections Faculty Team Leader. Using Machine Learning to Generate Clinical Prediction Rules for Clinical Outcomes in Schizophrenia. 2018 - 2019 2018 - 2019
- Bass Connections Faculty Team Leader. Data+ Project Lead. 2017 2017

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Education, Training, & Certifications

Subject Headings

Selected Grants

External Relationships

Selected Publications

Academic Articles

Book Sections

Conference Papers

Outreach & Engaged Scholarship