The Training Component of the Patient-centered Information Commons or PIC has chosen to focus on three major elements that will rely (1) on the strength of this team's existing infrastructure at the Center for Biomedical Informatics at Harvard Medical School and (2) the new science proposed for the Data Science Research component of this proposal to support the overall goals of the Big Data to Knowledge initiative. Direct training of the next generation of leaders is offered in two forms, a pre-doctoral-level distributed training initiative and an undergraduate research internship. With the goal of attracting students to the field of big data science, the competitive Distributed Pre-doctoral Program will target students currently enrolled in quantitatively-focused graduate programs across the country who have passed their qualifying exams and would like to engage in a distance collaborative project with faculty at PIC, thereby exposing them to opportunities not available at their local schools. The undergraduate research internship (Summer Institute in Bioinformatics and Integrative Genomics) will offer a nine week, intensive immersion in didactic lectures with leading big data scientists and a mentored research project with PIC faculty. A second major element will develop a series of instructional Big Data videos that will be publically available to the community. Choice of topics will be developed in consultation with the Consortium members. Lastly, the PIC training and science teams will host both an annual Big Data Conference and a series of monthly Lectures which will be available to the community via videography (for the Conference) and WebEx (for the Lecture series). Success of these initiatives will be evaluated by a defined set of metrics, including surveys and outcomes assessment.

Public Health Relevance

Insuring the next generation of scientists capable of understanding and applying the cutting edge technologies necessary to the acquisition and management of the increasingly huge volumes of data enabled by technology advancement that has exceeded our ability to fully utilize its byproducts is essential to the rapid advancement of biomedical research in general and 'precision medicine' in particular.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
3U54HG007963-04S2
Application #
9552429
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Di Francesco, Valentina
Project Start
Project End
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
4
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Type
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
Yu, Zhi; Kim, Seoyoung C; Vanni, Kathleen et al. (2018) Association between inflammation and systolic blood pressure in RA compared to patients without RA. Arthritis Res Ther 20:107
Neykov, Matey; Hejblum, Boris P; Sinnott, Jennifer A (2018) Kernel machine score test for pathway analysis in the presence of semi-competing risks. Stat Methods Med Res 27:1099-1114
Agniel, Denis; Kohane, Isaac S; Weber, Griffin M (2018) Biases in electronic health record data due to processes within the healthcare system: retrospective observational study. BMJ 361:k1479
Can, Anil; Castro, Victor M; Dligach, Dmitriy et al. (2018) Lipid-Lowering Agents and High HDL (High-Density Lipoprotein) Are Inversely Associated With Intracranial Aneurysm Rupture. Stroke 49:1148-1154
Boag, Willie; Doss, Dustin; Naumann, Tristan et al. (2018) What's in a Note? Unpacking Predictive Value in Clinical Note Representations. AMIA Jt Summits Transl Sci Proc 2017:26-34
Xia, Yin; Cai, Tianxi; Cai, T Tony (2018) Multiple Testing of Submatrices of a Precision Matrix with Applications to Identification of Between Pathway Interactions. J Am Stat Assoc 113:328-339
Brown, Adam S; Patel, Chirag J (2018) A review of validation strategies for computational drug repositioning. Brief Bioinform 19:174-177
Xia, Yin; Cai, Tianxi; Cai, T Tony (2018) Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions. Stat Sin 28:63-92
Kerpedjiev, Peter; Abdennur, Nezar; Lekschas, Fritz et al. (2018) HiGlass: web-based visual exploration and analysis of genome interaction maps. Genome Biol 19:125
Kothari, Cartik; Wack, Maxime; Hassen-Khodja, Claire et al. (2018) Phelan-McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports. Am J Med Genet B Neuropsychiatr Genet 177:613-624

Showing the most recent 10 out of 60 publications