ArticleBMC bioinformatics2009
Protein comparison at the domain architecture level.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 37 citations in OpenAlex.
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- Genome-guided analysis allows the identification of novel physiological traits in Trichococcus species.BMC genomics · 2020Article
- The protein architecture in Bacteria and Archaea identifies a set of promiscuous and ancient domains.PloS one · 2019Article
- In silico comparative analysis of GGDEF and EAL domain signaling proteins from the Azospirillum genomes.BMC microbiology · 2018Article
- Abundance, diversity and domain architecture variability in prokaryotic DNA-binding transcription factors.PloS one · 2018Article
- Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data.Scientific reports · 2016Article
- UniProt-DAAC: domain architecture alignment and classification, a new method for automatic functional annotation in UniProtKB.Bioinformatics (Oxford, England) · 2016Article
- Protein domain architectures provide a fast, efficient and scalable alternative to sequence-based methods for comparative functional genomics.F1000Research · 2016Article
- Comparative genome analysis of Weissella ceti, an emerging pathogen of farm-raised rainbow trout.BMC genomics · 2015Article
- Assessing the Metabolic Diversity of Streptococcus from a Protein Domain Point of View.PloS one · 2015Article
- Analysis of the protein domain and domain architecture content in fungi and its application in the search of new antifungal targets.PLoS computational biology · 2014Article
- An alignment-free domain architecture similarity search (ADASS) algorithm for inferring homology between multi-domain proteins.Bioinformation · 2013Article
- Multiple graph regularized protein domain ranking.BMC bioinformatics · 2012Article
- ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval.BMC bioinformatics · 2012Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe general method used to determine the function of newly discovered proteins is to transfer annotations from well-characterized homologous proteins. The process of selecting homologous proteins can largely be classified into sequence-based and domain-based approaches. Domain-based methods have several advantages for identifying distant homology and homology among proteins with multiple domains, as compared to sequence-based methods. However, these methods are challenged by large families defined by 'promiscuous' (or 'mobile') domains.
resultsHere we present a measure, called Weighed Domain Architecture Comparison (WDAC), of domain architecture similarity, which can be used to identify homolog of multidomain proteins. To distinguish these promiscuous domains from conventional protein domains, we assigned a weight score to Pfam domain extracted from RefSeq proteins, based on its abundance and versatility. To measure the similarity of two domain architectures, cosine similarity (a similarity measure used in information retrieval) is used. We combined sequence similarity with domain architecture comparisons to identify proteins belonging to the same domain architecture. Using human and nematode proteomes, we compared WDAC with an unweighted domain architecture method (DAC) to evaluate the effectiveness of domain weight scores. We found that WDAC is better at identifying homology among multidomain proteins.
conclusionOur analysis indicates that considering domain weight scores in domain architecture comparisons improves protein homology identification. We developed a web-based server to allow users to compare their proteins with protein domain architectures.
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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.