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Predoctoral Training in Bioinformatics and Computational Biology

生物信息学和计算生物学博士前培训

基本信息

批准号：
10413932
负责人：
THOMAS D TULLIUS
金额：
$ 46.83万
依托单位：
BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-07-01 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10413932
关键词：
Bioinformatics Computational Biology Training pre-doctoral

项目摘要

Project Summary/Abstract This renewal application seeks continued support for the Predoctoral Training Program in Bioinformatics and Computational Biology at Boston University. Five predoctoral training slots per year are requested, to support trainees for the first year of residence. The Bioinformatics Program aims to prepare top researchers for careers in the molecular life sciences who will support the advances now underway in modern medicine. Based largely on the framework of the human genome sequence, these advances depend upon a battery of high-throughput techniques that generate enormous quantities of data that in turn reflect the complexities of biological networks. Full exploitation of this information requires computation-based, interdisciplinary efforts. The Program will inculcate the skills required in this new environment, including (a) an understanding of biological systems, (b) facility with computational methods and statistics, especially for network analysis, and (c) the ability to interact and communicate with colleagues from diverse disciplines. The curriculum includes a strong didactic foundation in computational methods, statistics, biological networks, and database development, along with in-depth examination of biological systems. Experiential learning is emphasized throughout the training (1) the annual International Workshop in Bioinformatics and Systems Biology, a joint undertaking of computational biology graduate training programs in Boston, Kyoto/Tokyo, and Berlin; (2) the Challenge Project, which offers teams of first-year trainees the opportunity to do original research on large-scale problems; (3) the Wet-Lab Experience, which introduces new trainees to state-of-the- curriculum. Program features include art experimental methods in the summer before they officially enter the program; (4) the annual Student- Organized Symposium; (5) three rotations; and (6) an annual Student Seminar at which trainees present their research. Emphasis is placed throughout in developing skills in reproducible and rigorous research, and in communicating science. Numerous mechanisms are employed to assist trainees in preparing for diverse career paths. A distinguished training faculty of 28 members is drawn from 16 departments from the Charles River and Medical campuses of Boston University. Areas of mentor research include genomics, proteomics, epigenetics, neurobiology, biological networks, synthetic biology, systems biology, statistical methods in bioinformatics, metabolomics, virology, immunology, the microbiome, and structural biology. Several mentors are engaged in translational bioinformatics . Co-advising of trainees, by computational and experimental mentors, is strongly encouraged. Students play a large role in defining their interdisciplinary research projects. 16 trainees who have been supported by this T32 grant currently are working towards the Ph.D.; they are a subset of the 54 trainees who currently are members of the Boston University Bioinformatics Ph.D. program.

项目概要/摘要此更新申请寻求对生物信息学和博士前培训计划的持续支持波士顿大学计算生物学。每年需要五个博士前培训名额，以支持第一年居住的实习生。生物信息学项目旨在为顶尖研究人员的职业生涯做好准备分子生命科学领域的专家将支持现代医学目前正在取得的进展。很大程度上基于在人类基因组序列的框架上，这些进步依赖于一系列高通量产生大量数据的技术反过来又反映了生物的复杂性网络。充分利用这些信息需要基于计算的跨学科努力。这计划将灌输这种新环境所需的技能，包括（a）对生物学的理解系统，（b）具有计算方法和统计的设施，特别是网络分析，以及（c）与来自不同学科的同事互动和沟通的能力。课程包括强大的计算方法、统计学、生物网络和数据库开发的教学基础，以及深入研究生物系统。整个培训过程强调体验式学习 (1) 年度生物信息学与系统国际研讨会生物学，在波士顿、京都/东京联合开展计算生物学研究生培训项目，以及柏林; (2) 挑战项目，为一年级学员团队提供原创的机会研究大规模问题； (3) 湿实验室体验，向新学员介绍最先进的技术课程。程序功能包括正式入学前的暑期艺术实验方法； (4) 年度学生- 组织研讨会； (5)三轮； (6) 年度学生研讨会，学员在会上展示他们的成果研究。重点始终放在培养可重复和严谨的研究技能以及传播科学。采用多种机制来帮助学员为不同的课程做好准备职业道路。由 28 名成员组成的杰出培训师队伍来自查尔斯大学的 16 个系波士顿大学河校区和医学院校区。导师研究领域包括基因组学、蛋白质组学、表观遗传学、神经生物学、生物网络、合成生物学、系统生物学、统计方法生物信息学、代谢组学、病毒学、免疫学、微生物组和结构生物学。导师数名从事转化生物信息学。通过计算和实验为学员提供共同建议导师们，大力鼓励。学生在定义跨学科研究项目方面发挥着重要作用。获得本次T32资助的16名学员目前正在攻读博士学位；他们是一个目前是波士顿大学生物信息学博士的 54 名学员的一部分。程序。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data.

DOI：
10.1038/s41467-022-29212-9
发表时间：
2022-03-30
期刊：
Nature communications
影响因子：
16.6
作者：
Hong R;Koga Y;Bandyadka S;Leshchyk A;Wang Y;Akavoor V;Cao X;Sarfraz I;Wang Z;Alabdullatif S;Jansen F;Yajima M;Johnson WE;Campbell JD
通讯作者：
Campbell JD

The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures.

DOI：
10.1158/0008-5472.can-21-0899
发表时间：
2021-12-01
期刊：
Cancer research
影响因子：
11.2
作者：
Chevalier A;Yang S;Khurshid Z;Sahelijo N;Tong T;Huggins JH;Yajima M;Campbell JD
通讯作者：
Campbell JD

Environmental boundary conditions for the origin of life converge to an organo-sulfur metabolism