Statistical Physics in Biology Learn more

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. There has been an explosion of discoveries in biology over the past few years, such as the complete genome of many organisms from bacteria to human, the expression profiles of thousands of genes by chip technology and the structures of some RNA and numerous proteins. These biological discoveries resulted in enormous data, and sorting this data requires not only novel conceptual perspectives but also a multitude of computational and statistical tools.

?Who should take this course?
Students contemplating on pursuing advanced studies in bioinformatics or a career in this field are welcome. Even if you are not interested in bioinformatics, you can still take this course for better understanding of statistical models and their application in biological research.

What will you learn from this course?
At the end of the course, should be able to extract information content of DNA using bioinformatic methods. The course will also share with you how you can find genes and compare sequences. Physical interactions responsible for structure of biopolymers will also be discussed in this course.

Table of Contents:
- Evolving populations and Elements of population genetics
- Fixation            
- Introduction to sequence alignment
- Algorithms for sequence alignment
Significance of alignments
- Ionic interactions
- Polymer theory
- Protein folding
- Protein-DNA interactions
- Microtubules
- Molecular motors & cell motility
- Introduction to networks
- Dynamics on networks
- Packing of DNA inside cells       

Author Bio:
This course has been jointly prepared by Prof. Mehran Kardar and Prof. Leonid Mirny.
Mehran Kardar is a prominent Iranian born physicist, currently working as Professor of Physics at the Massachusetts Institute of Technology, and co-faculty at the New England Complex Systems Institute.
Leonid Mirny is an Associate Professor of Health Sciences and Technology and Physics at Massachusetts Institute of Technology.

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