Aspiring Bioinformatician Unveils the Secrets of Immune Disorders with Cutting-Edge Data Analysis Techniques

Professional Summary:

Aspiring Bioinformatician with a strong foundation in computational biology. Proficient in Python, R, bioinformatics tools and RNA-seq alignment pipelines. Experienced in NGS, data analysis and visualisation, with a deep understanding of Transcriptomics and Machine Learning. Passionate about uncovering the immunological and transcriptomic intricacies of complex disorders and leveraging computational skills to advance biological research.

Skills:

• Programming Languages & Databases: Python, R, Perl, MySQL
• Bioinformatics Tools & Techniques: NGS Analysis (RNA-seq, ChIP-seq, ATAC-seq, Proteomic, Metagenomics, STAR, FASTQC, DeSEQ2, SUPPA), Multi-omics studies (genomics, transcriptomics and proteomics data), Biomarker Discovery, Cytoscape, Functional Annotation, Bioinformatics Databases (ENCODE, TCGA, GTEx, UniProt, ChEMBL, ChEBI, DrugBank, KEGG, GEO, SRA, ENA) etc
• Linux Systems & Cloud Computing: Basics of bash/shell scripting, Grep, Awk, Sed, File systems, Google Colab, Version Control (Git, Github)
• Machine Learning: Pipeline pre and post-processing and analytics, Feature Engineering, Dimensionality Reduction, Data Modelling & Evaluation, Supervised & Unsupervised Machine Learning Models, Data Visualization (ggplot2, plotly, Shiny, matplotlib)
• Therapeutics Knowledge: Drug Discovery, Biochemistry, Immunology & Transcriptomics
• Soft Skills: Excellent verbal and written communication skills, strong presentation skills

Experience:

HaystackAnalytics | Bioinformatics Intern (12/2024 – Present)

• Extracted data from relevant databases via APIs for integration into bioinformatics pipelines.
• Developed an automated Recommendation Algorithm for personalized health insights.

BioMarkIQ | Biomarker Discovery & Analysis Intern (08/2024 – 09/2024)

• Conducted Biomarker Analysis from published literature, detailing the diagnostic utility of biomarkers and contributing to biomarker network construction.
• Analyzed and interpreted biomarker data for the development of VarSee tool.

Evoastra Ventures | Data Science Intern (06/2024 – 08/2024)

• Leveraged Web Scraping & Data Cleaning ([hidden] APIs, normalisation) to gather & prepare data.
• Developed Data Visualizations & Machine Learning models (R & Python) to extract insights.
• Created clustering models to identify patterns in proteomic data, contributing to Down Syndrome Biomarker Discovery.

Education:

Pondicherry University, Puducherry | MSc. Bioinformatics (Graduation Year: 2024)

• Overall CGPA – [hidden]

St. Anthony’s College, Shillong | BSc. Biochemistry (Graduation Year: 2022)

• Overall Percentage – [hidden]
• Among the Top 10 University Rank Holders (North Eastern Hills University)

Research Projects:

EXPLORING SHARED BIOMARKERS & THERAPEUTIC TARGETS IN RHEUMATOID ARTHRITIS & VITILIGO
Identified two major therapeutic targets for diagnosis and of both diseases. Deciphered the Immunology landscapes of RA and Vitiligo using cellular infiltration profiles. TOOLS USED – R, Python, Cibersort, FASTQC, Fastp, HISAT2, FeatureCount, DeSeq2

CLASSIFICATION OF MICE WITH DOWN SYNDROME BASED ON PROTEIN EXPRESSION LEVELS
Developed various machine learning based tools for the identification and prediction of proteins and peptides using proteomics data. Identified key proteins as biomarkers and analyzed the impact of genotype on protein expression. TOOLS USED: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)

BIOACTIVITY PREDICTION APP FOR IDO1 TARGET PROTEIN
Predicts whether a compound has favorable biological activity against the target protein. TECH STACK USED: PADEL-Descriptor Software, Random Forest Regression Model, Python (Pandas, Streamlit, Lazypredict)

Certifications:

• IELTS | English Proficiency Certification (2022) – Overall Band Score [hidden]
• Coursera | Biostatistics for Public Health Specialization (2020) – Summary Statistics, Hypothesis Testing, Simple and Multiple Regression Analysis

Skills (Keywords):
Python, R, Perl, MySQL, NGS Analysis, RNA-seq, ChIP-seq, ATAC-seq, Proteomic, Metagenomics, STAR, FASTQC, DeSEQ2, Linux, Cloud Computing, Bash, Shell Scripting, Machine Learning, Data Modeling, Data Visualization, Drug Discovery, Biochemistry, Immunology, Transcriptomics, Biostatistics

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Cover Letter:

My journey into Bioinformatics began during my undergraduate studies in Biochemistry, where I was captivated by the idea of using computational approaches in Biology. This fascination led me to pursue a postgraduate degree in Bioinformatics, where I have been fortunate to work on several projects such as, using transcriptomic data to identify shared biomarkers and therapeutic targets for Rheumatoid Arthritis and Vitiligo. This project idea was personal to me as close members of my family deal with autoimmune diseases such as Vitiligo, Arthritis and Psoriasis. Through this experience, I gained hands-on expertise in RNA-Seq Analysis, Data Visualization, and Immune Cell Infiltration Analysis. I am also familiar with other types of NGS Analysis such as WGS, Metagenomic and WES analysis. 

Currently, I am employed as a Bioinformatics Intern at HaystackAnalytics Ltd., which is a Healthtech company creating clinical genomic products and tools. This internship has provided me with experience in backend development of Bioinformatics pipelines. During my internship, I developed and implemented automated workflows to process and validate genomic data. I also gained experience in API integration by designing scripts to extract and refine biological databases while adhering to best practices. In collaboration with cross-functional teams, I contributed to creating algorithms that aligned nutritional, fitness, and pathological recommendations with personalized data, driving innovative healthcare solutions. 

During my previous internship at BioMarkIQ, I had the opportunity to learn more about Biomarker Analysis and contribute to the development of a tool for the company. This experience taught me not only theoretical skills, such as Literature Reviewing and Biomarker Analysis, but also the importance of collaboration and persistence in research. My internship at Evoastra Ventures Ltd. gave me exposure to Python, Data Science and Machine Learning techniques, helping me develop clustering models that identified patterns in proteomic data for one of the projects related to Down Syndrome. Beyond my technical skills, I bring a strong sense of dedication and enthusiasm for learning.