I am Shakthidhar K.V.

A passionate and detail-oriented Bioinformatics professional with strong expertise in computational biology, data analysis, and bioinformatics tools. Experienced in working with large datasets, performing advanced statistical analyses, and developing predictive models. Proven ability to collaborate in diverse teams and apply machine learning algorithms to real-world biological data. Actively contributing to open-source projects in bioinformatics and data science.

Edutech Life (affiliated with IIT Kharagpur)

• Conducted comprehensive analysis on adverse drug reactions across 9 countries, improving drug safety measures.
• Utilized bioinformatics tools like Linux, R, and Microsoft Office Suite for data processing and analysis.

• Performed CHiP-sequence analysis using K562 cell lines and human genome reference (hg19).
• Applied advanced statistical techniques to analyze chip regions, chromosomal distributions, and promoter regions, contributing to the understanding of cellular signaling in immune responses.

Master of Science in Bioinformatics
JSS Academy of Higher Education and Research, Mysuru, Karnataka

Technologies: R, RStudio, Python

• Analyzed PTK2 gene expression in relation to menopausal status and its effect on breast cancer progression.
• Created compelling visualizations using ggplot2 and analyzed statistical significance (p < 0.05) in cancer subtypes.

Technologies: AlphaFold, Phyre2, PyRx, Biovia Discovery Studio

• Conducted molecular docking simulations and structural analyses of Sxl2 protein to understand its biological functionality.
• Developed insights into protein folding and ligand interaction through computational approaches.

Technologies: Python, scikit-learn, Random Forest, Decision Trees

• Built a machine learning model to predict passenger survival based on demographic features.
• Applied Random Forest and Decision Tree algorithms for classification, achieving high predictive accuracy.

• Programming Languages: Python, R, C, SQL
• Tools & Libraries: Pandas, Numpy, Scikit-learn, Matplotlib, ggplot2, Seaborn
• Platforms & Technologies: Linux (Bash), AWS basics, Git (VCS), Docker
• Bioinformatics Tools: HOMER, IGB, MACS2, CEAS, AlphaFold, Phyre2, ClustalW
• Machine Learning: Random Forest, Decision Trees, Logistic Regression

• Data Analysis with Python: Zero to Pandas
• Git Version Control Systems
• Complete SQL Bootcamp
• Introduction to Data Science with Python (Coursera)

• Published a research paper on the computational analysis of protein-ligand interactions in Staphylococcus xylosus (under review).
• Awarded the "Best Research Presentation" for the CHiP-sequencing analysis at the Bioinformatics Conference 2023.

• Email: kvshakthidhar@gmail.com
• LinkedIn: linkedin.com/in/kvshakthidhar
• GitHub: github.com/kvshakthidhar