This grant requests support for a new Ph.D. training program in systems biology. Our goal is to train a new wave of systems biology faculty who have even broader interdisciplinary research expertise than the first generation of systems biologists. Systems biology is a nascent field with potential for major impact on drug discovery, the development of personalized medicine, and for helping us understand the molecular bases of complex diseases. It also promises to provide an approach to a deeper understanding of fundamental biological processes, such as differentiation, homeostasis, and evolution. It requires integration of concepts from many disciplines, including medicine, biology, computer science, mathematics, physics, chemistry, and engineering. The Program Faculty represents an energetic and committed multidisciplinary team, with extensive teaching and training experience, that takes seriously the challenge of forging a new discipline. Our Program attracts a diverse student group with varied skills and interests;our training approach is therefore a flexible one, including new interdisciplinary courses, course requirements that are tailored to the needs of the individual, and support for dissertation projects that involve collaboration across two or more labs. Our program aims to educate trainees in the current state of the art in systems biology, and to encourage them to reach higher, expanding the usefulness of theoretical and quantitative approaches in biology and medicine.

Public Health Relevance

Medicine and biology have much to learn from disciplines such as mathematics, physics and computer science. This graduate program brings together students and faculty from many disciplines with the explicit goal of creating a novel interdisciplinary training experience, and producing scientists with a unique and novel perspective on biomedical research.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Institutional National Research Service Award (T32)
Project #
5T32GM080177-02
Application #
8080181
Study Section
National Institute of General Medical Sciences Initial Review Group (BRT)
Program Officer
Maas, Stefan
Project Start
2010-07-01
Project End
2015-06-30
Budget Start
2011-07-01
Budget End
2012-06-30
Support Year
2
Fiscal Year
2011
Total Cost
$265,128
Indirect Cost
Name
Harvard University
Department
Biology
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
Van Egeren, Debra; Madsen, Thomas; Michor, Franziska (2018) Fitness variation in isogenic populations leads to a novel evolutionary mechanism for crossing fitness valleys. Commun Biol 1:151
Rodriguez-Fraticelli, Alejo E; Wolock, Samuel L; Weinreb, Caleb S et al. (2018) Clonal analysis of lineage fate in native haematopoiesis. Nature 553:212-216
Weinreb, Caleb; Wolock, Samuel; Klein, Allon M (2018) SPRING: a kinetic interface for visualizing high dimensional single-cell expression data. Bioinformatics 34:1246-1248
Kuo, James; Stirling, Finn; Lau, Yu Heng et al. (2018) Synthetic genome recoding: new genetic codes for new features. Curr Genet 64:327-333
Tusi, Betsabeh Khoramian; Wolock, Samuel L; Weinreb, Caleb et al. (2018) Population snapshots predict early haematopoietic and erythroid hierarchies. Nature 555:54-60
Weinreb, Caleb; Wolock, Samuel; Tusi, Betsabeh K et al. (2018) Fundamental limits on dynamic inference from single-cell snapshots. Proc Natl Acad Sci U S A 115:E2467-E2476
Briggs, James A; Weinreb, Caleb; Wagner, Daniel E et al. (2018) The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science 360:
Wagner, Daniel E; Weinreb, Caleb; Collins, Zach M et al. (2018) Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo. Science 360:981-987
Baron, Maayan; Veres, Adrian; Wolock, Samuel L et al. (2016) A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure. Cell Syst 3:346-360.e4
Jajoo, Rishi; Jung, Yoonseok; Huh, Dann et al. (2016) Accurate concentration control of mitochondria and nucleoids. Science 351:169-72

Showing the most recent 10 out of 31 publications