# Predoctoral Training Program in Biological Data Science at Brown University

> **NIH NIH T32** · BROWN UNIVERSITY · 2020 · $86,400

## Abstract

PROJECT SUMMARY (1 page/30 lines).
 In this era of Big Data, building a successful and independently funded biomedical research program
requires fluency in both biological data (experimental data generation, bioinformatics, and statistical inference)
and theory relevant to living systems (analytical modeling, computational simulation, and evolutionanry theory).
This dichotomy is challenging to address in doctoral training: biology students are rarely trained to develop or
critique new quantitative methods, and quantitative students analyzing biological data rarely gain depth in
biological data generation. There is an urgent need to curb fragmented efforts to address these challenges, and
to instead develop a centralized community and training program focused on fostering Biological Data Scientists:
scientists whose research leverages observed patterns in biological data to generate new models and
hypotheses for biological processes and systems.
 The objective of this Predoctoral Training Program in Biological Data Science at Brown University is to turn
“I-shaped” predoctoral students — with strength in one discipline — into “pi-shaped” Biological Data Scientists
with two core strengths: (1) generating and analyzing biological data, and (2) developing theoretical models for
and testable hypotheses regarding biological processes. This centralized community at Brown University will be
maintained by 28 engaged, crossdisciplinary faculty preceptors who will mentor four NIH-supported predoctoral
trainees each year along with 4 Brown University-supported trainees each year (resulting in 40 Biological Data
Scientists over 5 years) in a variety of didactic, research, and career development activities for one year. These
activities will include a new year-long graduate seminar, crossdisciplinary research rotations, a program retreat
for faculty and trainees, and a series of roundtable discussions focusing on professional development for
interdisciplinary researchers. The resulting community will promote the development of skills essential for
interdisciplinary biomedical research, including the ability to communicate science to both broad and field-
specific audiences, navigate interdisciplinary collaboration and grant applications, interview for academic and
industry-based research careers, and conduct reproducible and open science. The faculty preceptors' research
programs cover multiple biological organisms, systems, and problems, ranging across evolutionary genetics,
functional genomics, biological networks, molecular biology of aging, developmental robustness, biomedical
informatics, regulation of immunity, and biological physics. Further, the preceptors have a combined annual
research funding base of over $12 million in direct costs, offering a strong foundation to bolster this innovative
training program. This training program will yield investigators equipped to extract new insights into living
systems from complex biological datasets.

## Key facts

- **NIH application ID:** 10146136
- **Project number:** 3T32GM128596-03S1
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Sohini Ramachandran
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $86,400
- **Award type:** 3
- **Project period:** 2018-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10146136

## Citation

> US National Institutes of Health, RePORTER application 10146136, Predoctoral Training Program in Biological Data Science at Brown University (3T32GM128596-03S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10146136. Licensed CC0.

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