amyxlu's Stars
google-research/google-research
Google Research
google-deepmind/deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications
google-deepmind/alphafold
Open source code for AlphaFold.
PetarV-/GAT
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
aqlaboratory/openfold
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
HobbitLong/RepDistiller
[ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods
RosettaCommons/RoseTTAFold
This package contains deep learning models and related scripts for RoseTTAFold
HobbitLong/PyContrast
PyTorch implementation of Contrastive Learning methods
sokrypton/ColabFold
Making Protein folding accessible to all!
gpleiss/temperature_scaling
A simple way to calibrate your neural network.
rdevon/DIM
Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"
songlab-cal/tape
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
Philip-Bachman/amdim-public
Public repo for Augmented Multiscale Deep InfoMax representation learning
facebookresearch/CPC_audio
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.
loeweX/Greedy_InfoMax
Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations
brianhie/scanorama
Panoramic stitching of single cell data
microsoft/protein-sequence-models
samsinai/FLEXS
Fitness landscape exploration sandbox for biological sequence design.
fhalab/MLDE
A machine-learning package for navigating combinatorial protein fitness landscapes.
lucidrains/progen
Implementation and replication of ProGen, Language Modeling for Protein Generation, in Jax
J-SNACKKB/FLIP
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
brianhie/geosketch
Geometry-preserving random sampling
churchlab/low-N-protein-engineering
Code and data to reproduce analyses in Biswas et al. (2020) "Low-N protein engineering with data-efficient deep learning".
jmschrei/ledidi
Ledidi turns any machine learning model into a biological sequence editor, allowing you to design sequences with desired properties.
churchlab/Deep_diversification_AAV
Bioinformatics code for paper associated with deep diversification of AAV
HaochenW/Deep_promoter
The code for paper "Synthetic Promoter Design in Escherichia coli based on Deep Genera-tive Network"
google-research/slip
SLIP is a sandbox environment for engineering protein sequences with synthetic fitness functions.
rmrao/evo
Mono-repo for protein utilities.
smolkelab/promoter_design
Promoter activity measurement and modeling; artificial promoter design and testing
maxwshen/evoracle
A method for reconstructing frequency trajectories and fitnesses of long genotypes from short read data from directed evolution timepoints.