A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
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Updated
Jun 10, 2024 - Jupyter Notebook
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding
Protein function prediction using a variational autoencoder
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
A package to annotate protein sequences
SaprotHub: Making Protein Modeling Accessible to All Biologists
DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction
Deep Critical Learning. Implementation of ProSelfLC, IMAE, DM, etc.
Pipeline for searching and aligning contact maps for proteins, then running DeepFri's GCN.
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).
Domain-PFP is a self-supervised method to predict protein functions from the domains
Multi-label protein function annotation
Protein function prediction based on protein-protein interaction network topology and deep maxout neural networks
PrimaryOdors.org molecular docker.
molecular graph representation
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 through latent tensor reconstruction
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