{"title":"Proteins involved in more domain types tend to be more essential.","authors":"Lu Chen, Yingjiao Cheng, Min Li, Jianxin Wang","doi":"10.1504/IJBRA.2015.068086","DOIUrl":null,"url":null,"abstract":"<p><p>Investigation of essential proteins is significantly valuable for understanding of cellular life, drug design and other practical purposes. In most of current studies, essential proteins are generally mined in protein-protein interaction (PPI) networks with diverse topology features. In this study, we investigate what kind of proteins is inclined to be essential from a new perspective. The investigation implies that protein essentiality is correlated with protein domains, which are functional, structural and evolutionary units of proteins. Proteins with a larger Number of Domain Types (NDT) tend to be essential. The analyses on 22 species show that essential proteins identified by NDT are much more than those identified by ten random identifications. The consideration of the structural feature makes us less dependent on network data and thus enables us to investigate protein essentiality of more species with incomplete and/or inconsistent network data. </p>","PeriodicalId":35444,"journal":{"name":"International Journal of Bioinformatics Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJBRA.2015.068086","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Bioinformatics Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBRA.2015.068086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 4
Abstract
Investigation of essential proteins is significantly valuable for understanding of cellular life, drug design and other practical purposes. In most of current studies, essential proteins are generally mined in protein-protein interaction (PPI) networks with diverse topology features. In this study, we investigate what kind of proteins is inclined to be essential from a new perspective. The investigation implies that protein essentiality is correlated with protein domains, which are functional, structural and evolutionary units of proteins. Proteins with a larger Number of Domain Types (NDT) tend to be essential. The analyses on 22 species show that essential proteins identified by NDT are much more than those identified by ten random identifications. The consideration of the structural feature makes us less dependent on network data and thus enables us to investigate protein essentiality of more species with incomplete and/or inconsistent network data.
期刊介绍:
Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.