Bioinformatics graduate student with hands-on experience in RNA-seq analysis, genome assembly, and applied data science for biological datasets. Expertise in high-performance computing and automation of genomics workflows using SLURM and scripting languages such as Python, R, and Bash. Proven ability to apply computational tools to enhance reproducibility and support data-driven biological research.
Overview
1
1
year of professional experience
1
1
Certification
Work History
Research Trainee
Quick IsCool
11.2023 - 06.2024
Predicted protein-ligand interactions using AlphaFold, AutoDock Vina, and PyMOL, improving accuracy in drug-target modeling.
Performed Gene Ontology (GO) enrichment and pathway analysis, identifying key biological pathways for targeted drug interventions.
Analyzed drug-target interactions and off-target effects using computational tools, optimizing drug repurposing strategies.
Developed and validated machine learning models for disease risk prediction and drug sensitivity analysis in oncology, enhancing precision medicine approaches.
Data Science Intern
Solar Secure IT Solutions
12.2023 - 02.2024
Designed and implemented machine learning models to analyze booking trends, increasing predictive accuracy.
Preprocessed and cleaned large datasets, improving model performance and reliability for actionable insights.
Automated data analysis workflows, reducing processing time by 30% and improving efficiency in decision-making.
Education
Master of Science - Bioinformatics
Northeastern University
Toronto, ON
01.2026
PG Diploma - Bioinformatics
St. Xavier's College
Mumbai, India
01.2023
Bachelor of Science - Biotechnology, Chemistry, Botany
St. Aloysius College
Mangalore, India
01.2022
Skills
NGS data processing
RNA-Seq analysis
Variant interpretation
Pathway enrichment
Predictive modeling
Exploratory data analysis (EDA)
Data visualization
Python
R
Bash scripting
MySQL
Nextflow
Docker
Power BI
Tableau
Seaborn
Ggplot2
Problem-solving
Team collaboration
Adaptability
Critical thinking
Projects
Genome Assembly and Quality Control – Bacillus subtilis
Reproduced and evaluated the AssemblyQC pipeline, a Nextflow-based tool for genome assembly quality assessment, using Bacillus subtilis as a test case.
Executed the pipeline on HPC using Singularity and Nextflow, troubleshooting errors and resolving environment-specific compatibility issues.
Investigated discrepancies in assembly metrics and emphasized the importance of standardized, reproducible workflows in computational genomics.
Replication of RNA-seq Study in Hashimoto’s Thyroiditis
Reproduced a published RNA-seq pipeline to investigate gene expression patterns in Hashimoto’s Thyroiditis.
Implemented a full Bulk RNA-seq analysis workflow including quality filtering (fastp), rRNA removal (Bowtie2), alignment (HISAT2), and expression quantification (featureCounts).
Identified immune-related genes with significant differential expression and enriched pathways, validating findings consistent with autoimmune signatures.
Multi-Omics Statistical Analysis of Diabetes Subtypes
Analyzed high-dimensional RNA-seq and lipidomics data across diabetes subtypes to uncover disease-specific molecular patterns.
Applied dimensionality reduction and unsupervised clustering to stratify patient groups and detect outlier profiles.
Identified distinct biomarkers separating T2D from IGT and ND, and validated findings through clinical correlations.