Open to PhD & Research Roles

Hi, I'm Pranjali Sharma

Bioinformatics Researcher

I build context-aware computational biology systems for sequencing data, chromatin accessibility, regulatory networks, and deep-learning models that understand biological context.

CSIR-IHBT M.Sc. Bioinformatics Python β€’ PyTorch β€’ R Multi-omics
Pranjali Sharma

Research Snapshot

Bioinformatics, Deep Learning, and Regulatory Genomics

Current Work CSIR-IHBT Dissertation

Context-aware TF binding and CLIP-seq prediction

Education M.Sc. Bioinformatics

Devi Ahilya Vishwavidyalaya | 9.54 CGPA

Focus Multi-omics

Integrating ATAC-seq, RNA-seq, and ChIP-seq

Profile

About Me

Bridging biology and computation to decode life's regulatory logic

I focus on building deep learning systems that respect biological context. My work involves modeling how transcription factors and RNA-binding proteins interact with the genome and transcriptome, using multi-modal data integration.

"I bridge the gap between high-throughput sequencing data and actionable biological insights."

Currently at CSIR-IHBT, I am developing context-aware prediction frameworks for TF binding and RBP sites, combining sequence information with chromatin accessibility and expression profiles.

DL

Deep Learning

PyTorch, PyG, AlphaFold, CNNs, Graph Transformers

NGS

Bioinformatics

RNA-seq, CLIP-seq, ChIP-seq, ATAC-seq workflows

REG

Regulatory Genomics

TF Binding, Causal GRNs, Chromatin Accessibility

SYS

Systems

Linux/Ubuntu, Bash, Git, Python, R, MySQL

Academic Path

My Education

Foundations in microbiology and bioinformatics

πŸŽ“

M.Sc. in Bioinformatics

Devi Ahilya Vishwavidyalaya, Indore

Pursuing advanced studies in computational biology, multi-omics, and machine learning. Specializing in regulatory genomics and deep learning applications.

2024 – 2026DAVV IndoreCGPA 9.54
πŸ”¬

B.Sc. in Microbiology

Acropolis Institute, Indore

Built a strong foundation in molecular biology, genetics, and laboratory techniques. Graduated with honors and a focus on microbial systems.

2021 – 2024AcropolisCGPA 8.58
Portfolio

Research & Projects

Deep learning systems for biological discovery

β˜… FEATURED
🧬

DuATTAC

DualStream-ATAC regresses log2 fold-enrichment ATAC-seq signals from DNA sequence and RNA-seq derived multi-gene context vectors.

PyTorchATAC-seqRNA-seq
πŸ•ΈοΈ

Causal GRN Pipeline

Genome-wide RNA-seq causal network inference pipeline using knockoff selection, MB-LASSO, and directed acyclic edge orientation.

PythonNetworkXRNA-seq
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RNA-seq Automation

End-to-end workflow for quality control, alignment, and differential expression analysis for high-throughput sequencing data.

RSnakemakeQC
🧠

CLIP-seq prediction

Dissertation work applying DenseNet and transformer-style approaches to predict RNA-binding protein binding sites.

DenseNetCLIP-seqRBP
Presentations

International Conference

Sharing research with the global scientific community

COPM 2026
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Accepted Abstract

My abstract on "Context-aware deep learning for transcription factor binding prediction" has been accepted for presentation at the International Conference on Computational Omics and Precision Medicine (COPM 2026).

InternationalOmicsDeep Learning
Toolbox

Tech Stack

The tools powering my research

PyTorch
Python
R / Bioconductor
Jupyter
NumPy / Pandas
Scikit-learn
PyG / AlphaFold
Git
Linux / Bash
MySQL
Professional Dashboard

Resume Snapshot

A compact view of experience, research, and skills

9.54 Masters CGPA (DAVV Indore)
5+ Sequencing pipeline workflows
6 Branch late-fusion TF predictor
IHBT

Masters Dissertation - Bioinformatics

CSIR-IHBT, Palampur | 2025 - Present

  • Developing context-aware TF binding frameworks using multi-modal data.
  • Building ChIP-seq and ATAC-seq prediction workflows using deep learning.
  • Inferring regulatory interaction networks from high-dimensional omics data.
  • Implementing reproducible Snakemake pipelines for automated data processing.
AI

Technical Skills

Programming & ML

Python, R, PyTorch, scikit-learn, BioPython, tidyverse, PyG, CNNs, Transformers

Bioinformatics

STAR, HISAT2, Bowtie2, SRA Toolkit, Trimmomatic, FastQC, MultiQC, Bioconductor

Regulatory Genomics

RNA-seq, CLIP-seq, ChIP-seq, ATAC-seq, Causal GRNs, Chromatin Accessibility

βœ“

Abstracts & Training

COPM2026 Accepted Abstract ICMR-NICPR Internship Multi-modal Deep Learning Genomic Data Science
Connect

Let's Talk

Open to PhD opportunities and collaborative research