title: CytoPred: a server for prediction and classification of cytokines.
abstract: Cytokines are messengers of immune system. They are small secreted proteins that mediate and regulate the immune system, inflammation and hematopoiesis. Recent studies have revealed important roles played by the cytokines in adjuvants as therapeutic targets and in cancer therapy. In this paper, an attempt has been made to predict this important class of proteins and classify further them into families and subfamilies. A PSI-BLAST+Support Vector Machine-based hybrid approach is adopted to develop the prediction methods. CytoPred is capable of predicting cytokines with an accuracy of 98.29%. The overall accuracy of classification of cytokines into four families and further classification into seven subfamilies is 99.77 and 97.24%, respectively. It has been shown by comparison that CytoPred performs better than the already existing CTKPred. A user-friendly server CytoPred has been developed and available at http://www.imtech.res.in/raghava/cytopred.
authors.affiliation: Bioinformatics Centre, Institute of Microbial Technology, Chandigarh, India.
authors.forename: Sneh
authors.initials: S
authors.lastname: Lata
authors.forename: G P S
authors.initials: GP
authors.lastname: Raghava
mesh_terms: D016207:Cytokines / Q000145:classification* / Q000378:metabolism; D020407:Internet; D008954:Models, Biological; D012680:Sensitivity and Specificity; D012984:Software
chemical_list: D016207:Cytokines