There are 11 repositories under protein-function-prediction topic.
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
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.
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
PrimaryOdors.org molecular docker.
Protein function prediction based on protein-protein interaction network topology and deep maxout neural networks
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
python package to encode protein using different methods for machine learning
This repository contains the FPredX models for the prediction of excitation maximum, emission maximum, brightness and oligomeric state of fluorescent proteins.
Classification of protein function based on their sequences with Artificial Neural Networks
Predicting protein functions using positive-unlabeled ranking with ontology-based priors
A nextflow pipeline to cluster sets of proteins.
Integrating multimodal data through heterogeneous ensembles
Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations"
A Python tool for predicting protein functions by associating domains with Gene Ontology terms using existing domain and GO annotation data
🌱🌟 My Personal Portfolio 🌟🌱
Pipeline for searching and aligning contact maps for proteins, then running DeepFri's GCN. This repository is for portfolio purposes only. For currently maintained version go to Małopolskie Centrum Biotechnologii repository - https://github.com/bioinf-mcb/Metagenomic-DeepFRI
Developing assembled functional classifications models via optimized machine learning algorithms
An efficient attention-based approach for Protein Function Prediction using skip-gram features. Proposing two novel approaches, namely, OntoPred and OntoPredPlus capable to annotate protein sequences accurately.
Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required.we expect to create an accurate prediction model that assigns the best sub-graph of the gene ontology to each new protein and output a prediction score for this sub-graph and/or each predicted term .
🧬Protein Functions Prediction through Amino Acids Sequences🧬