Stars
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
Source code of ThermoFormer (Foundation Models for Science Workshop, NeurIPS 2024.)
This is for kinetic parameter prediction for all available enzymes
AI-powered ab initio biomolecular dynamics simulation
Predicting Protein-Ligand Binding Affinity using Persistent Directed Flag Laplacian (PDFL)
Tool to read crystallographic and cryo-EM files and interpolate density values onto a cartesian grid map
Efficient manipulation of protein structures in Python
Official implementation of NeurIPS'24 paper "Bridge-IF: Learning Inverse Protein Folding with Markov Bridges"
InterLabelGO+: Unraveling label correlations in protein function prediction
Workflow to clean up and fix structural problems in protein-ligand binding datasets
Joint embedding of protein sequence and structure with discrete and continuous compressions of protein folding model latent spaces. http://bit.ly/cheap-proteins
Designing target-specific PPI inhibitors with hot-spot-guided deep generative model
Learning Binding Affinities via Fine-tuning of Protein and Ligand Language Models
elkebir-group / derna < 8977 /h3>
RNA sequence design for a target protein sequence
A constraint programming algorithm for RNA inverse folding and molecular design
Deep Exploration Networks - Diverse Deep Generative Models for DNA, RNA and Protein Sequences
A script to detect sRNAs from RNA-seq data
The Read Origin Protocol (ROP) is a computational protocol that aims to discover the source of all reads, including those originating from repeat sequences, recombinant B and T cell receptors, and …
I watched a video on genetic engineering and thought it was really cool. I decided to make some simple tools to work with DNA sequences for fun.