My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype
| Autor: | Ruth Nussinov, Lang Li, Feixiong Cheng, Timothy A. Chan, Junfei Zhao, William R. Martin, Yadi Zhou, Jiansong Fang, Charis Eng |
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| Rok vydání: | 2021 |
| Předmět: |
lcsh:QH426-470
Genotype Computational biology Biology DNA sequencing Database Nodetic Protein-protein interaction Somatic mutations Neoplasms Drug Discovery medicine Humans Genomic medicine Exome Protein Interaction Domains and Motifs Allele lcsh:QH301-705.5 Alleles Exome sequencing Drug discovery Computational Biology Cancer Genomics medicine.disease Human genetics lcsh:Genetics Phenotype lcsh:Biology (General) Mutanome Mutation Edgetic Genotype to phenotype Protein Processing Post-Translational Precision cancer medicine |
| Zdroj: | Genome Biology Genome Biology, Vol 22, Iss 1, Pp 1-18 (2021) |
| ISSN: | 1474-760X |
| Popis: | Massive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces (“edgetic”) and 311,022 functional sites (“nodetic”), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org. |
| Databáze: | OpenAIRE |
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