Researchers develop new tool for better classification of in

Researchers develop new tool for better classification of inherited disease-causing variants

Researchers from Children's Hospital of Philadelphia (CHOP), the Perelman School of Medicine at the University of Pennsylvania, and the National Cancer Institute (NCI) of the National Institutes of Health have developed a new tool that allows scientists to annotate variant data from large-scale studies with clinically-focused classifications for risk of childhood cancer and other diseases. This new tool brings older applications in line with current guidelines and is available for use—for free—in the research community. The tool was described in a paper recently published in the journal Bioinformatics.

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Philadelphia , Pennsylvania , United States , University Of Pennsylvania , Jung Kim , Pathogenicity Auto , Jo Lynne Rokita , Sharonj Diskin , Perelman School Of Medicine , Association For Molecular Pathology , American College Of Medical Genetics , Health Informatics , Journal Of The National Cancer Institute , Division Of Cancer Epidemiology , Children Brain Tumor Network , Department Of Biomedical , National Cancer Institute , National Institutes Of Health , Perelman School , National Institutes , American College , Medical Genetics Association , Molecular Pathology , Associate Professor , Automated Germline Variant Pathogenicity , Brain Tumor Network , Supervisory Bioinformatics Scientist , Data Driven Discovery , Cancer Epidemiology ,

© 2024 Vimarsana
Researchers Develop New Tool For Better Classification Of Inherited Disease-causing Variants : Comparemela.com

Researchers develop new tool for better classification of inherited disease-causing variants

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Researchers from Children's Hospital of Philadelphia (CHOP), the Perelman School of Medicine at the University of Pennsylvania, and the National Cancer Institute (NCI) of the National Institutes of Health have developed a new tool that allows scientists to annotate variant data from large-scale studies with clinically-focused classifications for risk of childhood cancer and other diseases. This new tool brings older applications in line with current guidelines and is available for use—for free—in the research community. The tool was described in a paper recently published in the journal Bioinformatics.

Related Keywords

Philadelphia , Pennsylvania , United States , University Of Pennsylvania , Jung Kim , Pathogenicity Auto , Jo Lynne Rokita , Sharonj Diskin , Perelman School Of Medicine , Association For Molecular Pathology , American College Of Medical Genetics , Health Informatics , Journal Of The National Cancer Institute , Division Of Cancer Epidemiology , Children Brain Tumor Network , Department Of Biomedical , National Cancer Institute , National Institutes Of Health , Perelman School , National Institutes , American College , Medical Genetics Association , Molecular Pathology , Associate Professor , Automated Germline Variant Pathogenicity , Brain Tumor Network , Supervisory Bioinformatics Scientist , Data Driven Discovery , Cancer Epidemiology ,

© 2024 Vimarsana

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