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Volume 12 Supplement 5

Selected articles from the 8th Translational Bioinformatics Conference (TBC 2018): medical genomics

Research

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

Seoul, South Korea31 October - 2 November 2018

Conference website

Edited by Ju Han Kim and Keun Woo Lee

Related articles have been published as a supplement to BMC Bioinformatics.

  1. CoMut plot is widely used in cancer research publications as a visual summary of mutational landscapes in cancer cohorts. This summary plot can inspect gene mutation rate and sample mutation burden with their ...

    Authors: Po-Jung Huang, Hou-Hsien Lin, Chi-Ching Lee, Ling-Ya Chiu, Shao-Min Wu, Yuan-Ming Yeh, Petrus Tang, Cheng-Hsun Chiu, Ping-Chiang Lyu and Pei-Chien Tsai

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  2. The analysis of integrated multi-omics data enables the identification of disease-related biomarkers that cannot be identified from a single omics profile. Although protein-level data reflects the cellular sta...

    Authors: Tae Rim Kim, Hyun-Hwan Jeong and Kyung-Ah Sohn

    Citation: BMC Medical Genomics 2019 12(Suppl 5):94

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  3. Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies ...

    Authors: Sehee Wang, Hyun-Hwan Jeong and Kyung-Ah Sohn

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  4. Gene expression profiling has benefited medicine by providing clinically relevant insights at the molecular candidate and systems levels. However, to adopt a more ‘precision’ approach that integrates individua...

    Authors: Samir Rachid Zaim, Colleen Kenost, Joanne Berghout, Francesca Vitali, Helen Hao Zhang and Yves A. Lussier

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  5. Gene Expression database of Normal and Tumor tissues 2 (GENT2) is an updated version of GENT, which has provided a user-friendly search platform for gene expression patterns across different normal and tumor t...

    Authors: Seung-Jin Park, Byoung-Ha Yoon, Seon-Kyu Kim and Seon-Young Kim

    Citation: BMC Medical Genomics 2019 12(Suppl 5):101

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  6. Gene expression data is widely used for identifying subtypes of diseases such as cancer. Differentially expressed gene analysis and gene set enrichment analysis are widely used for identifying biological mecha...

    Authors: Sungjoon Park, Doyeong Hwang, Yoon Sun Yeo, Hyunggee Kim and Jaewoo Kang

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  7. In genome-wide association studies (GWASs), meta-analysis has been widely used to improve statistical power by combining the results of different studies. Meta-analysis can detect phenotype associated variants...

    Authors: Jieun Ka, Jaehoon Lee, Yongkang Kim, Bermseok Oh and Taesung Park

    Citation: BMC Medical Genomics 2019 12(Suppl 5):102

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  8. Recent large-scale genetic studies often involve clustered phenotypes such as repeated measurements. Compared to a series of univariate analyses of single phenotypes, an analysis of clustered phenotypes can be...

    Authors: Sungyoung Lee, Sunmee Kim, Yongkang Kim, Bermseok Oh, Heungsun Hwang and Taesung Park

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