642:613 Mathematical Foundations of Systems Biology
Rutgers, Fall 09, Course Index Number: 35710

link to sakai website

Instructor: Eduardo Sontag, email: sontag@math (add .rutgers.edu if mailing from outside Rutgers)

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Class will meet Tuesdays and Wednesdays 10:20-11:40, in the BioMaPS seminar room, Hill 260

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Schedule & syllabus for Fall 2009

teaching evaluations (and some comments of mine)

Class notes and other reading materials:

Grading: Class attendance and participation will be expected, and will represent a major component of the grade. In addition, students will be expected to complete a few problem sets to be handed-in, and prepare a term presentation on a mutually-agreed topic (typically, based on a paper).

Course Announcement:

Life, whether at the level of the genome, cells, organs, organisms, or populations, can only be understood when seen as the result of interactions among multiple components. Whether dealing with signal transduction pathways in cells and their disruption in cancer, neuronal networks in brain function, the spread of epidemics in populations, or ecosystem responses to climate change, the typical "reductionist" approach to learning and doing biology is not powerful enough to describe, analyze, and interpret such complex behaviors. Quantitative (i.e, mathematical!) formalisms, concepts, tools, and models are required. Indeed, one could say that the Life Sciences are in the midst of a major revolution in quantitative theoretical formulations, not unlike the transformation that physics underwent in the 17th century.

There are a very large number of possible topics to be covered, and the syllabus will evolve based on student's interest and input. Some of the possible topics include the dynamics of cell signaling networks including memories, switches, and oscillators, chemotaxis, pattern formation, neural transmission, synthetic biology, reverse engineering of gene and protein networks, Markov chains for population models, epidemiology, and the mathematics behind phylogenetic trees, sequence alignment methods, and shotgun DNA sequencing.

The course will consist of instructor's lectures, student discussion of research papers, and perhaps have some guest speakers.

Level and Background:

As I expect that many or even the majority of students taking the course will come from programs other than math (BioMaPS, various Engineering departments, chemistry, genetics, physics, computer science, etc), I will not impose any explicit course prerequisites. At a minimum, however, students should have a working familiarity with linear algebra, differential equations, and basic probability, at the level of an advanced undergraduate or beginning graduate student.