I'm Rafał, a PhD in Chemical Sciences, working with a strong focus on python programming and data science, especially in context of structural bioinformatics and related studies.
I began my career as a traditional wet-lab scientist, but discovery of the power of Python and Bash led me to transition into world of structural biology-related bioinformatics and data science. My expertise lies in structure-oriented python programming, data science, protein folding and analysis, molecular docking, molecular dynamics, computer-aided drug design (CADD), and molecular modelling. More recently, I started applying Machine Learning (ML) and Deep Learning (DL) techniques to biological and chemical data.
For my research, I rely on a range of powerful tools and technologies, such as:
- Python (pandas, numpy, seaborn, scikit-learn, torch, wandb, rdkit, biopandas, and occasionaly flask, streamlit and biopython)
- Bash (as a Linux user and Admin)
- HPC (for scientific calculations using cloud computing with SLURM queue system, AWS in progress..)
- AMBER (for Molecular Dynamics simulations)
- Gnina/vina/diffdock (for molecular docking)
- Rosetta (for versatile protein analysis)
- Colabfold (for AF2 protein folding)
- ESMfold
- USAlign (for screening proper folding)
Throughout my career, I've been involved in a variety of biology-related projects, including:
- Application of Graph Neural Networks in structural features of coiled-coil domains
- Prediction of nucleotide reacticivity in RNA sequence in Kaggle, where my team was awarded with bronze medal as we reached top 10% of prediction accuracy
- Biodegradation of nitroarenes Publication
- Development of selective inhibitors for alkaline phosphatases Publication
- Treatment strategies for Novichok poisoning Publication
- Investigating GPCR receptors Publication
- Exploring Rossmann fold domains Publication
- Establishing a pipeline for an AI-based model to predict new drug candidates Publication
Curious to know more about my scientific background, publications, and achievements? Check out my Google Scholar profile.
Currently, I'm tackling the challenge of resolving improper folding of Connexin proteins, which contributes to a wide range of inherited diseases, including the personal aspect of Charcot-Marie-Tooth 1X syndrome.
In the meantime, I'm extending my knowledge about Deep Learning and doing AWS Certified Cloud Practitioner CLF-C02 course.
If you have any questions or need assistance with AlphaFold2, USalign, Rosetta, or AMBER, feel free to reach out!
Currently, I'm looking for python and data-oriented positions in the IT.
Are you an employer intrigued by my projects and expertise, and believe I'd be a valuable addition to your company? Don't hesitate to get in touch with me!