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8/26/2015 12:03:00 PM | Browse: 1130 | Download: 1556
Publication Name World Journal of Medical Genetics
Manuscript ID 17298
Country/Territory United Kingdom
Received
2015-02-28 10:04
Peer-Review Started
2015-03-02 19:04
To Make the First Decision
2015-04-27 15:40
Return for Revision
2015-04-28 15:02
Revised
2015-04-28 17:44
Second Decision
2015-05-07 09:56
Accepted by Journal Editor-in-Chief
2015-05-07 18:00
Accepted by Company Editor-in-Chief
2015-05-18 17:04
Articles in Press
2015-05-18 17:04
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2015-08-19 09:08
Publish the Manuscript Online
2015-08-26 12:03
ISSN 2220-3184 (online)
Open Access This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Copyright © The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Genetics & Heredity
Manuscript Type Editorial
Article Title Value of predictive bioinformatics in inherited metabolic diseases
Manuscript Source Invited Manuscript
All Author List David J Timson
Funding Agency and Grant Number
Corresponding Author Dr. David J Timson, School of Biological Sciences and Institute for Global Food Security, Queen’s University Belfast, 97 Lisburn Road, BT9 7BL Belfast, United Kingdom. d.timson@qub.ac.uk
Key Words Genetic disease; Metabolism; In silico method; Protein stability; Disease-associated mutation
Core Tip Bioinformatics and other in silico methods are increasingly being used to predict the severity of disease-associated mutations in inherited metabolic diseases. In general, severity correlates with altered protein stability and the best predictions occur when a variety of tools are applied.
Publish Date 2015-08-26 12:03
Citation Timson DJ. Value of predictive bioinformatics in inherited metabolic diseases. World J Med Genet 2015; 5(3): 46-51
URL http://www.wjgnet.com/2220-3184/full/v5/i3/46.htm
DOI http://dx.doi.org/10.5496/wjmg.v5.i3.46
Full Article (PDF) WJMG-5-46.pdf
Full Article (Word) WJMG-5-46.doc
Manuscript File 17298-Review.docx
Answering Reviewers 17298-Answering reviewers.pdf
Audio Core Tip 17298-Audio core tip.wav
Conflict-of-Interest Disclosure Form 17298-Conflict-of-interest statement.pdf
Copyright License Agreement 17298-Copyright assignment.pdf
Peer-review Report 17298-Peer-review(s).pdf
Journal Editor-in-Chief Review Report 17298-Journal editor-in-chief review report.pdf
Scientific Misconduct Check 17298-Scientific misconduct check.pdf
Scientific Editor Work List 17298-Scientific editor work list.pdf