Research

Algorithms & Tools Development

We aim to investigate structure and function of proteins by implementing deterministic motif discovery using statistical learning, ligand binding site prediction based on geometrical constraint, and graph theory approaches for pattern discovery in biological sequences. We have developed several online tools/server utilities like Deeplnc, DeepInteract etc. Further, we have also developed database and software for large scale searching like Pharmadoop, DUSR and CEMDB etc.

1. Sunil Patel, Rashmi Tripathi, Vandana Kumari and Pritish Varadwaj, DeepInteract: Deep Neural Network Based Protein-Protein Interaction Prediction Tool, Current Bioinformatics (2017) 12: 551. https://doi.org/10.2174/1574893611666160815150746

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Systems Modeling

Research at SysBio involves investigating olfaction in humans and in machines. This research is aimed at comprehending the function olfactory cognitive process with the help of mathematical model systems-level neurobiological mechanisms of olfactory transduction. Work includes the study of odorant-olfactory receptor and Odors classification. We are currently working on developing cognitive models of olfaction with various in-house developed hardware and bio-signal acquisition devices. Machine learning based classification and other systems modeling approaches has been used to understand and model the olfaction system.

Kumar H, Tichkule S, Raj U, Gupta S, Srivastava S and Varadwaj PK, Effect of STAT3 inhibitor in chronic myeloid leukemia associated signaling pathway: A mathematical modeling, simulation and systems biology study. 3 Biotech. 6:402016. https://doi.org/10.1007/s13205-015-0357-7

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Genomic Big Data Analytics

During the last decades, there is an exponential growth of biological data. In this post genomic era, it has become a challenge to handle the enormous pile of data and to analyze these to mine relevant information. Our lab is currently into the analysis and mining of such large scale data to predict the behavior of such data and the crucial inferences therein. It needs a systematic and intelligent approach to process these Next Generation Sequencing Genomics data efficiently. We have developed workflows and programs to analyze large-scale biological data sets, especially focused towards NGS. Our analysis process includes data quality assessment, comprehensive analysis, and interpreting results. We are currently working on various type of Next Generation Sequencing data (Whole Genome Sequencing Data, Exome Sequencing Data, RNA Sequencing Data and Chip-Seq Data) with special emphasis on variant calling, assembly and alignment problem.

Raj U, Aier I, Semwal R, Varadwaj PK., Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis, Scientific reports. 2017 Jun 12;7(1):3229. https://doi.org/10.1038/s41598-017-03534-x

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Structural Biology

Structural bioinformatics is a challenging field due to biological structures being generally more dynamic when compared to sequential data. This branch of bioinformatics specializes in analysis or prediction of three-dimensional structure of proteins, and their interaction with other molecules. Our work at SysBio encompasses several research activities related to drug discovery, including identification of relevant biological targets and viable lead compounds, classification of proteins based upon unique key features, and identification of active site and potential binding sites in proteins.

1. Aier, I., Varadwaj, P. K. & Raj, U., Structural insights into conformational stability of both wild-type and mutant EZH2 receptor. Scientific reports 6 (2016). https://doi.org/10.1038/srep34984

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