A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding

A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design

Protein function prediction using a variational autoencoder

SaprotHub: Making Protein Modeling Accessible to All Biologists

A package to annotate protein sequences

DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction

Pipeline for searching and aligning contact maps for proteins, then running DeepFri's GCN.

Deep Critical Learning. Implementation of ProSelfLC, IMAE, DM, etc.

Feature map and function annotation of Proteins

Improving protein function prediction with synthetic feature samples created by generative adversarial networks

Benchmarking uncertainty quantification methods on proteins.

Epistatic Net is an algorithm which allows for spectral regularization of deep neural networks to predict biological fitness functions (e.g., protein functions).

A Deep Learning Toolkit for Protein Property Prediction, Localization Prediction, Protein-Protein Interaction, antigen epitope prediction, antibody paratope prediction, antibody developability prediction, etc. [NeurIPS 2024 AIDrugX Spotlight]

Domain-PFP is a self-supervised method to predict protein functions from the domains

Multi-label protein function annotation

Assigns short human readable descriptions to biological sequences or gene families using references. For this, prot-scriber consumes sequence similarity search results in tabular format (Blast or Diamond).

Protein function prediction based on protein-protein interaction network topology and deep maxout neural networks

PrimaryOdors.org molecular docker.

protein graph representation