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CanPredict: a computational tool for predicting cancer-associated missense mutations

CanPredict: a computational tool for predicting cancer-associated missense mutations

http://www.wikidata.org/entity/Q24684564

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Cancer genome landscapes Cancer-associated loss-of-function mutations implicate DAPK3 as a tumor-suppressing kinase Advances in translational bioinformatics: computational approaches for the hunting of disease genes Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine How do oncoprotein mutations rewire protein-protein interaction networks?Drug resistance missense mutations in cancer are subject to evolutionary constraints Bioinformatics for personal genome interpretation Status quo of annotation of human disease variants.MoKCa database--mutations of kinases in cancer.Applications of computational tools to predict functional SNPs effects in human ErbB genes.Automated inference of molecular mechanisms of disease from amino acid substitutions.Human allelic variation: perspective from protein function, structure, and evolution.Predicting disease-associated substitution of a single amino acid by analyzing residue interactions.In silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B.MuSiC: identifying mutational significance in cancer genomes.Interpretation of the consequences of mutations in protein kinases: combined use of bioinformatics and text mining.Multisample aCGH data analysis via total variation and spectral regularization.An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology.Sequence and structure signatures of cancer mutation hotspots in protein kinases Bi-directional SIFT predicts a subset of activating mutations.Automated network analysis identifies core pathways in glioblastoma.Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation.Making sense of cancer genomic data.Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnostics CHASM and SNVBox: toolkit for detecting biologically important single nucleotide mutations in cancer.Cancer driver mutations in protein kinase genes Phylomedicine: an evolutionary telescope to explore and diagnose the universe of disease mutations.Prioritization of pathogenic mutations in the protein kinase superfamily Predicting cancer-associated germline variations in proteins.Predicting the functional consequences of cancer-associated amino acid substitutions.Ranking non-synonymous single nucleotide polymorphisms based on disease concepts Variation Interpretation Predictors: Principles, Types, Performance, and Choice.Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis.Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel.WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation.Assessment of computational methods for predicting the effects of missense mutations in human cancers Prediction of disease causing non-synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP.CanDrA: cancer-specific driver missense mutation annotation with optimized features.Bioinformatics challenges for personalized medicine Detection and analysis of disease-associated single nucleotide polymorphism influencing post-translational modification.

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CanPredict: a computational tool for predicting cancer-associated missense mutations

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2007 nî lūn-bûn

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CanPredict: a computational tool for predicting cancer-associated missense mutations

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CanPredict: a computational tool for predicting cancer-associated missense mutations

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CanPredict: a computational tool for predicting cancer-associated missense mutations

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CanPredict: a computational tool for predicting cancer-associated missense mutations

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Colin Watanabe

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Joshua S Kaminker

http://www.w3.org/2001/XMLSchema#string

Yan Zhang

http://www.w3.org/2001/XMLSchema#string

Zemin Zhang

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The consensus coding sequences of human breast and colorectal cancers

Human non-synonymous SNPs: server and survey

A comparative study of machine-learning methods to predict the effects of single nucleotide polymorphisms on protein function.

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources.

Statistical geometry approach to the study of functional effects of human nonsynonymous SNPs.

Distinguishing cancer-associated missense mutations from common polymorphisms.

Accounting for human polymorphisms predicted to affect protein function.

Somatic mutations of the protein kinase gene family in human lung cancer.

Identification and analysis of deleterious human SNPs.

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553594

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10.1093/NAR/GKM405

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Web Server issue

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35

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17537827

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1933186

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