Decoding Life

Bioinformatics · AI · Statistical Engineering

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Research Interests

Single-Cell DNA Repair Biology

Developing computational pipelines to decipher repair mechanisms in CRISPR-edited cells using scRNA-seq data

CRISPR Repair Modeling

Multi-layer inference analysis for understanding HDR/NHEJ pathway selection in genome editing

RNA Structure & Function

Computational prediction of RNA triple helices and G-quadruplexes in gene regulation

Statistical Methods for Omics

Building user-friendly statistical tools for biological data analysis and experimental design

Research Software Development

Creating production-ready bioinformatics tools with integrated educational frameworks

0 Publications &
Preprints
0 Major Research
Projects
0 Software Tools
Developed
0 GATE Biotech
AIR 2020

StickForStats

An interactive, modular statistical toolkit that bridges complex inference with an intuitive Streamlit UI. 15+ statistical modules deployed for real‑world research workshops & PhD curricula. 100+ active users in beta testing.

Status: Manuscript complete (v3.0). Public deployment in progress; preprint will be posted upon release (target mid-September 2024).

Python Streamlit Statistics

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TRIPinRNA

In silico platform for predicting intramolecular RNA triple helix structures. Published in Biochemistry (2024), co-first author contribution. Applications in X chromosome inactivation and gene regulation mechanisms.

Python RNA Biology Bioinformatics

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DNA Repair Analysis

Developed a three-layer computational pipeline to decipher repair factor requirements in staggered versus blunt-end DNA breaks using scRNA-seq data and advanced statistical methods.

R scRNA-seq Genomics

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G-Quadruplexes in CCN1

Investigated IGF2BP1-mediated regulation of CCN1 expression through specific binding to G-quadruplex structures in its 3'UTR, revealing novel mechanisms of post-transcriptional control.

Python Proteomics RNA Biology

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Forebrain Assembloids

Computational analysis of RNA-seq data from human forebrain organoids to understand interneuron migration disorders and their role in neurodevelopmental conditions.

RNA-seq Network Analysis Neuroscience

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Confidence Intervals Explorer

Interactive educational tool for understanding statistical confidence intervals through visualizations and simulations, part of the StickForStats statistical platform.

Python Streamlit Statistics

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RNA Lab Navigator

AI-powered RAG assistant transforming laboratory knowledge management with intelligent question-answering, enterprise security, and sub-5-second response times.

Django React RAG AI/ML

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Publications

5.

Das, P. K., Aich, M., Adu, P., Bharti, V., Maiti, S., Chakraborty, D. (2024). "CRISPR-Cas Diagnostics (CRISPR-Dx) of Viral Pathogens in Low and Limited-Resource Areas: Current State and Future Directions." TrAC – Trends in Analytical Chemistry (Review). Under review; rebuttal submitted Aug 24, 2024

4.

Sharma, S., Bharti, V., Das, P.K., et al. (2025). "MLC1 alteration in iPSCs give rise to disease-like cellular vacuolation phenotype in the astrocyte lineage." bioRxiv. DOI: 10.1101/2025.01.06.631607

3.

Rauthan, R., Bharti, V., et al. (2024). "An Interface of Genetically Engineered Human Forebrain Assembloids and Polymeric Nanofiber Scaffolds for Multiscale Profiling of Interneuron Migration Disorders." Stem Cell Reports (Under revision). DOI: 10.21203/rs.3.rs-3831019/v1

2.

Rana, P., Rajat, U., Bharti, V., et al. (2024). "IGF2BP1-Mediated Regulation of CCN1 Expression by Specific Binding to G-Quadruplex Structure in its 3´UTR." Biochemistry. DOI: 10.1021/acs.biochem.4c00172

1.

Rakheja, I.*, Bharti, V.*, et al. (2024). "Development of an In Silico Platform (TRIPinRNA) for the Identification of Novel RNA Intramolecular Triple Helices." Biochemistry. (*Co-first authors). DOI: 10.1021/acs.biochem.4c00334

Manuscript in Preparation

1.

Bharti, V., Chakraborty, D. "StickForStats: An Intelligent Statistical Analysis Platform with Integrated Educational Framework and Semi-Automatic Workflow Guidance." Manuscript complete (v3.0); deployment in progress. Preprint planned upon public release (target mid-September 2024).

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About Me

Electronics-engineer-turned-bioinformatician, currently working as a Project Associate-II at CSIR-IGIB under Dr. Debojyoti Chakraborty. My work spans single-cell genomics, RNA structure analysis, CRISPR repair screens, and AI-driven statistical tools.

I hold an MTech in Biotechnology from IIT Guwahati and a BTech in Electronics and Communication from IEM Kolkata. GATE Biotechnology AIR 127 (2020). My research focuses on developing computational methods for analyzing complex biological data.

Research Focus

Computational Biology & Single-cell: I integrate scRNA-seq analysis and repair-pathway modeling to explain CRISPR HDR/NHEJ outcomes and design better editing strategies.

Methods & Statistics: I build production-grade statistical software for biologists (StickForStats), with validated modules and pedagogy baked in.

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Technical Proficiencies

Programming & Software

Python R JavaScript SQL Django React Streamlit

Bioinformatics & Genomics

RNA-seq Analysis scRNA-seq Network Analysis CRISPR Screens Structural Biology Proteomics

Machine Learning & AI

RAG Systems Statistical Modeling Deep Learning NLP TensorFlow PyTorch

Computational Resources

HPC Clusters Cloud Computing Docker Git Linux

Selected Software

StickForStats

Details

Intelligent statistical analysis platform with 15+ modules for experimental design, hypothesis testing, and data visualization. Features semi-automatic workflow guidance and integrated educational framework.

Python Streamlit Pandas NumPy SciPy

Confidence Intervals Explorer

Live Demo Details

Interactive educational tool for understanding statistical confidence intervals through visualizations and simulations. Deployed on Streamlit Cloud with real-time parameter adjustment.

Python Streamlit Plotly Statistics

RNA Lab Navigator

Details

AI-powered RAG assistant for laboratory knowledge management. Features intelligent Q&A, enterprise security, and sub-5-second response times for complex queries.

Django React RAG PostgreSQL Docker

Future Research Interests

Quantum Biology & Biomolecular Systems

Exploring quantum mechanical phenomena in biological systems, particularly focusing on quantum coherence in photosynthesis, electron tunneling in DNA repair mechanisms, and quantum entanglement in enzyme catalysis. Integrating computational physics with molecular biology to understand life at its most fundamental level.

AI-Driven Drug Discovery

Developing machine learning models for protein-drug interaction prediction, utilizing deep learning for de novo drug design, and creating AI systems that can understand complex biological networks to identify novel therapeutic targets.

Systems Biology & Network Medicine

Understanding disease mechanisms through network analysis of multi-omics data, developing computational models of cellular systems, and identifying biomarkers through integrative analysis of genomic, transcriptomic, and proteomic data.

RNA Biology & Therapeutics

Continuing my work on RNA structural elements (G-quadruplexes, triple helices) and their regulatory roles, developing computational tools for RNA drug design, and exploring RNA-based therapeutic interventions for genetic disorders.

Let's Collaborate

I'm open to research collaborations, consulting opportunities, and discussions about bioinformatics, statistical tools, and computational biology.

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