Enhance Healthcare

Projects being carried out at our Life Sciences Innovation Labs explore the application of computational tools to biological problems. These explorations take the form of algorithm development for analysis of

• Large sets of genomic and metagenomic data using statistical methods.
• Bio-medical literature using natural language processing.
• Drug and drug-like chemicals using mathematical optimization and statistical methods to develop models for their likely behavior in humans.
• Biochemical systems through simulations and the development of software tools for modeling biological macromolecules and drugs (Bio-SuiteTM).
• Enhanced exploration of information on biological entities and processes that are available publicly, through the use of better data integration techniques (Bio-Appliance).
• Better search and retrieval of published bio-medical literature (PubmedAssist) or any corpus of bio-medical documents.

The use of IT tools for computationally intensive processing of medium to large data sets, as well as, the use of high performance computing for simulation of macromolecular systems is a common theme of our research. Our research finds application in solutions that are of use to scientists involved in drug discovery and development. For e.g., the SOrt-ITEMS method is used by researchers worldwide for taxonomic binning of metagenomic data, while the PubmedAssist tools are being used by scientists in pharmaceutical companies for information search and retrieval. The BIO SUITETM set of tools are being used by students in several Indian Universities.

1. Knowledge Platform for Drug Development, in which tools and algorithms are developed to extract information from diverse structured and unstructured information sources, followed by the development of models for biological processes. The key technologies used here are Natural Language Processing, data warehousing and integration.

2. Metagenomics , in which algorithms are developed for analyzing massive quantities of sequence data obtained from a multitude of organisms. Some of these organisms play key roles in the onset and progression of various diseases. With the availability of cheaper high throughput sequencing technologies, Life sciences R&D has witnessed a recent shift of research focus from single genome-based approaches to the high throughput metagenomics approach. The latter approach attempts to identify and characterize a multitude of organisms present in a given environment. Given the volume and complexity of metagenomics data, developing efficient algorithms for accurately analyzing such data still remains a major challenge.

The Metagenomics team in Innovation Labs, Hyderabad is currently involved in developing the following algorithms for analyzing metagenomics sequence data.

• Estimation of taxonomic diversity
• Gene prediction
• Functional characterization
• Community interaction analysis
• Identification and characterization of genes/proteins/metabolites which could serve as potential drug targets

3. Modeling and Simulation, which involves modeling at various scales and modeling of a large variety of systems ranging from chemicals to proteins to networks of proteins

4. Post-genomic health care,in which tools and algorithms are sought to be developed to understand the effects of genomic variations on individual health.

Conclusion: With the increasing volume of experimental and literature data generated from biological experiments, there is a need for developing efficient computational tools for managing and analyzing these data. We have developed a number of tools in this regard and plan to further extend our work in the emerging areas of Life Sciences. For example, various tools are currently being developed by us for analyzing metagenomics data. These tools will be of immense use in identifying organisms/genes/proteins/metabolites which play key roles in the onset and progression of various diseases. Identification of these key players will enable us to identify potential drug targets, diagnostic markers and vaccine candidates for combating several life threatening diseases.