Abstract:
:Most of current gene expression signatures for cancer prognosis are based on risk scores, usually calculated as some summaries of expression levels of the signature genes, whose applications require presetting risk score thresholds and data normalization. In this study, we demonstrate the critical limitations of such type of signatures that the risk scores of samples will change greatly when they are normalized together with different samples, which would induce spurious risk classification and difficulty in clinical settings, and the risk scores of independent samples are incomparable if data normalization is not adopted. To overcome these limitations, we propose a rank-based method to extract a prognostic gene pair signature for overall survival of stage I non-small-cell lung cancer. The prognostic gene pair signature is verified in three integrated data sets detected by different laboratories with different microarray platforms. We conclude that, different from the type of signatures based on risk scores summarized from gene expression levels, the rank-based signatures could be robustly applied at the individualized level to independent clinical samples assessed in different laboratories.
journal_name
Brief Bioinformjournal_title
Briefings in bioinformaticsauthors
Qi L,Chen L,Li Y,Qin Y,Pan R,Zhao W,Gu Y,Wang H,Wang R,Chen X,Guo Zdoi
10.1093/bib/bbv064subject
Has Abstractpub_date
2016-03-01 00:00:00pages
233-42issue
2eissn
1467-5463issn
1477-4054pii
bbv064journal_volume
17pub_type
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
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abstract::This Briefing reviews the widely used, currently active, up-to-date databases derived from the worldwide Protein Data Bank (PDB) to facilitate browsing, finding and exploring its entries. These databases contain visualization and analysis tools tailored to specific kinds of molecules and interactions, often including ...
journal_title:Briefings in bioinformatics
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更新日期:2017-07-01 00:00:00
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journal_title:Briefings in bioinformatics
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更新日期:2015-01-01 00:00:00
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
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abstract::Circular RNA (circRNA) is a group of RNA family generated by RNA circularization, which was discovered ubiquitously across different species and tissues. However, there is no global view of tissue specificity for circRNAs to date. Here we performed the comprehensive analysis to characterize the features of human and m...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbw081
更新日期:2017-11-01 00:00:00
abstract::Functional annotation of protein sequence with high accuracy has become one of the most important issues in modern biomedical studies, and computational approaches of significantly accelerated analysis process and enhanced accuracy are greatly desired. Although a variety of methods have been developed to elevate prote...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2020-07-15 00:00:00
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