Welcome to my GitHub! I'm a Data Scientist and Bioinformatician bridging the gap between computational biology and real-world data science applications. 🧬📊

• 🎓 Master's in Bioinformatics from Hebrew University of Jerusalem
• 📊 B.S. in Data Science from Indian Institute of Science Education and Research (IISER)
• 🧬 Specialized in genomic data analysis, machine learning, and computational biology
• 🌍 International research experience: Charpak Lab Scholarship (Paris) & MITACS (Western University, Canada)
• 💡 Passionate about open-source collaboration, data-driven research, and solving complex biological problems with computational approaches
• 🚀 Committed to making science more accessible and reproducible

• 🦠 Working on microbiome data science and biological data curation
• 🤖 Applying machine learning to genomic and biological datasets
• 📚 Contributing to open-source bioinformatics projects and communities
• 🧠 Expanding expertise in data engineering, database management, and scientific computing
• 🌐 Exploring the intersection of AI, biology, and healthcare

• Bioinformatics & computational biology projects
• Machine learning applications in healthcare and life sciences
• Data science pipelines for genomic and biological data
• Open-source software development
• Scientific data standardization and reproducible research initiatives

• 📊 Statistical Analysis: Predictive modeling, hypothesis testing, experimental design
• 🤖 Machine Learning: Supervised/unsupervised learning, deep learning, model optimization
• 📈 Data Visualization: Creating insights through compelling visual storytelling
• 🔍 Data Mining: Pattern recognition, anomaly detection, feature engineering

• 🧬 Genomic Data Analysis: RNA-seq, variant calling, comparative genomics
• 🦠 Microbiome Analysis: Metagenomic data processing and statistical analysis
• 📚 Scientific Data Curation: Literature review, data standardization, ontology mapping
• 🗂️ Biological Databases: Design, management, and querying of biological data

• Languages: Python, R, SQL, Java, C++
• Data Science Tools: Pandas, NumPy, scikit-learn, TensorFlow, PyTorch
• Bioinformatics Tools: BioPython, Bioconductor packages, genomic analysis pipelines
• Cloud & DevOps: AWS, GCP, Azure, Git, Docker
• Databases: MySQL, PostgreSQL, MongoDB

• AI in Healthcare: Applying machine learning to medical and biological challenges
• Genomic Data Science: Computational approaches to understanding biological systems
• Microbiome Research: Data-driven insights into microbial communities
• Open Science: Building tools and workflows for reproducible research
• Data Engineering: Scalable pipelines for biological and scientific data

• Email: shreyamanushka@gmail.com
• LinkedIn: linkedin.com/in/anushkashreyam
• GitHub: @AnushkaShreyam