A Modular Course on Applications of Support Vector Machines and Ant Colony Optimization in Chemo and Bioinformatics
 (August 26 - 28, 2008)

Support vector machine (SVM) is a very popular learning algorithm, rigorously based on statistical learning theory and structural risk minimization principle. It is a linear classifier in a higher dimensional feature space. Additionally, by virtue of definition of appropriate kernels, the calculations can be carried out in the input space itself. Employing SVM classification and regression methodologies, one can solve several real life and potentially important problems. Ant colony optimization algorithms are inspired by the co-operative search behaviour of real life ants.  Almost blind ants by virtue of their indirect communications made possible by deposition of a chemical known as pheromone are able to do a variety of tasks very efficiently. The software “Ants” mimics the pheromone-mediated search for solving a variety of problems. This modular course has been designed to teach employment of SVM for classification and regression and Ant colony for mining rules for classification. The course will also provide a practical insight on usage of these algorithms for simultaneous classification and feature extraction. These techniques would be illustrated by dealing with important applications in the areas of Chemo- and Bio- informatics and in biomedical signals.

Participants: This course is intended for those working in the broad area of bioinformatics, cheminformatics drug discovery programs in academia and industry. Intake is restricted to 10.

Prerequisites: Master degree in Pharmaceutical science / Life science / Bioinformatics or Batchelor’s Degree in engineering and ability to use Linux and Windows operating systems.

Plan of Course: Workshop presentation would consist of comprehensive lectures and hands on sessions. The first two sessions in the morning would be introduction to Ant Colony Optimization and support vector machine with illustrations of how to implement them for problems in Chemo and bioinformatics and biomedical engineering. Rest of the sessions will concentrate on hands-on and illustration of case studies.  

For further details see www.ibab.ac.in

Course Outline: This workshop will introduce support vector machines, the universally employed classification and regression algorithm and Ant Colony Optimization a recently introduced nature inspired heuristic algorithm based on the search behaviour of real life ants.  

Fee structure: Rs.2000/- and Rs. Rs.5000 /- for participants from Academia and Industry respectively.

Course Coordinators: Dr. V. K. Jayaraman and Dr.Shipra Agrawal
Contact: nsmitha@ibab.ac.in