Predoctoral Training Program in Biological Data Science at Brown University
Predoctoral Training Program in Biological Data Science at Brown University
批准号:
10447019
负责人:
Sohini Ramachandran
金额:
$31.09万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-07-01 至 2023-06-30
中文摘要
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英文摘要
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.
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Heuristic bias in stem cell biology.
干细胞生物学中的启发式偏差。
DOI:
10.1186/s13287-019-1355-1
发表时间:
2019
期刊:
Stem cell research & therapy
影响因子:
7.5
作者:
[Quesenberry,Peter, Borgovan,Theo, Nwizu,Chibuikem, Dooner,Mark, Goldberg,Laura]
通讯作者:
Goldberg,Laura
DOI:
10.1016/j.ajhg.2022.03.005
发表时间:
2022-05-05
期刊:
American journal of human genetics
影响因子:
9.8
作者:
[]
通讯作者:
DOI:
10.1371/journal.pgen.1010399
发表时间:
2023-08
期刊:
PLoS genetics
影响因子:
4.5
作者:
[]
通讯作者:
Out of destruction comes new growth: Pore-forming antimicrobials make pancreas grow.
破灭后会产生新的生长:成孔抗菌剂使胰腺生长。
DOI:
10.1016/j.cmet.2022.10.006
发表时间:
2022
期刊:
Cell metabolism
影响因子:
29
作者:
[Yunker,Rebecca, Bonakdar,Maryam, Vaishnava,Shipra]
通讯作者:
Vaishnava,Shipra
GenBank as a source to monitor and analyze Host-Microbiome data.
GenBank 作为监测和分析宿主微生物组数据的来源。
DOI:
10.1093/bioinformatics/btac487
发表时间:
2022
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
[Ramanan,Vivek, Mechery,Shanti, Sarkar,IndraNeil]
通讯作者:
Sarkar,IndraNeil
共 19 条
Novel population-genetic methods for localizing targets of natural selection in diverse human genomes
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批准号:10321900
-
项目类别:
-
资助金额:$37.4万
-
财政年份:2021
-
负责人:Sohini Ramachandran
-
依托单位:
Novel population-genetic methods for localizing targets of natural selection in diverse human genomes
-
批准号:10538648
-
项目类别:
-
资助金额:$37.45万
-
财政年份:2021
-
负责人:Sohini Ramachandran
-
依托单位:
Predoctoral Training Program in Biological Data Science at Brown University
-
批准号:10405983
-
项目类别:
-
资助金额:$8.64万
-
财政年份:2018
-
负责人:Sohini Ramachandran
-
依托单位:
Predoctoral Training Program in Biological Data Science at Brown University
-
批准号:10197955
-
项目类别:
-
资助金额:$29.26万
-
财政年份:2018
-
负责人:Sohini Ramachandran
-
依托单位:
Novel statistical methods to localize genomic elements underlying adaptive evolution
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批准号:9078921
-
项目类别:
-
资助金额:$32.37万
-
财政年份:2016
-
负责人:Sohini Ramachandran
-
依托单位:
Novel statistical methods to localize genomic elements underlying adaptive evolution
-
批准号:9926886
-
项目类别:
-
资助金额:$32.44万
-
财政年份:2016
-
负责人:Sohini Ramachandran
-
依托单位:
Project 1: Incorporating Ethnic and Gender Disparities in Genomic Studies of Disease
-
批准号:9433665
-
项目类别:
-
资助金额:$27.06万
-
财政年份:--
-
负责人:Sohini Ramachandran
-
依托单位:
海外基金