ArticleBioinformatics (Oxford, England)2009
ESG: extended similarity group method for automated protein function prediction.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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60 citing papers in PubMed.
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- Advancing generative large language models toward discriminative performance in protein function prediction.Genome biology · 2026Article
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- Translating a GO Term List to Human Readable Function Description Using GO2Sum.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Proteomic changes orchestrate metabolic acclimation of a unicellular diazotrophic cyanobacterium during light-dark cycle and nitrogen fixation states.bioRxiv : the preprint server for biology · 2024Article
- Proteomic analysis of unicellular cyanobacteriumbioRxiv : the preprint server for biology · 2024Article
- GO2Sum: generating human-readable functional summary of proteins from GO terms.NPJ systems biology and applications · 2024Article
- Chromosome level genome assembly of the Etruscan shrew Suncus etruscus.Scientific data · 2024Article
- Iron transport pathways in the human malaria parasiteFrontiers in cellular and infection microbiology · 2024Article
- Domain-PFP allows protein function prediction using function-aware domain embedding representations.Communications biology · 2023Article
- Domain-PFP: Protein Function Prediction Using Function-Aware Domain Embedding Representations.bioRxiv : the preprint server for biology · 2023Article
- Machine learning for the identification of respiratory viral attachment machinery from sequences data.PloS one · 2023Article
- Targeting Essential Hypothetical Proteins ofBioMed research international · 2023Article
- ContactPFP: Protein function prediction using predicted contact information.Frontiers in bioinformatics · 2022Article
- Graph2GO: a multi-modal attributed network embedding method for inferring protein functions.GigaScience · 2020Article
- Pseudo2GO: A Graph-Based Deep Learning Method for Pseudogene Function Prediction by Borrowing Information From Coding Genes.Frontiers in genetics · 2020Article
- Prediction of protein group function by iterative classification on functional relevance network.Bioinformatics (Oxford, England) · 2019Article
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- Progression of the canonical reference malaria parasite genome from 2002-2019.Wellcome open research · 2019Article
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4 authors.
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Abstract
motivationImportance of accurate automatic protein function prediction is ever increasing in the face of a large number of newly sequenced genomes and proteomics data that are awaiting biological interpretation. Conventional methods have focused on high sequence similarity-based annotation transfer which relies on the concept of homology. However, many cases have been reported that simple transfer of function from top hits of a homology search causes erroneous annotation. New methods are required to handle the sequence similarity in a more robust way to combine together signals from strongly and weakly similar proteins for effectively predicting function for unknown proteins with high reliability.
resultsWe present the extended similarity group (ESG) method, which performs iterative sequence database searches and annotates a query sequence with Gene Ontology terms. Each annotation is assigned with probability based on its relative similarity score with the multiple-level neighbors in the protein similarity graph. We will depict how the statistical framework of ESG improves the prediction accuracy by iteratively taking into account the neighborhood of query protein in the sequence similarity space. ESG outperforms conventional PSI-BLAST and the protein function prediction (PFP) algorithm. It is found that the iterative search is effective in capturing multiple-domains in a query protein, enabling accurately predicting several functions which originate from different domains. AVAILABILITY: ESG web server is available for automated protein function prediction at http://dragon.bio.purdue.edu/ESG/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.