/Awesome-Contact-Prediction

A curated list of Contact Prediction related research (including Protein Prediction)

Awesome Contact Prediction:Awesome

A curated list of Contact Prediction and related area.

Research Papers

2022

Scientific Reports 2022

  • Enhancing protein inter-residue real distance prediction by scrutinising deep learning models. [paper] [code]

Bioinformatics 2022

  • ProteinBERT: A universal deep-learning model of protein sequence and function. [paper] [code] train

Briefings in Bioinformatics 2022

  • Accurate protein function prediction via graph attention networks with predicted structure information. [paper]

ICLR 2022

  • OntoProtein: Protein Pretraining With Gene Ontology Embedding. [paper] [code] train
  • Geometric Transformers for Protein Interface Contact Prediction. [paper] [code] (multimer)

2021

Cell Systems 2021

  • Learning the protein language: Evolution, structure, and function. [paper] [code]

Nature 2021

  • DNCON2_Inter: predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning. [paper] [code]

BIBM 2021

  • Inter-protein contact map generated only from intra-monomer by image inpainting. [paper] [code] (multimer)

Proteins: Structure, Function, and Bioinformatics 2021

  • When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14—(tFold for CASP14 contact prediction). [paper]

Bioinformatics 2021

  • Deep graph learning of inter-protein contacts. [paper] [code] (multimer)
  • A deep dilated convolutional residual network for predicting interchain contacts of protein homodimers. [paper] [code]
  • SPOT-Contact-Single: Improving Single-Sequence-Based Prediction of Protein Contact Map using a Transformer Language Model, Large Training Set and Ensembled Deep Learning. [paper]

Briefings in Bioinformatics 2021

  • Accurate prediction of inter-protein residue–residue contacts for homo-oligomeric protein complexes. [paper]

NIPS 2021

  • Language models enable zero-shot prediction of the effects of mutations on protein function. [paper]

ICML 2021

PANS 2021

  • Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. [paper] [code]

TPAMI 2021

  • ProtTrans: Towards Cracking the Language of Lifes Code Through Self-Supervised Deep Learning and High Performance Computing. [paper] [code]

KDD Workshop 2021

  • Modeling Protein Using Large-scale Pretrain Language Model. [paper] [code]

IJCAI 2021

  • Learning unknown from correlations: Graph neural network for inter-novel-protein interaction prediction. [paper] [code] train

ICLR 2021

  • Transformer protein language models are unsupervised structure learners. [paper]
  • BERTology Meets Biology: Interpreting Attention in Protein Language Models. [paper] [code]

arxiv 2021

  • Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model. [paper]

2020

PANS 2020

  • Improved protein structure prediction using predicted interresidue orientations. [paper]

KDD 2020

  • Deep Learning of High-Order Interactions for Protein Interface Prediction. [paper]

2019

NIPS 2019

  • Evaluating Protein Transfer Learning with TAPE. [paper] [code]
  • Generative Models for Graph-Based Protein Design. [paper] [code]
  • End-to-End Learning on 3D Protein Structure for Interface Prediction. [paper] [code]

ICLR 2019

  • Learning protein sequence embeddings using information from structure. [paper] [code]

2018

Nucleic Acids Res 2018

  • ComplexContact: a web server for inter-protein contact prediction using deep learning. [paper] (multimer)

2017

NIPS 2017