Graduate

Center for Complex Biological Systems (UC Irvine)

Ph.D. training program in Mathematical, Computational and Systems Biology
The Center for Complex Biological Systems (CCBS) at the University of California Irvine administers a Ph.D. training program in Mathematical, Computational and Systems Biology that was developed with the assistance of a grant from the Howard Hughes Medical Institute to create new interdisciplinary Ph.D. programs. Currently, this program is supported by two NIH training grants.

The goal of UCI’s program in Mathematical, Computational and Systems Biology (MCSB) is to provide students from a variety of educational backgrounds with Ph.D. training suitable for research careers in the nascent field of Systems Biology. The program emphasizes in-depth classroom study, interdisciplinary research rotations, and individualized advising. Currently, the program begins with an initial “gateway” year, known as the Mathematical and Computational Biology (MCB) program, during which students receive basic training in principles of biology, as well as in mathematics, engineering and computer science. Students also participate in research rotations, workshops, and directed reading of the Systems Biology literature. Upon successful completion of the MCB year, students select a thesis advisor from among the participating faculty, who represent departments throughout the biological, physical and information sciences and engineering. Students fulfill the remainder of their degree requirements according to the guidelines of the departmental programs to which their thesis advisors belong, at the same time continuing to participate in workshops, retreats, journal clubs and other activities of the MCSB program. At some point in the future, it is expected that MCSB students will also have the option of receiving an interdisciplinary degree independent from departmental program requirements.

A Short Course in Systems Biology: Morphogenesis & Spatial Dynamics

January 9-14, 2012 (Preparatory Workshops)
January 16-27, 2012 (Core Course)

We welcome scientists from all disciplines (biological, physical, mathematical, computational and engineering) with an interest in developing Systems Biology skills. This high-level introductory course is geared towards senior graduate students, postdocs, faculty and industry researchers with a long term interest in pursuing Systems Biology research but who have little or no prior experience in this emerging discipline.

The course design will provide a mix of strategies to help participants:

identify and pose scientific questions from a Systems Biology perspective,
provide biological methodologies for gathering the appropriate kinds of data
and apply mathematical tools for analyses and modeling.

The subject emphasis of the first course will be on cellular controls of cell differentiation, with a central theme of morphogenesis and spatial dynamics. Research models that are dependent on complex spatial information will be the primary focus since this builds on the extensive research expertise of participating faculty, departments and existing centers of excellence at UCI. The course consists of both didactic lectures and hands-on “wet/dry” laboratories and tutorials.

Center for Genome Dynamics (The Jackson Laboratory)

Short Course on Systems Genetics
The one-week Short Course on Systems Genetics covers computational and experimental approaches to genetic studies that utilize whole genome approaches. The course is led by Gary Churchill of the Center for Genome Dynamics and lectures and computer workshops are designed to accommodate students with a wide variety of backgrounds.

Center for Modular Biology (Harvard University)

Marine Biological Laboratory Physiology Course
The Center for Modular Biology provides support for students from outside biology to attend The MBL Physiology Course. The course, founded by Jacques Loeb and one of the oldest continually running biology courses in the world, has a distinguished history that includes the discovery of cyclin B, which led to a Nobel prize for Tim Hunt. Despite its name (which is unalterable since the course has been in existence since 1892), this course has been revamped by Ron Vale and Tim Mitchison into a systems biology course in which half the students come from biological backgrounds and half come from engineering, mathematics, physics or other quantitative sciences. This course is providing exactly the kind of meeting place, graduate training and cutting edge research for biologists and quantitative scientists that the National Centers of Systems Biology try to foster.

Harvard University Systems Biology PhD program
Together with the Harvard Medical School Department of Systems Biology the Center runs the Harvard cross-school PhD program in Systems Biology. Through coursework and collaborative research, the Program enables students to combine experimental and theoretical approaches to develop physical and quantitative models of biological processes. The Program aims to introduce students to the tools that are now available, and to help them select important unsolved problems in biology that may now be possible to address using quantitative and theoretical approaches.

Center for Quantitative Biology (Princeton University)

QCB at Princeton Ph.D. Program
The Program in Quantitative and Computational Biology (QCB) is intended to facilitate graduate education at Princeton at the interface of biology and the more quantitative sciences and computation. Administered from The Lewis-Sigler Institute for Integrative Genomics, QCB is a collaboration in multidisciplinary graduate education among faculty in the Institute and the Departments of Chemistry, Computer Science, Ecology and Evolutionary Biology, Molecular Biology, and Physics. The program covers the fields of genomics, computational biology, systems biology, biophysics, quantitative genetics, molecular evolution, and microbial interactions.

Center for Systems Biology (Institute for Systems Biology)

Graduate students. Since 2006, 25 graduate students have been supervised by ISB Faculty through affiliate appointments with the University of Washington Departments of Bioengineering, Immunology, Computer science, Biology, Biochemistry, Microbiology, and Genome sciences, as well as with the interdisciplinary programs in Molecular and Cellular Biology, and Biomolecular Structure and Design. In 2009, the Center formed a graduate student group to provide career development training. A monthly lunch for the student group is managed by a Center senior scientist, and topics have included ‘op-ed’ discussions relating to current research, laboratory practice, and choosing a postdoctoral position.

Postdoctoral fellows. In 2008, a “Postdoc Association” was formed in response to an ISB survey which indicated postdoctoral fellows needed additional career resources and a formal forum for increased social networking, both within and outside ISB. The Association developed the first annual “ISB Postdoc Retreat”, an all day meeting which also included graduate students as presenters. Agenda items included: “Grant writing at ISB”, discussions on specific research, “Postdoc issues forum”, “All you need to know about IP”, and a workshop “How to pitch to a biotech”. Additionally the Association is a member of the “Postdoc Administrative Leaders”, a cross-organizational group which includes the University of Washington, Fred Hutchinson Cancer Research Center, Seattle BioMed, and Seattle Children’s Hospital. The group was formed to identify and address institutional postdoctoral challenges, and is brainstorming a “Careers in Industry” workshop with the Washington Biotechnology and Biomedical Association (WBBA) early in 2011.

Chicago Center for Systems Biology

Systems Biology Ph.D. Program Overview
A new graduate training program builds on the University of Chicago’s rich tradition of organizing interdisciplinary programs and facilities to encourage collaborative learning and research. Within the Biological Sciences Division (BSD) exists the Committee on Genetics, Genomics and Systems Biology.

Post-Baccalaureate Research Education Program (PREP), The University of Chicago
The Center will fund and host two participants in PREP per year.

Duke Center for Systems Biology

The DCSB supports the PhD program in Computational Biology and Bioinformatics. CBB is an integrative, multi-disciplinary training program that encompasses the study of biology using computational and quantitative methods. In and out of the classroom, students learn to apply the tools of statistics, mathematics, computer science and informatics to biological problems. The vibrant and innovative Duke research in these fields provides exciting interactions between biological and computational scientists.

Systems Biology Center New York (SBCNY)

PhD Training Program

Mount Sinai School of Medicine’s Graduate School of Biological Sciences offers a PhD in Biomedical Sciences in several training areas, including Systems Biology of Disease and Therapeutics. This program trains students to integrate approaches in systems biology, genomics and pharmacology in order to elucidate the pathophysiology of complex human diseases and develop novel therapeutic strategies.

Core Courses

Systems Biomedicine: Molecules, Cells and Networks
This is a core course for entering PhD, MD/PhD and master’s students that introduces the student to integrated approaches to understanding physiological functions and the underlying biochemical, cell biological and molecular biological mechanisms. Elements of genetics and epidemiology are also included. The emphasis is ‘top-down’, beginning with a patho-physiological condition studied from a clinical perspective going down to exploration of the biochemistry and molecular biology underlying the disease and normal state. The course uses a combination of experimental and computational approaches, including methodologies for handling large data sets and for generating different kinds of systems models. An Introductory Module introduces an array of basic concepts and computational tools that will be used throughout the four disease-focused modules that follow. Those four modules are focused on: Diabetes, Cancer, Renal Disease and Drug Abuse.

Principles of Pharmacology
Graduate and medical courses are integrated to introduce the students to important areas of pharmacology including pharmacokinetics, pharmacodynamics and drug metabolism. Receptors, enzymes, and channels are considered as drug targets. Structural aspects of drug design, computational methods for drug-target docking, current issues in drug discovery and development, and gene therapy strategies are all discussed. Students attend medical pharmacology lectures on drug treatment within the cancer pathophysiology course to get a clinical perspective. The students are introduced to emerging concepts in systems pharmacology and how these may be used for drug discovery and polypharmacology and prediction of complex adverse events based on genomic and epigenomic status.

Cell Signaling Systems
This course uses the primary literature to develop a systems level understanding of the mechanisms underlying both information flow and information processing through cell signaling pathways and networks. Effects of signaling on tissue and organ functions in normal and disease states are considered. Current experimental and theoretical concepts in cellular regulatory and drug action, therapeutic and adverse, are highlighted.

Systems Biology: Biomedical Modeling (published in Science Signaling)
This course takes a case-based approach to teach contemporary mathematical modeling techniques to graduate students. Lectures provide biological background and describe the development of both classical mathematical models and more recent representations of biological processes. Students are taught how to analyze the models and use computation to generate predictions that may be experimentally tested. The course has four sections to cover different modeling approaches that are currently being used in biomedical research. These approaches can be classified as: 1) graph theory and network analysis; 2) statistical models, including principal components and regression; 3) ordinary differential equation & partial differential equation-based models; and 4) stochastic models.

The lectures notes, slides and problem sets are accessible from the following page on the SBCNY website: http://sbcny.org/biomedical_modeling.htm

Teaching Resources Published in the Science Signaling September 13 2011 Online Issue

Teaching Resources Published in the Science Signaling September 20 2011 Online Issue

Teaching Resources Published in the Science Signaling September 27 2011 Online Issue