Characterization of glycosylphosphatidylinositol biosynthesis defects by clinical features, flow cytometry, and automated image analysis

Characterization of glycosylphosphatidylinositol biosynthesis defects by clinical features, flow cytometry, and automated image analysis

Abstract Background Glycosylphosphatidylinositol biosynthesis defects (GPIBDs) cause a group of phenotypically overlapping recessive syndromes with intellectual disability, for which pathogenic mutations have been described in 16 genes of the corresponding molecular pathway. An elevated serum activi...

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Main Authors: Alexej Knaus, Jean Tori Pantel, Manuela Pendziwiat, Nurulhuda Hajjir, Max Zhao, Tzung-Chien Hsieh, Max Schubach, Yaron Gurovich, Nicole Fleischer, Marten Jäger, Sebastian Köhler, Hiltrud Muhle, Christian Korff, Rikke S. Møller, Allan Bayat, Patrick Calvas, Nicolas Chassaing, Hannah Warren, Steven Skinner, Raymond Louie, Christina Evers, Marc Bohn, Hans-Jürgen Christen, Myrthe van den Born, Ewa Obersztyn, Agnieszka Charzewska, Milda Endziniene, Fanny Kortüm, Natasha Brown, Peter N. Robinson, Helenius J. Schelhaas, Yvonne Weber, Ingo Helbig, Stefan Mundlos, Denise Horn, Peter M. Krawitz
Format: Article
Language:English
Published: BMC 2018-01-01
Series:Genome Medicine
Subjects:
GPI
Anchor biosynthesis defects
Automated image analysis
Gene
Prediction
Online Access:http://link.springer.com/article/10.1186/s13073-017-0510-5

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http://link.springer.com/article/10.1186/s13073-017-0510-5

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