Decoding Life

Bioinformatics · AI · Statistical Engineering

Research Interests

The thread through my work: whether a biological conclusion actually follows from the data that produced it. It connects my CRISPR repair analysis, StickForStats, and a pre-registered audit of whether published statistical results can be checked by recomputation.

What I want to find out next: after a Cas9 break, whether a cell repairs or dies, whether the structure of the break and the manner of its delivery shape that commitment, and whether the decision is made cell by cell or coordinated across neighbours. The repair-or-die decision →

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

Building open-source research software, validated against reference implementations

Publications

Peer-reviewed

1.

Rakheja I.*, Bharti V.*, et al. (2024). Development of an in silico platform (TRIPinRNA) for the identification of novel RNA intramolecular triple helices and their validation using biophysical techniques. Biochemistry (ACS) 64(1):250-265. *Equal contribution. DOI: 10.1021/acs.biochem.4c00334

2.

Sharma S., Bharti V., et al. (2026). MLC1 alteration in human iPSCs give rise to disease-like cellular vacuolation phenotype in the astrocyte lineage. Orphanet Journal of Rare Diseases 21:176. DOI: 10.1186/s13023-026-04316-3

3.

Rakheja I., Bharti V., Singh V., Maiti S. (2026). Quercetin affects carcinogenic phenotype of breast and lung cancer cells differentially through sterol regulation mediated by MALAT1 perturbation. Chemistry - An Asian Journal 21(11):e70821. DOI: 10.1002/asia.70821

4.

Das P.K., Aich M., Adu P., Bharti V., Maiti S., Chakraborty D. (2026). CRISPR-Cas diagnostics (CRISPR-Dx) of viral pathogens in low- and limited-resource areas. TrAC Trends in Analytical Chemistry 195:118590. DOI: 10.1016/j.trac.2025.118590

5.

Rana P., Ujjainiya R., Bharti V., Maiti S., Ekka M.K. (2024). IGF2BP1-mediated regulation of CCN1 expression by specific binding to a G-quadruplex structure in its 3' UTR. Biochemistry (ACS) 63(17):2166-2182. DOI: 10.1021/acs.biochem.4c00172

Preprints and manuscripts

6.

Bharti V., Chakraborty D. (2026). StickForStats: automated statistical assumption validation for reproducible computational biology. bioRxiv. DOI: 10.64898/2026.06.15.732278. First and corresponding author; in peer review at BMC Bioinformatics.

7.

Bharti V., Chakraborty D. (2026). Most biomedical articles print no statistical result checkable by recomputation: a pre-registered audit with a 20,000-article out-of-sample replication. First and corresponding author; in preparation for submission to Nature Human Behaviour.

8.

Rauthan R., Bharti V., et al. An interface of genetically engineered human forebrain assembloids and polymeric nanofiber scaffolds for multiscale profiling of interneuron-migration disorders. Research Square preprint, under revision at Stem Cell Reports. DOI: 10.21203/rs.3.rs-3831019/v1

9.

Kochar M., Rao S., Bhattacharjee S., Goel P., Timsina H., Azhar M.K., Bharti V., et al. Folding on the way in: vectorial substrate recognition by human Hsp60. Submitted to Cell, 2026.

10.

Azam T., Kumar A., Singh P., Bharti V., Ekka M.K. Structural and functional analysis of the Chast-NUCB1 interaction in cardiac hypertrophy. Submitted to the Journal of Biological Chemistry, 2026.

Awards

Projects

StickForStats

An open-source web platform whose Guardian system runs eight assumption validators (normality, variance homogeneity, independence, outliers, sample size, modality, linearity, homoscedasticity) before a test executes, and reroutes to an appropriate nonparametric alternative when a critical assumption fails. A companion module re-checks the statistical claims in manuscripts. Validated against SciPy and R. Best Poster Award, EMBO Conference 2025.

Status: Preprint on bioRxiv (2026); in peer review at BMC Bioinformatics. First and corresponding author.

Python Django React Statistics

Checkability Audit

A pre-registered audit of whether published biomedical statistics can be recomputed at all. With the protocol frozen before any data were fetched, 3,000 randomly sampled PubMed Central Open Access research articles (2020–2025) were checked for results whose p-value can be recomputed from the printed test statistic and degrees of freedom, and every estimate was replicated out of sample on a further 20,000 articles. The measurement pipeline is deterministic, with no machine learning in it, so every number reproduces from committed code.

Status: In preparation for submission to Nature Human Behaviour. First and corresponding author.

Python Meta-research Reproducibility PubMed Central

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

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

G-Quadruplexes in CCN1

Computational and proteomics analysis for a study of how IGF2BP1 regulates CCN1 expression by binding a G-quadruplex structure in its 3' UTR (Biochemistry, 2024).

Python Proteomics RNA Biology

Forebrain Assembloids

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

RNA-seq Network Analysis Neuroscience

Confidence Intervals Explorer

Interactive educational tool for understanding statistical confidence intervals through visualizations and simulations, built during the early Streamlit prototype of StickForStats. Deployed on Streamlit Cloud with real-time parameter adjustment; it sleeps when idle, so the first load can take a minute.

Python Streamlit Plotly Statistics

RNA Lab Navigator

Retrieval-augmented research assistant over internal lab documents and the primary literature, for fast, grounded literature triage in a wet-dry lab. In routine use by about 21 researchers.

Django React PostgreSQL Docker RAG

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 build statistical inference pipelines for single-cell data, most recently contrasting repair-factor requirements at staggered versus blunt CRISPR-induced DNA breaks.

Methods & Statistics: I build open-source statistical software that checks the assumptions behind a test before running it (StickForStats, validated against SciPy and R).

Vishal Bharti at the podium at Frontiers in Genome Engineering 2023

Path

  1. Institute of Engineering and Management, Salt Lake, Kolkata
    2014–2018

    B.Tech, Electronics & Communication Engineering

    Institute of Engineering & Management, Kolkata

    Photo: Pinakpani, Wikimedia Commons, CC BY-SA 4.0; cropped and rendered as characters
  2. Tree-lined road on the IIT Guwahati campus
    2020–2022

    M.Tech, Biotechnology

    Indian Institute of Technology Guwahati

    Photo: Nilotpal Hazarika123, Wikimedia Commons, CC BY-SA 4.0; cropped and rendered as characters
  3. CSIR-IGIB South Campus, New Delhi
    2023–

    RNA Biology Group (Dr. Debojyoti Chakraborty)

    CSIR-Institute of Genomics and Integrative Biology, New Delhi

    Photo: Singhprtk, Wikimedia Commons, CC BY-SA 4.0; cropped and rendered as characters

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

Future Research Interests

The repair-or-die decision

SpCas9 leaves blunt DNA ends. FnCas9 leaves a staggered overhang of two to five bases. That difference is small, and it is enough to change which repair pathway a cell commits to. I want to understand the decision one level above pathway choice: whether a cell repairs at all, or dies, and whether the structure of a break and the manner of its delivery propagate upward into that commitment. In our single-cell data we recovered pathway-specific signatures and no death signature at all, and that absence is what I want to work on.

The second half of the question is whether that decision is made cell by cell or coordinated across neighbours. Dissociation destroys the information needed to answer it, so this requires reading perturbation and outcome in the same tissue section rather than building a better model of dissociated data.

Adjacent interests

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.

Email Me Download CV