Machine Learning Data Analytics

Shivani Pimparkar

+1-959-***-**** ********@**.*** LinkedIn Git

Education

Boston University Expected August 2025

Master of Science in Bioinformatics Boston, MA

Coursework: Applications in Bioinformatics, Foundations of Programming, Data Analytics, Machine Learning in python, Molecular Biology and Biochemistry, Biological Database Analysis, Applications in Translational Bioinformatics, Applied Genetic Analysis.

Dr. D.Y. Patil Biotechnology & Bioinformatics Institute August 2023 Master of Technology (Integrated) Biotechnology Pune, India Coursework: Bioinformatics, Molecular modeling and cheminformatics, Design and analysis of algorithms, Omics Technology, C Programming, Simulation and Modeling, Engineering graphics Skills

Programming: Python, R, Bash, Workflow management (Snakemake, Nextflow), HPC, Git, scikit-learn, SQL Technologies: RNA-seq, scRNA-seq (Seurat), DNA-seq, miRNA analysis, GEOparse, DESeq2, GSEA Wet lab and Molecular Biology: Cell culture, DNA/RNA extraction Tools and platforms: R Shiny, ggplot2, plotly, PyMOL, SWISS-MODEL, FastQC, Linux, public databases (GEO, Ensembl, NCBI) Research Experience

Graduate Bioinformatics Intern May 2025 -August 2025 Boston University Boston, Massachusetts

• Analyzing scRNA-seq data from cortical organoids to study neuronal maturation and oligodendrocyte development under BrainPhys treatment. Assisting with cell type annotation and differential expression analysis; collaborating with the wet lab team and observing calcium imaging and histology workflows. Master’s Project Student November 2022 – May 2023

Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, United Kingdom

• Developed and optimized lipid-modified oligonucleotides (LMOs) to enable spatial relocation of single cells within complex tissue environments

• Generated single-cell RNA sequencing (scRNA-seq) data and conducted downstream analysis using Seurat to map gene expression with high spatial resolution. Focused on improving spatial mapping and cellular localization to better understand tissue architecture

Project Intern January 2022– July 2022

Molecular Diagnostic and Cytogenetics lab, Deenanath Mangeshkar Hospital and Research Centre Pune, India

• Retrospectively analyzed data from 4,439 amniotic fluid samples to detect maternal cell contamination by identifying co- occurrence of XX and XY chromosomes using FISH (Fluorescence In Situ Hybridization)

• Flagged potential contamination where the presence of XX chromosomes indicated maternal cell origin in male fetus

• Utilized excel for data organization, analysis, and cross-referencing with clinical assessments and performed DNA and RNA extraction from blood samples as part of extended molecular diagnostics Clinical Research Assistant July 2023 – July 2024

Renuka Netralaya and Research Foundation Pune, India

• Captured retinal fundus images using a smartphone-based Remidio fundus device and collected AI-generated diagnostic data, including diabetic retinopathy stages

• Compiled patient data in excel and compared AI-based predictions with clinical assessments by ophthalmologists to evaluate diagnostic accuracy. Assessed the reliability and sensitivity of AI tools for early diabetic retinopathy detection in a real-world clinical setting

Projects

1. Protein Structural Analysis of Alpha-Synuclein: Modeled structures and analysed salt bridges to study the E46K mutation linked to Parkinson’s disease;

Tools: PyMOL, SWISS-MODEL

2. R Shiny App for Genomic Data Analysis: Built an interactive app to explore Huntington’s Disease transcriptomics data. Included GSEA, DE analysis, and visualizations

Tools: R Shiny, DESeq2, ggplot2, plotly

3. miRNA Analysis for Cardiovascular Disease

Analyzed miRNA expression in acute myocardial infarction using bioinformatics tools Tools: Python, GEOparse, Scikit-learn, Jupyter Notebook

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