The Experts below are selected from a list of 129933 Experts worldwide ranked by ideXlab platform
Jessica X Chong - One of the best experts on this subject based on the ideXlab platform.
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mendelian Gene Discovery fast and furious with no end in sight
American Journal of Human Genetics, 2019Co-Authors: Michael J Bamshad, Deborah A Nickerson, Jessica X ChongAbstract:Gene Discovery for Mendelian conditions (MCs) offers a direct path to understanding genome function. Approaches based on next-Generation sequencing applied at scale have dramatically accelerated Gene Discovery and transformed Genetic medicine. Finding the Genetic basis of ∼6,000–13,000 MCs yet to be delineated will require both technical and computational innovation, but will rely to a larger extent on meaningful data sharing.
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Gene Discovery for mendelian conditions via social networking de novo variants in kdm1a cause developmental delay and distinctive facial features
Genetics in Medicine, 2016Co-Authors: Jessica X Chong, Peter Lorentzen, Karen M Park, Seema M Jamal, Holly K Tabor, Anita Rauch, Margarita Saenz, Eugen Boltshauser, Karynne E PattersonAbstract:Gene Discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features
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Gene Discovery for mendelian conditions via social networking de novo variants in kdm1a cause developmental delay and distinctive facial features
bioRxiv, 2015Co-Authors: Jessica X Chong, Peter Lorentzen, Karen M Park, Seema M Jamal, Holly K Tabor, Anita Rauch, Margarita Saenz, Eugen Boltshauser, Karynne E Patterson, Deborah A NickersonAbstract:Purpose: The pace of Mendelian Gene Discovery is slowed by the "n-of-1 problem" - the difficulty of establishing causality of a putatively pathogenic variant in a single person or family. Identification of an unrelated person with an overlapping phenotype and suspected pathogenic variant in the same Gene can overcome this barrier but is often impeded by lack of a convenient or widely-available way to share data on candidate variants / Genes among families, clinicians and researchers. Methods: Social networking among families, clinicians and researchers was used to identify three children with variants of unknown significance in KDM1A and similar phenotypes. Results: De novo variants in KDM1A underlie a new syndrome characterized by developmental delay and distinctive facial features. Conclusion: Social networking is a potentially powerful strategy to discover Genes for rare Mendelian conditions, particularly those with non-specific phenotypic features. To facilitate the efforts of families to share phenotypic and genomic information with each other, clinicians, and researchers, we developed the Repository for Mendelian Genomics Family Portal (RMD-FP). Design and development of a web-based tool, MyGene2, that enables families, clinicians and researchers to search for Gene matches based on analysis of phenotype and exome data deposited into the RMD-FP is underway.
Jean-michel Savoie - One of the best experts on this subject based on the ideXlab platform.
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The first set of expressed sequence tags (EST) from the medicinal mushroom Agaricus subrufescens delivers resource for Gene Discovery and marker development
Applied Microbiology and Biotechnology, 2014Co-Authors: Marie Foulongne-oriol, Nicolas Lapalu, Cathy Spataro, Nathalie Ferrer, Joelle Amselem, Cyril Férandon, Jean-michel SavoieAbstract:Agaricus subrufescens is one of the most important culinary-medicinal cultivable mushrooms with potentially high-added-value products and extended agronomical valorization. The development of A. subrufescens -related technologies is hampered by, among others, the lack of suitable molecular tools. Thus, this mushroom is considered as a genomic orphan species with a very limited number of available molecular markers or sequences. To fill this gap, this study reports the Generation and analysis of the first set of expressed sequence tags (EST) for A. subrufescens . cDNA fragments obtained from young sporophores (SP) and vegetative mycelium in liquid culture (CL) were sequenced using 454 pyrosequencing technology. After assembly process, 4,989 and 5,125 sequences were obtained in SP and CL libraries, respectively. About 87 % of the EST had significant similarity with Agaricus bisporus -predicted proteins, and 79 % correspond to known proteins. Functional categorization according to Gene Ontology could be assigned to 49 % of the sequences. Some Gene families potentially involved in bioactive compound biosynthesis could be identified. A total of 232 simple sequence repeats (SSRs) were identified, and a set of 40 EST-SSR polymorphic markers were successfully developed. This EST dataset provides a new resource for Gene Discovery and molecular marker development. It constitutes a solid basis for further Genetic and genomic studies in A. subrufescens .
Karynne E Patterson - One of the best experts on this subject based on the ideXlab platform.
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Gene Discovery for mendelian conditions via social networking de novo variants in kdm1a cause developmental delay and distinctive facial features
Genetics in Medicine, 2016Co-Authors: Jessica X Chong, Peter Lorentzen, Karen M Park, Seema M Jamal, Holly K Tabor, Anita Rauch, Margarita Saenz, Eugen Boltshauser, Karynne E PattersonAbstract:Gene Discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features
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Gene Discovery for mendelian conditions via social networking de novo variants in kdm1a cause developmental delay and distinctive facial features
bioRxiv, 2015Co-Authors: Jessica X Chong, Peter Lorentzen, Karen M Park, Seema M Jamal, Holly K Tabor, Anita Rauch, Margarita Saenz, Eugen Boltshauser, Karynne E Patterson, Deborah A NickersonAbstract:Purpose: The pace of Mendelian Gene Discovery is slowed by the "n-of-1 problem" - the difficulty of establishing causality of a putatively pathogenic variant in a single person or family. Identification of an unrelated person with an overlapping phenotype and suspected pathogenic variant in the same Gene can overcome this barrier but is often impeded by lack of a convenient or widely-available way to share data on candidate variants / Genes among families, clinicians and researchers. Methods: Social networking among families, clinicians and researchers was used to identify three children with variants of unknown significance in KDM1A and similar phenotypes. Results: De novo variants in KDM1A underlie a new syndrome characterized by developmental delay and distinctive facial features. Conclusion: Social networking is a potentially powerful strategy to discover Genes for rare Mendelian conditions, particularly those with non-specific phenotypic features. To facilitate the efforts of families to share phenotypic and genomic information with each other, clinicians, and researchers, we developed the Repository for Mendelian Genomics Family Portal (RMD-FP). Design and development of a web-based tool, MyGene2, that enables families, clinicians and researchers to search for Gene matches based on analysis of phenotype and exome data deposited into the RMD-FP is underway.
Holly K Tabor - One of the best experts on this subject based on the ideXlab platform.
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Gene Discovery for mendelian conditions via social networking de novo variants in kdm1a cause developmental delay and distinctive facial features
Genetics in Medicine, 2016Co-Authors: Jessica X Chong, Peter Lorentzen, Karen M Park, Seema M Jamal, Holly K Tabor, Anita Rauch, Margarita Saenz, Eugen Boltshauser, Karynne E PattersonAbstract:Gene Discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features
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Gene Discovery for mendelian conditions via social networking de novo variants in kdm1a cause developmental delay and distinctive facial features
bioRxiv, 2015Co-Authors: Jessica X Chong, Peter Lorentzen, Karen M Park, Seema M Jamal, Holly K Tabor, Anita Rauch, Margarita Saenz, Eugen Boltshauser, Karynne E Patterson, Deborah A NickersonAbstract:Purpose: The pace of Mendelian Gene Discovery is slowed by the "n-of-1 problem" - the difficulty of establishing causality of a putatively pathogenic variant in a single person or family. Identification of an unrelated person with an overlapping phenotype and suspected pathogenic variant in the same Gene can overcome this barrier but is often impeded by lack of a convenient or widely-available way to share data on candidate variants / Genes among families, clinicians and researchers. Methods: Social networking among families, clinicians and researchers was used to identify three children with variants of unknown significance in KDM1A and similar phenotypes. Results: De novo variants in KDM1A underlie a new syndrome characterized by developmental delay and distinctive facial features. Conclusion: Social networking is a potentially powerful strategy to discover Genes for rare Mendelian conditions, particularly those with non-specific phenotypic features. To facilitate the efforts of families to share phenotypic and genomic information with each other, clinicians, and researchers, we developed the Repository for Mendelian Genomics Family Portal (RMD-FP). Design and development of a web-based tool, MyGene2, that enables families, clinicians and researchers to search for Gene matches based on analysis of phenotype and exome data deposited into the RMD-FP is underway.
Anthony A Philippakis - One of the best experts on this subject based on the ideXlab platform.
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the matchmaker exchange a platform for rare disease Gene Discovery
Human Mutation, 2015Co-Authors: Anthony A Philippakis, Danielle R Azzariti, Sergi Beltran, Anthony J Brookes, Catherine A Brownstein, Michael Brudno, Han G BrunnerAbstract:There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of Discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease Gene Discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.