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DriverDBv4: a multi-omics integration database for cancer driver gene research.
Liu, Chia-Hsin; Lai, Yo-Liang; Shen, Pei-Chun; Liu, Hsiu-Cheng; Tsai, Meng-Hsin; Wang, Yu-De; Lin, Wen-Jen; Chen, Fang-Hsin; Li, Chia-Yang; Wang, Shu-Chi; Hung, Mien-Chie; Cheng, Wei-Chung.
Afiliação
  • Liu CH; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Lai YL; Department of Radiation Oncology, China Medical University, Taichung 404328, Taiwan.
  • Shen PC; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Liu HC; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Tsai MH; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Wang YD; Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404328, Taiwan.
  • Lin WJ; Department of Urology, China Medical University, Taichung 404328, Taiwan.
  • Chen FH; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Li CY; School of Medicine, China Medical University, Taichung 404328, Taiwan.
  • Wang SC; Institute of Nuclear Engineering and Science, National Tsing Hua University, Hsinchu 300044, Taiwan.
  • Hung MC; Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
  • Cheng WC; Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Nucleic Acids Res ; 52(D1): D1246-D1252, 2024 Jan 05.
Article em En | MEDLINE | ID: mdl-37956338
ABSTRACT
Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http//driverdb.bioinfomics.org/). This updated version offers several significant enhancements (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Genéticas / Multiômica / Neoplasias Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Genéticas / Multiômica / Neoplasias Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article