songlab-cal / tape-neurips2019Links
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology. (DEPRECATED)
☆120Updated 3 years ago
Alternatives and similar repositories for tape-neurips2019
Users that are interested in tape-neurips2019 are comparing it to the libraries listed below
Sorting:
- PyTorch library of layers acting on protein representations☆118Updated 11 months ago
- ☆81Updated last year
- Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019☆260Updated 4 years ago
- Predicting protein structure through sequence modeling☆111Updated 5 years ago
- ☆127Updated 4 years ago
- Modelling the Language of Life - Deep Learning Protein Sequences☆72Updated 4 years ago
- UniRep model, usage, and examples.☆352Updated 3 years ago
- Official Pytorch implementation of PLUS (Protein sequence representations Learned Using Structural information), IEEE Access 2021☆41Updated last year
- Recurrent Geometric Network in Pytorch☆28Updated 4 years ago
- Protein function prediction using a variational autoencoder☆93Updated 7 years ago
- Protein-compound affinity prediction through unified RNN-CNN☆147Updated 11 months ago
- Variational autoencoder for protein sequences - add metal binding sites and generate sequences for novel topologies☆87Updated last year
- trRosetta for protein design☆179Updated 4 years ago
- A package to predict protein inter-residue geometries from sequence data☆215Updated 3 years ago
- Reimplementation of the UniRep protein featurization model.☆107Updated 9 months ago
- Energy-based models for atomic-resolution protein conformations☆97Updated 3 years ago
- A generative latent variable model for biological sequence families.☆221Updated 3 years ago
- This repository has been integrated in https://github.com/DeepRank/deeprank2☆145Updated last year
- Deep residual neural network for protein contact/distance prediction developed by Xu group☆79Updated 4 years ago
- The official implementation of the Molecule Attention Transformer.☆246Updated 5 years ago
- A new approach for representing biological sequences☆99Updated 9 months ago
- Note that current version does not include search of very large metagenome data. For some proteins, metagenome data is important. We will…☆100Updated 3 years ago
- DeeplyTough: Learning Structural Comparison of Protein Binding Sites☆164Updated 2 years ago
- Fitness landscape exploration sandbox for biological sequence design.☆163Updated 2 years ago
- Analysis and figure code from Alley et al. 2019.☆59Updated 2 years ago
- Database of Interacting Protein Structures (DIPS)☆101Updated last year
- Official code repository of "BERTology Meets Biology: Interpreting Attention in Protein Language Models."☆301Updated last month
- GREMLIN - learn MRF/potts model from input multiple sequence alignment! Implementation now available in C++ and Tensorflow/Python!☆55Updated 2 years ago
- A convolutional neural network to predict PPI interactions☆42Updated 6 years ago
- Generative Models for Graph-Based Protein Design☆278Updated 4 years ago