Symptom-driven idiopathic disease gene identification

Bhuvan Molparia; Phillip H. Pham; Ali Torkamani

doi:10.1038/gim.2014.202

Symptom-driven idiopathic disease gene identification

Genetics in Medicine ◽

10.1038/gim.2014.202 ◽

2015 ◽

Vol 17 (11) ◽

pp. 859-865 ◽

Cited By ~ 1

Author(s):

Bhuvan Molparia ◽

Phillip H. Pham ◽

Ali Torkamani

Keyword(s):

Disease Gene ◽

Gene Identification ◽

Idiopathic Disease

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Human Gene Mapping and Disease Gene Identification

Thompson &amp Thompson Genetics in Medicine ◽

10.1016/b978-1-4160-3080-5.50012-2 ◽

2007 ◽

pp. 207-230

Author(s):

Robert L. Nussbaum ◽

Roderick R. McInnes ◽

Huntington F. Willard ◽

Ada Hamosh

Keyword(s):

Gene Mapping ◽

Disease Gene ◽

Human Gene ◽

Gene Identification ◽

Human Gene Mapping

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Use of Congenic Mouse Strains for Candidate Disease Gene Identification in Complex Traits

Sourcebook of Models for Biomedical Research ◽

10.1007/978-1-59745-285-4_59 ◽

2008 ◽

pp. 575-581

Author(s):

Ute Christine Rogner ◽

Philip Avner

Keyword(s):

Complex Traits ◽

Disease Gene ◽

Congenic Mouse ◽

Gene Identification ◽

Mouse Strains ◽

Candidate Disease Gene ◽

Congenic Mouse Strains

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Evaluating the Role of MAST1 as an Intellectual Disability Disease Gene: Identification of a Novel De Novo Variant in a Patient with Developmental Disabilities

Journal of Molecular Neuroscience ◽

10.1007/s12031-019-01415-8 ◽

2019 ◽

Vol 70 (3) ◽

pp. 320-327 ◽

Cited By ~ 3

Author(s):

Afif Ben-Mahmoud ◽

Aisha M. Al-Shamsi ◽

Bassam R. Ali ◽

Lihadh Al-Gazali

Keyword(s):

Intellectual Disability ◽

Developmental Disabilities ◽

Disease Gene ◽

De Novo ◽

Gene Identification ◽

De Novo Variant

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Disease gene identification by using graph kernels and Markov random fields

Science China Life Sciences ◽

10.1007/s11427-014-4745-8 ◽

2014 ◽

Vol 57 (11) ◽

pp. 1054-1063 ◽

Cited By ~ 24

Author(s):

BoLin Chen ◽

Min Li ◽

JianXin Wang ◽

Fang-Xiang Wu

Keyword(s):

Random Fields ◽

Markov Random Fields ◽

Disease Gene ◽

Gene Identification ◽

Graph Kernels ◽

Markov Random

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New Tools for Mendelian Disease Gene Identification: PhenoDB Variant Analysis Module; and GeneMatcher, a Web-Based Tool for Linking Investigators with an Interest in the Same Gene

Human Mutation ◽

10.1002/humu.22769 ◽

2015 ◽

Vol 36 (4) ◽

pp. 425-431 ◽

Cited By ~ 86

Author(s):

Nara Sobreira ◽

François Schiettecatte ◽

Corinne Boehm ◽

David Valle ◽

Ada Hamosh

Keyword(s):

Disease Gene ◽

Gene Identification ◽

Mendelian Disease ◽

Web Based ◽

Variant Analysis

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Prediction and experimental validation of osteoporosis susceptibility genes by computational disease gene identification strategy

Bone ◽

10.1016/j.bone.2008.08.021 ◽

2008 ◽

Vol 43 ◽

pp. S44-S45

Author(s):

Qingyang Huang ◽

Li Gloria H.Y. Li ◽

Annie W.C. Kung

Keyword(s):

Experimental Validation ◽

Disease Gene ◽

Susceptibility Genes ◽

Gene Identification ◽

Identification Strategy

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SCO-ping Out the Mechanisms Underlying the Etiology of Hydrocephalus

Physiology ◽

10.1152/physiol.00039.2008 ◽

2009 ◽

Vol 24 (2) ◽

pp. 117-126 ◽

Cited By ~ 34

Author(s):

Michael S. Huh ◽

Matthew A. M. Todd ◽

David J. Picketts

Keyword(s):

Disease Gene ◽

Subcommissural Organ ◽

Clinical Problem ◽

Gene Identification ◽

Transgenic Mouse Models ◽

Heterogeneous Nature ◽

And Function ◽

Identification And Characterization ◽

Common Clinical Problem

The heterogeneous nature of congenital hydrocephalus has hampered our understanding of the molecular basis of this common clinical problem. However, disease gene identification and characterization of multiple transgenic mouse models has highlighted the importance of the subcommissural organ (SCO) and the ventricular ependymal (vel) cells. Here, we review how altered development and function of the SCO and vel cells contributes to hydrocephalus.

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