Close
Help




JOURNAL

Cancer Informatics

Network Analysis of Circular Permutations in Multidomain Proteins Reveals Functional Linkages for Uncharacterized Proteins

Submit a Paper


Cancer Informatics 2014:Suppl. 5 109-124

Methodology

Published on 19 Feb 2015

DOI: 10.4137/CIN.S14059


Further metadata provided in PDF



Sign up for email alerts to receive notifications of new articles published in Cancer Informatics

Abstract

Various studies have implicated different multidomain proteins in cancer. However, there has been little or no detailed study on the role of circular multidomain proteins in the general problem of cancer or on specific cancer types. This work represents an initial attempt at investigating the potential for predicting linkages between known cancer-associated proteins with uncharacterized or hypothetical multidomain proteins, based primarily on circular permutation (CP) relationships. First, we propose an efficient algorithm for rapid identification of both exact and approximate CPs in multidomain proteins. Using the circular relations identified, we construct networks between multidomain proteins, based on which we perform functional annotation of multidomain proteins. We then extend the method to construct subnetworks for selected cancer subtypes, and performed prediction of potential link-ages between uncharacterized multidomain proteins and the selected cancer types. We include practical results showing the performance of the proposed methods.



Downloads

PDF  (14.96 MB PDF FORMAT)

RIS citation   (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)

Supplementary Files 1  (6.16 MB ZIP FORMAT)

BibTex citation   (BIBDESK, LATEX)

XML

PMC HTML


Sharing


What Your Colleagues Say About Cancer Informatics
This is the first time for us to submit a manuscript to Cancer Informatics.  We thank the peer reviewers for their insightful comments, which have improved our manuscript markedly. We were pleased to find that the staff were extremely helpful and kept us informed of the progress of the submission step-by-step. Our experience with Cancer Informatics has been tremendous. Thank you very much!
Dr Yirong Wu (University of Wisconsin, Madison, WI, USA)
More Testimonials

Quick Links


New article and journal news notification services
Email Alerts RSS Feeds
Facebook Google+ Twitter
Pinterest Tumblr YouTube