Computational immunology : models and tools

Free download. Book file PDF easily for everyone and every device. You can download and read online Computational immunology : models and tools file PDF Book only if you are registered here. And also you can download or read online all Book PDF file that related with Computational immunology : models and tools book. Happy reading Computational immunology : models and tools Bookeveryone. Download file Free Book PDF Computational immunology : models and tools at Complete PDF Library. This Book have some digital formats such us :paperbook, ebook, kindle, epub, fb2 and another formats. Here is The CompletePDF Book Library. It's free to register here to get Book file PDF Computational immunology : models and tools Pocket Guide.

  • Auto Mania: Cars, Consumers, and the Environment.
  • Developing Literacy in the Primary Classroom;
  • Computational Biology & Bioinformatics | Broad Institute.

In the M. Tech CB program, the student will do 32 credits of course work and 16 credits for a Thesis, for a total of 48 credits.

Background

The student will have to do a minimum of 20 credits of coursework in Computational Biology. Following are the core and elective subjects for this program.

This list will evolve over time. Among the elective course, upto 12 credits can be done from CSE course that are approved by the PG committee. The following is the list of approved CSE elective courses and more may be added over time.

Thesis: Student will be required to do a thesis in Computational Biology — there is no scholarly paper option. Preparatory Course : An intensive preparatory course is conducted for a month every year, before the onset of the first semester for a new M. Tech batch of students, which includes the following three components: Biology, Mathematics and Programming and Data Structures.

With the successful completion of this program, graduates will acquire the necessary knowledge and skill set to be employed in companies that are working in the areas of computational biology. To this end, we have extended an agent-based simulator of the immune response, C-ImmSim, such that it represents pathogens, as well as lymphocytes receptors, by means of their amino acid sequences and makes use of bioinformatics methods for T and B cell epitope prediction.

Introduction to Computational Immunology

This is a key step for the simulation of the immune response, because it determines immunogenicity. The binding of the epitope, which is the immunogenic part of an invading pathogen, together with activation and cooperation from T helper cells, is required to trigger an immune response in the affected host.

source site To determine a pathogen's epitopes, we use existing prediction methods. In addition, we propose a novel method, which uses Miyazawa and Jernigan protein-protein potential measurements, for assessing molecular binding in the context of immune complexes.

Society Affiliations
admin