Repositories List#

bcell - A framework for linear B-cell epitope prediction and classification. (ECML PKDD 2023)

master-thesis - The code for my master’s degree project.

py-cdhit - A Python package for CD-HIT, clustering protein or nucleotide sequences.

auto-sphinx-page-action - GitHub action that creates website using Sphinx.

phasty - A Python interface for PHAST (phylogenetic analysis with space/time models).

config-argument-parser - A package to help automatically create command-line interface from configuration or code.

vae-mixin-pytorch - Variational autoencoders as mixins.

complex_systems - A Python package for studying complex systems.

deep-vaccine - Predict multi-epitope vaccine subunit candidates using NLP.

2048-ai-tk - 2048 AI in Python with GUI.

genome_analysis - Genome analysis labs.

config-argument-parser-docs - Docs of config-argument-parser.

repositories-list - A list of my public repos.

n-body - N-body simulation with quadtree, OpenMP parallelized.

docker-flask-redis-celery - Docker Compose template for web application.

scikit-learn/scikit-learn - scikit-learn: machine learning in Python

pandas-dev/pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

scipy/scipy - SciPy library main repository

matplotlib/matplotlib - matplotlib: plotting with Python

numpy/numpy - The fundamental package for scientific computing with Python.

pytorch/pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

pyg-team/pytorch_geometric - Graph Neural Network Library for PyTorch

huggingface/transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

shap/shap - A game theoretic approach to explain the output of any machine learning model.

probml/pyprobml - Python code for “Probabilistic Machine learning” book by Kevin Murphy

networkx/networkx - Network Analysis in Python

scverse/scanpy - Single-cell analysis in Python. Scales to >100M cells.