Special Feature

User Panel

My Panel

My Panel

Bookmark Science Articles

Recent News
Bookmark / Share This Science Site

Predicting disulfide bond connectivity in proteins by correlated mutations analysis.

Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

  • Abstract Text of This Paper
  • Journal Published
  • MeSH Keywords of This Abstract
  • Chemicals and Substances Used in this Paper
  • Grants and Granting Agency of this Research
  • Database Accession Numbers Used in this Paper
  • Related Papers
  • Related Research Tags
  • Rate this Research Paper
  • Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Abstract Text:

    rotem rubinsteinRotem Rubinstein,andras fiserAndras Fiser,

    Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Publishing Authors By Initials

    r rubinsteinR Rubinstein,a fiserA Fiser,

    For similar abstracts research abstracts see: abstracts research

    PUBMED ID PMID:

    MEDLINE DATE:

    Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Journal Published:

    PUBLICATION TYPE: Research Support, U.S. Gov't,

    Journal: Bioinformatics (Oxford, England)

    VOLUME: 24

    Page Numbers: 498-504

    Journal Abbreviation:

    ISSN: 1460-2059

    DAY: 18

    MONTH: 01

    YEAR: 2008

    Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 9808944

    Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Keywords Mesh Terms:

    KEYWORDS:

    MESH TERMS:

    Chemical & Substance for Abstract: Predicting disulfide bond connectivity in proteins by correlated mutations analysis. Information

    Substance Name:

    Registry Number:

    Grant and Affiliation Information for Predicting disulfide bond connectivity in proteins by correlated mutations analysis.

    AFFILIATION:

    Country: England

    England Research PublicationEngland Research Publication

    AGENCY:

    GRANT:

    ACRONYM:

    MEDLINETA: Bioinformatics

    REFSOURCE:

    DATABASENAME:

    ACCESSION NUMBER:

    Number Hits: 0

    Predicting disulfide bond connectivity in proteins by correlated mutations analysis Related Publications

     

    Molecular Station USER Menu

    Welcome to Molecular Station!

    You have to register before you can post on our forums or use our advanced features. Register Now! Its Free and Fast!

    Already registered? Login now below.

    User Name:

    Password:

    Already registered and Forgot your password? Click below to recover it.

    Recover Lost Password

    Join now - it's fast and free!

    Molecular Station is THE largest network of researchers, scientists and science lovers anywhere!

    Research Terms of Usage and Disclaimer
    Home
    Features

    Protocols

    DNA Forum

    Science Forum

    DNA Forum
    Biology Forum

    Science News


    [CaRP] XML error: Invalid document end at line 2

    For more click here:Science News