RESEARCH ACTIVITIES
Systems Biology
Systems Biology seeks to apply quantitative methods to the study of well-studied biological systems. The Systems Biology cluster was established to build on the deep understanding of the influenza virus / human host cell interactions obtained by Professor Sunil Lal from the studies of the system by his research group.
Research
Systems biology interdisciplinary approaches have become an essential analytical tool that may yield novel and powerful insights about the nature of human health and disease. Complex disorders are known to be caused by the combination of genetic, environmental, immunological and / or neurological factors. Thus, to understand such disorders, it becomes necessary to understand biology at the system level, entailing the functional analysis of the structure and dynamics of cells and organisms. It is an approach to identify the crucial determinants which when altered change the physiological state of the body from healthy to a diseased one.
Systems biology of the host, influenza virus and their interaction with each other gives insights into various signaling cascades triggered post-influenza infection in the host cells which may change the activity of the effector proteins, thereby generating a specific phenotypic response.
With the advent of all these high throughput platforms, a huge amount of high-dimensional data is generated which has to be analyzed in a systematic manner to understand the dynamics of a diseased state. The same approach has been utilized here wherein, Influenza A NP( Nucleoprotein) interaction partners in the host have been deciphered.
Gene expression data of either the host or the virus during infection-related conditions or in vivo has strongly contributed to our knowledge about virulence factors, biomarkers, host immunity and the dynamics of infection. The underlying aim of the current project is to identify the different interacting partners, host or virus for Influenza A nucleoprotein that help the virus to establish a successful infection in the host. In order to achieve the same the project has been divided into the following.
Infrastructure Development
Research infrastructure that is imperative for handling huge data sets has been partially developed and the remainder is underway, to be completed in 2018. Both Software and Hardware infrastructure upgrades has been summarized below:
a. Computational Software
1. Host network generation: STRING( Search Tool for the Retrieval of Interacting genes / Proteins), HAPPI version 2.0( Human Annotated and Predicted Protein Interactions).
2. Virus network generation: NCBI( Literature search tool), VirHostNet, viRBase, VirusMentha databases.
3. Host-virus map development: Cytoscape version 3.5.1 and Gephi were used for visualizing and analyzing the interaction data graphically.
b. Hardware Requirements
Currently, we are using the Genomics Facility for our in-silico data analysis. However, we are limited due to the low compatibility of some of the plugins and softwares with Linux based operating systems. Proposals have been submitted to ITS, Monash University, Malaysia to develop and provide access to high end virtual computing facilities to ensure smooth operation of the project. The following are the upgrades in progress:
• Operating System: Windows 10( Dual boot with Ubuntu) • 28 GB RAM( Quadracore)
• Intel Core i7-7700 3.6G( up to 4.2GHz) 8M 2133 4C CPU • CPU: i8( Coffee Lake)
• 2TB 7200 RPM SATA 6G 3.5 HDD
• Graphics card: GTX 1080 Ti / Titan XP
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