Python, R/Bioconductor, SQL, SAS, GitHub, GraphPad Prism, Jupyter

SAYANTANI MUKHERJEE, M.S.

602-***-**** • ********@***.*** • 1265 E University Dr, Tempe, AZ, 85288, United States • LinkedIn SUMMARY

Dedicated Computational Biologist & Bioinformatics Analyst with expertise in genomic data analysis, molecular biology, and integrative omics, driving biomarker discovery and therapeutic development in precision medicine. Proficient in Python, R/Bioconductor, and NGS workflows, with a strong track record in processing and analyzing large-scale biological datasets to yield actionable insights. Proven ability to collaborate cross-functionally and apply machine learning for predictive modeling in complex biological systems.

CORE COMPETENCIES

Computational Biology & Data Science: Next-Generation Sequencing (NGS), RNA-seq, DNA-seq, Single-cell RNA-seq

(scRNA-seq), GATK, Differential Expression Analysis, Multi-Omics Integration, MHC Haplotype Analysis, Machine Learning

(Random Forest, SVM), Predictive Modeling, Bioinformatics Pipelines, Data Visualization Programming & Data Systems: Python, R/Bioconductor, SAS, MATLAB, Github, Jupyter Notebook, RStudio, BLAST, Galaxy, FastQC, HISAT2, STAR, UCSC Genome Browser, Ensembl, EHR Systems, FHIR Standards, Clinical Data Repositories, MySQL

Preclinical Research & Molecular Biology: qPCR/qRT-PCR, ddPCR CRISPR/Cas9, ELISA, Flow Cytometry, DNA/RNA Extraction, Cell Culture, Western Blotting, FISH, PBMC Isolation, Primary Cell Isolation, Advanced Mammalian Cell Culture, SDS-PAGE, Microbiological Assays, Gene Editing (ZFNs, HDR, NHEJ) Drug Discovery & Translational Science: Target Selection, structure-/ligand-based drug design, molecular docking/dynamics, ADME/PK profiling, lead Compound Optimization, QSAR modeling, BBB permeability prediction, biomarker validation, translational pharmacology

Data Analysis & Statistics: LIMS, Statistical Modeling (PCA, clustering, linear models), GraphPad Prism, Excel, Data Interpretation, Quality Control Protocols

WORK EXPERIENCE

Biodesign Center for Personalized Diagnostics, Arizona State University Summer Research Intern,

Tempe, AZ

May 2024 – Aug 2024

Processed and analyzed over 1 million COVID-19 diagnostic records, achieving a 25% enhancement in dataset quality for downstream molecular analysis.

Developed and validated predictive models to identify significant correlations between demographic/genomic variables and test positivity rates, providing actionable insights for public health strategies. Conducted large-scale protein expression data analysis (>350 profiles), utilizing hierarchical clustering to identify 200+ immunogenic protein candidates, yielding key insights for antigen discovery and vaccine development. Applied core bioinformatics techniques and statistical methods to support molecular diagnostics research, demonstrating foundational strengths in experimental design, protein biology, and translational application of research findings.

Arizona State University,

Research Assistant - Immunogenomics

Tempe, AZ

Sept 2023 - Present

Title: Deciphering the Genetics and Genomics of Resus Monkey Immune Responses Engineered a Python-based analytical pipeline for comprehensive MHC haplotype analysis, enabling rapid characterization across 1,900+ individuals, accelerating genetic insights for vaccine development. Characterized immune gene expression signatures and diversity patterns using multi-omics datasets, integrating RNA-Seq data to uncover key insights into immune function modulation and evolutionary adaptation. Applied high-throughput sequencing data to assess haplotype diversity and genetic linkage, significantly enhancing translational relevance to vaccine development and disease resistance modeling. Generated dynamic visualizations to effectively communicate complex findings in immunogenetics and population health management.

Fortis Hospital (Psychiatry and Mental Health Department), Clinical Psychology & Alzheimer's Patient Data Analysis Intern Chennai, India

Dec 2022 - July 2023

Pioneered Alzheimer's patient-centered research, leveraging MySQL to manage and analyze patient data, enhancing clinical data accessibility by 15% and supporting precision treatment planning. Analyzed Alzheimer's patient records using Python, SAS, and EHR systems, performing rigorous data cleaning to ensure 98% accuracy for research and reporting.

Led training sessions for medical personnel on data recording and assessment procedures, enhancing consistency in patient evaluations by 20% and improving clinical documentation. SRM Institute of Science & Technology,

Computational and Biological Genetics Lab,

Undergraduate Research Assistant,

Chennai, India

Sept 2021 - June 2023

Title: In-Silico and in-Vitro Drug Discovery for Breast Cancer Targets Designed and executed wet lab validation assays using MCF-7 breast cancer cells, including qRT-PCR, ELISA, and Western blotting, to validate biomarkers associated with STAT-3 and MAPK pathways, informing therapeutic strategies.

Developed and validated high-fidelity sample preparation protocols for RNA and protein extraction, ensuring 95%+ integrity for accurate biomarker expression profiling. Executed molecular docking, cross-docking, and molecular dynamics simulations, utilizing cheminformatics tools to evaluate selective inhibitor binding, predict drug transport properties, and optimize lead compounds for drug discovery.

Integrated computational predictions with experimental biomarker validation to strengthen target selection and accelerate preclinical assay development for therapeutic discovery programs. DYJ Life Sciences,

Computer-Aided Drug Designing & Data Visualization Intern, Chennai, India

Jan 2021 - Nov 2021

Conducted integrative RNA-Seq and ChIP-Seq data analysis to identify novel therapeutic targets for influenza virus intervention, leveraging public repositories.

Engineered end-to-end bioinformatics pipelines using Galaxy, BLAST, and custom scripts to efficiently preprocess, align, and interpret high-throughput sequencing data for viral-host interaction profiling. Applied structure-based (SBDD) and ligand-based (LBDD) drug design methodologies, including molecular docking and dynamics simulations, to accurately model drug-target interactions and assess binding stability, pharmacokinetics, and blood-brain barrier permeability of lead candidates. Developed QSAR models and incorporated machine learning algorithms to strategically prioritize compounds based on molecular descriptors, ADME profiles, and predicted bioactivity scores. IIT Kharagpur,

Research Project Assistant, Edufabrica Training

Kharagpur, India (Online)

May 2020 - Dec 2020

Title: Advancing Cystic Fibrosis Treatment through Gene Editing and Drug Interaction Prediction Designed and executed a comparative analysis of CRISPR/Cas9 and Zinc Finger Nucleases (ZFNs) for targeted correction of CFTR gene mutations, modeling editing outcomes in conceptual in vitro and in vivo settings. Extracted and analyzed mutation data from NCBI Gene, ClinVar, and OMIM, designed custom guide RNAs (gRNAs), and performed sequence alignment and in silico modeling to assess nuclease specificity, off-target risks, and target site accessibility for gene therapy applications.

Developed a machine learning-based predictive model to evaluate drug-drug, drug-disease, and drug-herbal supplement interactions, applying Random Forest and SVM algorithms to classify compounds based on pharmacogenomic features.

TEACHING & ACADEMIC CONTRIBUTIONS

Academic Associate Teaching Assistant – BIO 182 School of Life Sciences, Arizona State University Aug 2024 – May 2025

Facilitated interactive lab sessions and discussions for BIO 182, improving student comprehension of complex molecular biology, genetics, and physiology concepts by an estimated 15%. Graduate Teaching Assistant Arizona State University, College of Health Solutions Jan 2024 – Dec 2025

Collaborated with Dr. Valentin Dinu to enhance student engagement, manage assessments, and facilitate team projects for MED 450 and BMI 517.

EDUCATION

Master of Science (MS) in Biomedical Informatics and Data Science Arizona State University, College of Health Solutions

August 2023 – May 2025 Tempe, AZ GPA: 3.97

Bachelor of Technology (B. Tech) in Biotechnology, Specialization in Genetic Engineering SRM Institute of Science & Technology July 2019 – May 2023 Chennai, India GPA: 3.88 CERTIFICATIONS

IRB - Biomedical Research, Arizona State University (ID 662) Basic Life Support (BLS) – American Heart Association Training Center: LBW Training Center, Tempe, AZ SAS - Arizona State University Academic Specialization in Biomedical Informatics issued by SAS Bioinformatics Methods I and II - University of Toronto Drug Discovery - University of California, San Diego COVID-19 Contact Tracing - Johns Hopkins University SELECTED PUBLICATIONS, PRESENTATIONS & CONTRIBUTIONS Authored a bioinformatics research paper (under Prof. Bharat Kwatra) titled “In-Silico Phytochemicals Screening and Analysis for Tuberculosis,” currently under review for publication in the International Journal of Medical and Biomedical Studies (IJMBS), highlighting computational strategies for identifying potential anti-tubercular compounds. Poster Presentation: In-Silico and in-Vitro Drug Discovery for Breast Cancer Targets, Computational and Biological Genetics Lab, SRM Institute of Science & Technology (2021–2023); presented integrated wet-lab and computational approaches for optimizing STAT-3 and MAPK pathway inhibitors using qRT-PCR, ELISA, Western blotting, DFT, ADME profiling, and molecular docking simulations. Generated dynamic visualizations (heatmaps, heterozygosity graphs, LD plots) to support findings in immunogenetics and population health management. Visual outputs are available in a supplementary document upon request. Engineered a Python-based analytical pipeline for comprehensive MHC haplotype analysis across 1,900+ individuals, accelerating population-scale vaccine genomics research. Code is maintained in a private GitHub repository due to ongoing publication review and can be shared upon request. REFERENCES

Available upon request.

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