Literature DB >> 18287174

CytoPred: a server for prediction and classification of cytokines.

Sneh Lata1, G P S Raghava.   

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.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18287174     DOI: 10.1093/protein/gzn006

Source DB:  PubMed          Journal:  Protein Eng Des Sel        ISSN: 1741-0126            Impact factor:   1.650


  3 in total

1.  An approach for identifying cytokines based on a novel ensemble classifier.

Authors:  Quan Zou; Zhen Wang; Xinjun Guan; Bin Liu; Yunfeng Wu; Ziyu Lin
Journal:  Biomed Res Int       Date:  2013-08-21       Impact factor: 3.411

2.  TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings.

Authors:  Trinh-Trung-Duong Nguyen; Nguyen-Quoc-Khanh Le; Quang-Thai Ho; Dinh-Van Phan; Yu-Yen Ou
Journal:  BMC Med Genomics       Date:  2020-10-22       Impact factor: 3.063

3.  Augmented Innate and Adaptive Immune Responses Under Conditions of Diabetes-Filariasis Comorbidity.

Authors:  Joy Manohar Sibi; Viswanathan Mohan; Saravanan Munisankar; Subash Babu; Vivekanandhan Aravindhan
Journal:  Front Immunol       Date:  2021-09-10       Impact factor: 7.561

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.