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Neural Network and Random Forest Models in Protein Function Prediction

https://doi.org/10.1109/tcbb.2020.3044230

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Evolving Regular Expression-Based Sequence Classifiers for Protein Nuclear Localisation

inferredcites →https://doi.org/10.1007/s00726-015-2049-3openalex-snapshot

Protein function prediction using guilty by association from interaction networks

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GoFDR: A sequence alignment based method for predicting protein functions

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Selection of relevant features and examples in machine learning

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Basic Local Alignment Search Tool

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Favorable domain size in proteins

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Gene Ontology: tool for the unification of biology

inferredcites →https://doi.org/10.1038/nmeth.2340openalex-snapshot

A large-scale evaluation of computational protein function prediction

inferredcites →https://doi.org/10.1038/s41598-018-24760-xopenalex-snapshot

Computational Protein Design with Deep Learning Neural Networks

inferredcites →https://doi.org/10.1038/srep18962openalex-snapshot

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

inferredcites →https://doi.org/10.1073/pnas.89.22.10915openalex-snapshot

Amino acid substitution matrices from protein blocks.

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Profile hidden Markov models.

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Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation

inferredcites →https://doi.org/10.1093/bioinformatics/bti130openalex-snapshot

NetAcet: prediction of N-terminal acetylation sites

inferredcites →https://doi.org/10.1093/bioinformatics/bti721openalex-snapshot

Prediction of protein–protein interactions using random decision forest framework

inferredcites →https://doi.org/10.1093/bioinformatics/btu031openalex-snapshot

InterProScan 5: genome-scale protein function classification

inferredcites →https://doi.org/10.1093/bioinformatics/btu851openalex-snapshot

PANNZER: high-throughput functional annotation of uncharacterized proteins in an error-prone environment

inferredcites →https://doi.org/10.1093/bioinformatics/btv345openalex-snapshot

ProFET: Feature engineering captures high-level protein functions

inferredcites →https://doi.org/10.1093/bioinformatics/btw255openalex-snapshot

Convolutional neural network architectures for predicting DNA–protein binding

inferredcites →https://doi.org/10.1093/bioinformatics/btx624openalex-snapshot

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

inferredcites →https://doi.org/10.1093/bioinformatics/btx780openalex-snapshot

DeepSF: deep convolutional neural network for mapping protein sequences to folds

inferredcites →https://doi.org/10.1093/bioinformatics/bty130openalex-snapshot

GOLabeler: improving sequence-based large-scale protein function prediction by learning to rank

inferredcites →https://doi.org/10.1093/nar/25.17.3389openalex-snapshot

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

inferredcites →https://doi.org/10.1093/nar/gkm998openalex-snapshot

AAindex: amino acid index database, progress report 2008

inferredcites →https://doi.org/10.1093/nar/gkr1178openalex-snapshot

The NCBI Taxonomy database

inferredcites →https://doi.org/10.1093/nar/gku1003openalex-snapshot

STRING v10: protein–protein interaction networks, integrated over the tree of life

inferredcites →https://doi.org/10.1093/nar/gkw1099openalex-snapshot

UniProt: the universal protein knowledgebase

inferredcites →https://doi.org/10.1093/nar/gkw1129openalex-snapshot

CDD/SPARCLE: functional classification of proteins via subfamily domain architectures

inferredcites →https://doi.org/10.1093/nar/gky1055openalex-snapshot

The Gene Ontology Resource: 20 years and still GOing strong

inferredcites →https://doi.org/10.1093/nar/gky1100openalex-snapshot

InterPro in 2019: improving coverage, classification and access to protein sequence annotations

inferredcites →https://doi.org/10.1109/cvpr.2019.00277openalex-snapshot

Do Better ImageNet Models Transfer Better?

inferredcites →https://doi.org/10.1109/icbbe.2009.5162790openalex-snapshot

Enzyme Function Classification Using Protein Sequence Features and Random Forest

inferredcites →https://doi.org/10.1142/9789812776303_0056openalex-snapshot

SEMANTIC SIMILARITY MEASURES AS TOOLS FOR EXPLORING THE GENE ONTOLOGY

inferredcites →https://doi.org/10.1145/1854776.1854797openalex-snapshot

Random forest-based prediction of protein sumoylation sites from sequence features

inferredcites →https://doi.org/10.1146/annurev.biochem.70.1.209openalex-snapshot

Divergent Evolution of Enzymatic Function: Mechanistically Diverse Superfamilies and Functionally Distinct Suprafamilies

inferredcites →https://doi.org/10.1186/1471-2105-10-421openalex-snapshot

BLAST+: architecture and applications

inferredcites →https://doi.org/10.1186/1471-2105-11-364openalex-snapshot

Automatic structure classification of small proteins using random forest

inferredcites →https://doi.org/10.1186/1471-2105-13-s4-s14openalex-snapshot

Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms

inferredcites →https://doi.org/10.1186/1471-2105-14-s3-s1openalex-snapshot

Protein function prediction by massive integration of evolutionary analyses and multiple data sources

inferredcites →https://doi.org/10.1186/1471-2105-15-s11-s14openalex-snapshot

Improving protein fold recognition by random forest

inferredcites →https://doi.org/10.1186/1471-2105-9-392openalex-snapshot

PredGPI: a GPI-anchor predictor

inferredcites →https://doi.org/10.1186/1745-6150-7-12openalex-snapshot

Domain enhanced lookup time accelerated BLAST

inferredcites →https://doi.org/10.1186/s13059-016-1037-6openalex-snapshot

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

inferredcites →https://doi.org/10.1186/s13059-019-1835-8openalex-snapshot

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

inferredcites →https://doi.org/10.1371/journal.pone.0178832openalex-snapshot

Predicting human protein subcellular localization by heterogeneous and comprehensive approaches

inferredcites →https://doi.org/10.1371/journal.pone.0198216openalex-snapshot

Predicting human protein function with multi-task deep neural networks

inferredcites →https://doi.org/10.3390/molecules22101732openalex-snapshot

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network

inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-snapshot

AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale

inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot

Scikit-learn: Machine Learning in Python

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A systematic review of state-of-the-art strategies for machine learning-based protein function prediction

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What Kinds of Machine Learning Models Might Guide the Design of Biomedical Nanomaterials?

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Evaluating the evolutionary relationship of TATA binding protein (TBP) with various folding patterns of protein domains using support vector machine (SVM)

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Elucidating the functional roles of prokaryotic proteins using big data and artificial intelligence

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SERF , a family of tiny highly conserved, highly charged proteins with enigmatic functions

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A Multiscale Attention Network for the Classification of Lightning Safety Risk Warnings

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SDN2GO: An Integrated Deep Learning Model for Protein Function Prediction

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Peer Review #2 of "Detection of spreader nodes in human-SARS-CoV protein-protein interaction network (v0.1)"

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Peer Review #3 of "Detection of spreader nodes in human-SARS-CoV protein-protein interaction network (v0.1)"

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Peer Review #2 of "Detection of spreader nodes in human-SARS-CoV protein-protein interaction network (v0.2)"

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Peer Review #3 of "Detection of spreader nodes in human-SARS-CoV protein-protein interaction network (v0.2)"

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Detection of spreader nodes in human-SARS-CoV protein-protein interaction network

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