Search anything and hit enter
  • Teams
  • Members
  • Projects
  • Events
  • Calls
  • Jobs
  • publications
  • Software
  • Tools
  • Network
  • Equipment

A little guide for advanced search:

  • Tip 1. You can use quotes "" to search for an exact expression.
    Example: "cell division"
  • Tip 2. You can use + symbol to restrict results containing all words.
    Example: +cell +stem
  • Tip 3. You can use + and - symbols to force inclusion or exclusion of specific words.
    Example: +cell -stem
e.g. searching for members in projects tagged cancer
Search for
Count
IN
OUT
Content 1
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinical Research Nurse
  • Clinician Researcher
  • Department Manager
  • Dual-education Student
  • Full Professor
  • Honorary Professor
  • Lab assistant
  • Master Student
  • Non-permanent Researcher
  • Nursing Staff
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Prize
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Content 2
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinical Research Nurse
  • Clinician Researcher
  • Department Manager
  • Dual-education Student
  • Full Professor
  • Honorary Professor
  • Lab assistant
  • Master Student
  • Non-permanent Researcher
  • Nursing Staff
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Prize
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Search

← Go to Research

Go back
Scroll to top
Share
© Research
Publication : Proceedings of the National Academy of Sciences of the United States of America

The human gene connectome as a map of short cuts for morbid allele discovery

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Proceedings of the National Academy of Sciences of the United States of America - 18 Mar 2013

Itan Y, Zhang SY, Vogt G, Abhyankar A, Herman M, Nitschke P, Fried D, Quintana-Murci L, Abel L, Casanova JL

Link to Pubmed [PMID] – 23509278

Proc. Natl. Acad. Sci. U.S.A. 2013 Apr;110(14):5558-63

High-throughput genomic data reveal thousands of gene variants per patient, and it is often difficult to determine which of these variants underlies disease in a given individual. However, at the population level, there may be some degree of phenotypic homogeneity, with alterations of specific physiological pathways underlying the pathogenesis of a particular disease. We describe here the human gene connectome (HGC) as a unique approach for human mendelian genetic research, facilitating the interpretation of abundant genetic data from patients with the same disease, and guiding subsequent experimental investigations. We first defined the set of the shortest plausible biological distances, routes, and degrees of separation between all pairs of human genes by applying a shortest distance algorithm to the full human gene network. We then designed a hypothesis-driven application of the HGC, in which we generated a Toll-like receptor 3-specific connectome useful for the genetic dissection of inborn errors of Toll-like receptor 3 immunity. In addition, we developed a functional genomic alignment approach from the HGC. In functional genomic alignment, the genes are clustered according to biological distance (rather than the traditional molecular evolutionary genetic distance), as estimated from the HGC. Finally, we compared the HGC with three state-of-the-art methods: String, FunCoup, and HumanNet. We demonstrated that the existing methods are more suitable for polygenic studies, whereas HGC approaches are more suitable for monogenic studies. The HGC and functional genomic alignment data and computer programs are freely available to noncommercial users from http://lab.rockefeller.edu/casanova/HGC and should facilitate the genome-wide selection of disease-causing candidate alleles for experimental validation.