Shahid Ullah, Tianshun Gao, W. Rahman, F. Ullah, R. Jahan, Anees Ullah, Gulzar Ahmad, Muhammad Ijaz, Yihang Pan
{"title":"LDBPR: Latest Database of Protein Research","authors":"Shahid Ullah, Tianshun Gao, W. Rahman, F. Ullah, R. Jahan, Anees Ullah, Gulzar Ahmad, Muhammad Ijaz, Yihang Pan","doi":"10.26502/jbsb.5107032","DOIUrl":null,"url":null,"abstract":"With the vast and rapid growth of protein research data, a large number of databases are produced to annotate proteins. How to use these databases is becoming a crucial part of modern biology. Database research is usually the first step in the analysis of a new protein. The combined utilization of multiple databases could help researchers to understand the evolution, structure, and function of proteins. Therefore, a well comprehensive and large-scale resource integrated with most of databases is urgently desirable for systematic and precise studies of proteins. Here we designed a platform LDBPR with a collection of 564 latest scientific protein databases. It fully covered physical, chemical, and biological information of Protein sequence, structure, and model, domain, function, and protein‐ protein interactions. Furthermore, The LDBPR can be explored by three ways: (i) single database can be browsed by typing the name in the given search bar; (ii) all protein categories can be browsed by clicking on the name of the category; (iii) the image icon, could give all categorized protein databases on single click. Moreover, the programming languages including PHP, HTML, CSS, and MySQL were used to construct LDBPR for the protein scientific community that can be freely searched by clicking http://www.habdsk.org/ldbpr.php and will be updated timely.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of bioinformatics and systems biology : Open access","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26502/jbsb.5107032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the vast and rapid growth of protein research data, a large number of databases are produced to annotate proteins. How to use these databases is becoming a crucial part of modern biology. Database research is usually the first step in the analysis of a new protein. The combined utilization of multiple databases could help researchers to understand the evolution, structure, and function of proteins. Therefore, a well comprehensive and large-scale resource integrated with most of databases is urgently desirable for systematic and precise studies of proteins. Here we designed a platform LDBPR with a collection of 564 latest scientific protein databases. It fully covered physical, chemical, and biological information of Protein sequence, structure, and model, domain, function, and protein‐ protein interactions. Furthermore, The LDBPR can be explored by three ways: (i) single database can be browsed by typing the name in the given search bar; (ii) all protein categories can be browsed by clicking on the name of the category; (iii) the image icon, could give all categorized protein databases on single click. Moreover, the programming languages including PHP, HTML, CSS, and MySQL were used to construct LDBPR for the protein scientific community that can be freely searched by clicking http://www.habdsk.org/ldbpr.php and will be updated timely.