NSF Sponsored REU in Bioinformatics and Computational Biology
General Information
The excitement for biological research in the 21st century is palpable. Technological advances have opened up a whole new realm of questions that can be addressed experimentally. Thousands of genomes, transcriptomes, and proteomes are being deciphered at an unprecedented pace, and additional high-throughput technologies are in the pipeline. Yet, it is clear that the constraint is no longer generating these vast datasets, but having the time, computer resources, and bioinformatics expertise to analyze them. CSHL’s specialized NSF Research Experience for Undergraduates (REU) program is designed to help address this need for expertise in bioinformatics and computational biology today and in the future by providing early training to undergraduate students that might not otherwise have access to education and research in BCB. This program is an integral component of a larger 10-week summer Undergraduate Research Program (URP) at CSHL, in which 25 U.S. and foreign students participate each year. Students in the CSHL NSF REU perform cutting-edge research in quantitative biology under the close supervision of CSHL mentors, becoming increasingly independent throughout the summer. In addition they learn early in their careers how to integrate biological research with sophisticated computational tools and techniques, REU students interact together, and attend scientific lectures and workshops on topics in biology, bioinformatics, computational biology, ethics, and careers in science by noted faculty in the Center for Quantitative Biology at CSHL and visiting scientists.
Prospective Project Mentors–
Gurinder Atwal - Population genetics; bioinformatics; cancer; stochastic processes; statistical mechanics and information theory
Thomas Gingeras - Genome-wide organization of transcription and the functional roles of non-protein coding RNAs
Christopher Hammell - Post-transcriptional gene regulation; control of animal developmental timing; RNA biology
Gregory Hannon - Growth control in mammalian cells; post-transcriptional gene silencing
Ivan Iossifov - Computational biology; molecular networks; human genetics; human disease; applied statistical and machine learning; biomedical text-mining; molecular evolution
David Jackson - Plant development; stem cell signaling; genomics and imaging
Justin Kinney - Sequence-function relationships; biophysics; deep sequencing; machine learning; transcriptional regulation; DNA replication
Alexei Koulakov - Theoretical neurobiology; quantitative principles of cortical design; computer science; applied mathematics
Alexander Krasnitz - Genomics of cancer; machine learning for biology; inference from noisy biological data; large-scale numerical computing.
Zachary Lippman - Plant development, genetics; molecular mechanisms of phase transitions for flowering time and inflorescence branching; heterosis
Robert Lucito - Genome microarrays; copy number fluctuation; cancer genomics; amplification; deletion; oncogene; tumor suppressor
Rob Martienssen - Epigenetics; DNA methylation; chromatin and chromosome biology; transposable elements; RNA interference; stem cells; germline specification; plant genomics; plant evolution; aquatic plants
W. Richard McCombie - Genomics of psychiatric disorders; genomics of cancer; computational genomics; plant genomics
Partha P. Mitra - Neuroinformatics; theoretical engineering; animal communications; neural prostheses; brain mapping; developmental linguistics
Scott Powers - Cancer genome; molecular targets and therapeutics; functional genomics; cancer biology
Michael Schatz - Genomics; genome assembly & validation; sequence alignment; high performance and multicore computing; parallel algorithms; cloud computing
Marja Timmermans - Plant development; epigenetic regulation of stem cell fate; pattern formation via small RNAs
Doreen Ware - Computational biology; comparative genomics; genome evolution; diversity; gene regulation; plant biology
Michael Wigler - Human genetic disorders; population genetics; cancer genomics
Eligibility
NSF-supported REU participants must be citizens or permanent residents of the United States or its possessions and currently enrolled as an undergraduate student. An undergraduate student is a student who is enrolled in a degree program (part-time or full-time) leading to a baccalaureate or associate degree. Students graduating in the May before the program are not eligible for the CSHL REU-Sites program.
Please click here for the Application Guidelines
Program Overview
Yearly the 10-week CSHL REU Program begins the first week of June and ends the second week of August. During the first week, students receive a guided historical tour of the CSHL campus, and a tour of all CSHL facilities and resources available to them. Before starting in their laboratories, students attend a two-part Responsible Conduct in Research program. Throughout the remaining nine weeks the students receive training in Scientific Research, Science Communication, Career Preparation, and Bioinformatics and Computational Biology, all while interacting socially with fellow program participants and members of the CSHL community at large in formal and informal activities. Below is a schematic of the 10-week intellectually rigorous, yet socially and academically rewarding, experience.
REU Program Alumni
