Python in the Life Sciences

With increasing amounts of quantitative data in biology, in particular sequencing and image data, use of Python to process the data and to bridge different tools together is increasing.

I will start with data analysis requirements in biology. In particular, introduce Biopython which is a collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics. Then move to frameworks like Galaxy which are written in Python and allow researchers with no programming experience access to advanced data processing capabilities and, for developers, a front end to make tools easier to use.

Talk outline

• Increase in quantitative data in biology (need for automated handling of data)
• Advances in DNA sequence data generation (high throughput sequencing)
• Brief introduction to bioinformatics
• Introduction to BioPython
• Handling sequence data with BioPython
• Interfacing with online databases using BioPython
• Working with Phylogenetic trees using Biopython
• Galaxy framework to allow non-programmers to perform bioinformatics analysis
• Other open-source bioinformatics projects in Python

I am currently a scientist at the Center of Excellence in Epigenetics at IISER Pune. I have a PhD in Physics from The Ohio State University and a B.Tech. in Engineering Physics from IIT Bombay. I have worked on a number of computational projects from modeling of magnetic fields in sunspots to modeling DNA-protein interactions. I work on developing algorithms for genotype-phenotype correlations, inferring phylogenies, and developing pipelines for processing high-throughput sequencing data. More information about me can be found on my webpage.