Research

Natural Information processing is an exciting interdisciplinary new area that deals with the question: How the nature is doing information processing? Research in this field involves all aspects of information and communication technology (ICT). We want to learn how natural computation is done? How nature stores data? What are the principles of biological information processing? Answers to these questions would help us in understanding the basics of molecular health and diseases, deciphering new methods for drug discovery and also in engineering computers using bio-molecules that can help us in building computers even at nanoscale. Even the chemical reactions can also be viewed as computation per se. Some of the groups doing similar research are listed below. Learn more by reading them.

1. View Microsoft Research on Natural Computation
2. View DNA and Natural Algorithms Group at Caltech
3. View Leiden Center for Natural Computing
4. View Natural Computation Wiki

The main areas of expertise of our lab is in mathematics and computer science. In particular we focus on error correcting codes which is at the heart of classical information and communication technologies ranging from sending data from here to there (communication) and sending data from now to then (storage). When we look at natural information processing we look at from our standpoint where core expertise of error correction has well developed roots in many areas of research of ICT. Currently our ongoing interdisciplinary projects are in RNA secondary structure, Systems Biology, DNA self assembly, computational biology of cancer, cryptography and information security, network coding, quantum error correction, coding theory and e-health. More description for some of our projects is given below.

Molecular Self-Assembly

Self-assembly is a process by which supra-molecular species forms spontaneously from its components. This process is ubiquitous throughout life chemistry and is central to biological information processing. It has been suggested that self-assembly will ultimately become a useful tool for bio-molecular computation, crystallography, nano-technology, and medicine. However robustness (error correction) is a key challenge in realizing the potential of self-assembly. In this area we have developed several interesting compact error correction schemes for DNA self assembly, in close analogy with coding theory, where we use redundancy to correct errors.

Computational and Systems Biology

Systems biology of human and pathogens is quite interesting and challenging. Our research here focuses on the viral pathogen HIV-1, the number one killer in Africa which has already killed 25 million people worldwide. We have modeled the HIV-1 infection in CD4+ T cells and the induced NFk-B activation using a recent technique of stochastic pi-calculus. The goal of our research is to privde a complete molecular picture of this interaction.

1. View Microsoft Research on Computational and Systems Biology
2. View Janelia Farm Research Campus: HHMI
3. View IBM Research on Computational Biology
4. View Systems Biology at Harvard Medical School
5. View Computational and Systems Biology at MIT
6. View Computational and Systems Biology Wiki

RNA-omics

RNA is an important molecule and its double role was discovered by Thomas R. Cech. We are interested in RNA regulatory systems, RNA secondary structures, discovery of non-coding RNAs, classification and RNA-i. We have given a new representation of RNA secondary structure that includes pseudo knots. This will help us in classifying RNA secondary structures.

Quantum Error Correction

Quantum information processing principles are very important to study. After the discovery of Shor's algorithm and subsequently the first quantum error correction scheme in 1995 a lot of work has been done to ensure the relibility of quantum computers. Our work here focus on constructing optimal quantum codes. These include binary (additive and non-additive) and non-binary quantum codes and their various links to combinatorial sturctures such as finite geometry.

Coding Theory (classical, space-time, network)

Our research here focuses on codes over finite rings, finite fields, unitary space time codes and netowork codes. We have found many new and optimal codes. Some of the key problems that we study in coding theory includes the following:

1. Constructions of error-correcting codes
2. Bounds (limitations) on the performance of the error-correcting codes
3. Algorithms for error-corrections (Encoding and Decoding)
4. Connections to other fields (some described above)