LIPOPREDICT: Bacterial lipoprotein prediction server

Autor:	S. Ramya Kumari, V. K. Jayaraman, Kiran Kadam, Ritesh Badwaik
Jazyk:	angličtina
Rok vydání:	2012
Předmět:	Bacterial lipoproteins Sequence model Computer science Computational biology General Medicine computer.software_genre compositional features Bacterial lipoprotein Support vector machine Dipeptide composition Server Data mining prediction server computer Support Vector Machine (SVM)
Zdroj:	Bioinformation
ISSN:	0973-2063 0973-8894
Popis:	Bacterial lipoproteins have many important functions owing to their essential nature and roles in pathogenesis and represent a class of possible vaccine candidates. The prediction of bacterial lipoproteins from sequence is thus an important task for computational vaccinology. A Support Vector Machines (SVM) based module for predicting bacterial lipoproteins, LIPOPREDICT, has been developed. The best performing sequence model were generated using selected dipeptide composition, which gave 97% accuracy of prediction. The results obtained were compared very well with those of previously developed methods. Availability The database is available for free at www.lipopredict.cdac.in
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10c95f9062512735390629d7544b4e43 http://europepmc.org/articles/PMC3346017 Zobrazit plný text záznamu