Focus Feature – Genome Landscapes and Phenotype Prediction of Disease
This Focus Feature led by Rachel Karchin and Ruth Nussinov highlights strategies to predict the phenotypic disease consequences of human germline and somatic variation. The rapid growth in genomic data from large patient cohorts and healthy control populations calls for development of novel, capable and efficient strategies to derive and interpret the phenotypic consequences of germline and somatic variation. The Focus includes network approaches to uncover genotype-phenotype effects in cancer, strategies to bridge the gap between molecular function and the macro level of disease, and in silico methods to predict pathogenic missense variants.
Image Credit: Mathias Appel / Flickr
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PLOS Computational Biology Towards Increasing the Clinical Relevance of In Silico Methods to Predict Pathogenic Missense Variants
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PLOS Computational Biology Understanding Genotype-Phenotype Effects in Cancer via Network Approaches
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PLOS Computational Biology Predicted Molecular Effects of Sequence Variants Link to System Level of Disease
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Center for Cancer Research Ruth Nussinov
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Johns Hopkins Rachel Karchin