Python-centric Cookiecutter for Molecular Computational Chemistry Packages
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- python-packages
- molecular-sciences
- conda-environment
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Python-centric Cookiecutter for Molecular Computational Chemistry Packages
A dependency-free cross-platform swiss army knife for PDB files.
A C++14-compatible physical units library with no dependencies and a single-file delivery option. Emphasis on safety, accessibility, performance, and developer experience.
A thin layer of graphic data types
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
Exascale multiphase flow solver — 2025 Gordon Bell Prize Finalist | 200T grid points on 43K+ GPUs
Benchmarking analysis of data integration tools
Parsers and algorithms for computational chemistry logfiles
The repository host gives no description.
PyKEP is a scientific library providing basic tools for research in interplanetary trajectory design.
The repository host gives no description.
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
A simple script for fracturing polygons. Also adds nice helper functions for polygons like calculateArea, triangulate, getRandomPointsInPolygon, getBoundingRect)
Universal cheminformatics toolkit, utilities and database search tools
Reference mapping for single-cell genomics
V library to develop Artificial Intelligence and High-Performance Scientific Computations
The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.
Python library for multilinear algebra and tensor factorizations
Quantum Computer Library for Everyone
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
A library designed to ease geographic coordinate format conversions, and determine sun/moon information in C#
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
Deep Reinforcement Learning for de-novo Drug Design