Protein Structure Prediction

46 papers with code • 4 benchmarks • 1 datasets


Use these libraries to find Protein Structure Prediction models and implementations

Most implemented papers

Highly accurate protein structure prediction with AlphaFold

deepmind/alphafold Nature 2021

Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics.

MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure Prediction

mzweilin/EvadeML-Zoo 10 May 2016

Predicting protein properties such as solvent accessibility and secondary structure from its primary amino acid sequence is an important task in bioinformatics.

Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations

idrori/cu-tsp 9 Nov 2019

Our dataset consists of amino acid sequences, Q8 secondary structures, position specific scoring matrices, multiple sequence alignment co-evolutionary features, backbone atom distance matrices, torsion angles, and 3D coordinates.

SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning

jonathanking/sidechainnet 16 Oct 2020

Despite recent advancements in deep learning methods for protein structure prediction and representation, little focus has been directed at the simultaneous inclusion and prediction of protein backbone and sidechain structure information.

Distribution-Free, Risk-Controlling Prediction Sets

aangelopoulos/rcps 7 Jan 2021

While improving prediction accuracy has been the focus of machine learning in recent years, this alone does not suffice for reliable decision-making.

ProteinNet: a standardized data set for machine learning of protein structure

EricAlcaide/MiniFold 1 Feb 2019

We have created the ProteinNet series of data sets to provide a standardized mechanism for training and assessing data-driven models of protein sequence-structure relationships.

Iterative SE(3)-Transformers

FabianFuchsML/se3-transformer-public 26 Feb 2021

Motivated by this application, we implement an iterative version of the SE(3)-Transformer, an SE(3)-equivariant attention-based model for graph data.

PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction

mindspore-ai/mindscience 24 Jun 2022

We provide in addition the benchmark training procedure for SOTA protein structure prediction model on this dataset.

Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure Prediction

mindspore-ai/mindscience 20 Aug 2022

Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and medical development.