Literature DB >> 30872259

[Common cancer genetic analysis methods and application study based on TCGA database].

Xin Li1, Meng Wei Li1, Yi Nan Zhang1, Han Mei Xu1.   

Abstract

The development of second-generation sequencing (NGS) technology is providing numerous data which shifts the focus of cancer research from the sequencing of multi-species to the analysis and comparison of select data via high-throughput sequencing. The NGS also facilitates the diversity of available genetic data analysis methods, the constant optimization and innovation of analytical approaches for high-throughput genomics as well as the rapid development of genetic data mining and analysis models. The Cancer Genome Atlas (TCGA) database is a direct result of this work. The TCGA database provides a comprehensive record of genetic data collected from a tumor patient's sample, including its DNA sequence, transcriptional information, epigenetic modification and related. This review elaborates the latest progress in both the mining algorithm and analysis methods for tumor genomics. Specially, we introduce and review the TCGA database and data analysis approaches while demonstrating its applicability using representative cases. This review may shed light on new tumor-related targets discovery for researchers by means of bid data.

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Year:  2019        PMID: 30872259     DOI: 10.16288/j.yczz.18-279

Source DB:  PubMed          Journal:  Yi Chuan        ISSN: 0253-9772


  2 in total

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Authors:  Jia-Ning Zhang; Feng Wei; Lin-Han Lei; Yang Yang; Yuan Yang; Wei-Ping Zhou
Journal:  Bioengineered       Date:  2021-12       Impact factor: 3.269

2.  Identification of candidate aberrantly methylated and differentially expressed genes in Esophageal squamous cell carcinoma.

Authors:  Bao-Ai Han; Xiu-Ping Yang; Davood K Hosseini; Po Zhang; Ya Zhang; Jin-Tao Yu; Shan Chen; Fan Zhang; Tao Zhou; Hai-Ying Sun
Journal:  Sci Rep       Date:  2020-06-16       Impact factor: 4.379

  2 in total

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