Prateek Arora
Bioinformatics Research Associate, Institute of Anatomy, University of Bern, Switzerland
Bern, Switzerland
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I am a Research Associate in Bioinformatics, currently focused on cardiac regeneration research at the University of Bern. My expertise spans transcriptomics, epigenomics, and metabolomics, with a foundation in developing and deploying analytical pipelines. A significant part of my work involves creating and managing R Shiny apps, enhancing data visualization and accessibility for complex biological datasets. These apps, hosted on platforms like Heroku and shinyapps.io, leverage cutting-edge technologies such as single-cell RNA sequencing, demonstrating my capability in both bioinformatics analysis and software development.
My academic background includes a PhD in Cellular and Molecular Biology from the Tata Institute of Fundamental Research, Mumbai, where I investigated genetic mechanisms in zebrafish, laying the groundwork for my career in bioinformatics. At Elucidata Data Consulting, I led a team in drug target discovery, applying my skills in cloud computing and pipeline development.
I am excited about applying my bioinformatics and app development skills to new challenges in life science and healthcare research, aiming to make significant contributions to the field and improve outcomes.
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Deciphering Heart Regeneration: A Shiny App to Unravel Zebrafish Heart Intercellular Communication
Myocardial infarction, a leading cause of human death according to World Health Organization data, results in a permanent fibrotic scar in the heart. In contrast, zebrafish hearts can regenerate throughout their lifetime, providing opportunities for novel target identification for potential therapies. Although previous studies have identified the cell types involved in this process, the mechanisms of their intercellular communications remain elusive.
To address this knowledge gap, we reanalyzed transcriptomic data from three studies, focusing on key cell types, and constructed a ligand-receptor network based on differentially expressed genes. Utilizing transcriptomic changes, network theory, and literature-based natural language processing, we identified crucial nodes in the network and created a ranked list of genes regulating the regeneration process.
Currently, we are validating our results using CRISPR Cas9-based knockout lines. We present our findings through a user-friendly Shiny app interface, enhancing accessibility. This app allows users to delve into various aspects of the network for deeper insights. Each node provides information on differential ligand receptors, gene expression fold changes, and interacting partners. The ranking table details the gene, its orthologues, synonyms, and the scores that contributed to its rank. The ranking can also be visualized through an interactive graph, highlighting the contribution of each parameter to the total score. Moreover, the option to visualize the data in a scatter plot offers insights into targets based on literature.
The user-friendly interface, with its interactive features for data exploration, provides researchers with freedom and independence in target identification, facilitating heart regeneration research across species.
Prateek Arora
Bioinformatics Research Associate, Institute of Anatomy, University of Bern, Switzerland
Bern, Switzerland
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