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๐Ÿ’ซ About Me:

I am Raksha Devi, an MSc Bioinformatics student (DBT Sponsored) at Savitribai Phule Pune University, with a research focus on computational drug discovery, structural biology, and AI-driven therapeutics. My work centers on molecular docking, ADMET analysis, and machine learningโ€“based modeling of bioactive compounds to identify and optimize potential drug candidates.

I am particularly interested in structure-based drug design and epigenetic targets such as BRD4 and HDAC6, with an aim to develop reproducible computational workflows that integrate molecular modeling and data-driven approaches. My current efforts involve applying Python-based scientific computing tools, including NumPy, pandas, matplotlib, and seaborn, alongside machine learning techniques for biological data analysis.

My academic journey began with teaching NEET Biology, where I developed the ability to simplify complex biological concepts. I now apply this analytical clarity to research, including work on protein structure modeling and exploration of novel compounds such as triazole derivatives for anti-tuberculosis activity.

I am actively seeking opportunities for research collaboration and mentorship in computational biology and drug discovery. My long-term goal is to contribute to impactful, interdisciplinary research and pursue a fully funded PhD at the intersection of bioinformatics, artificial intelligence, and therapeutic design.

Research Interests -Structure-based drug design -AI-driven drug discovery -Epigenetic targets (BRD4, HDAC6) -Molecular docking and simulation -Computational biology -genomics

๐ŸŒ Socials:

Discord LinkedIn email

๐Ÿ’ป Tech Stack:

Markdown PowerShell Python R Windows Terminal Google Cloud Anaconda MySQL Matplotlib PyTorch Plotly scikit-learn NumPy Scipy TensorFlow Pandas GitHub Git Google Cloud Canva

๐Ÿ“Š GitHub Stats:


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MSc Bioinformatics student with a research focus on computational drug discovery and structural biology. Experienced in Python (NumPy, pandas, matplotlib, seaborn) and machine learning for molecular modeling, docking, and ADMET analysis. Interested in AI-driven drug design targeting epigenetic regulators such as BRD4 and HDAC6.

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