Literature DB >> 34951658

Data analysis methods for defining biomarkers from omics data.

Chao Li1,2, Zhenbo Gao1, Benzhe Su1, Guowang Xu2, Xiaohui Lin3.   

Abstract

Omics mainly includes genomics, epigenomics, transcriptomics, proteomics and metabolomics. The rapid development of omics technology has opened up new ways to study disease diagnosis and prognosis and to define prospective information of complex diseases. Since omics data are usually large and complex, the method used to analyze the data and to define important information is crucial in omics study. In this review, we focus on advances in biomarker discovery methods based on omics data in the last decade, and categorize them as individual feature analysis, combinatorial feature analysis and network analysis. We also discuss the challenges and perspectives in this field.
© 2021. Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Biomarker discovery; Combinatorial features; Molecular biomarkers; Network analysis; Omics data analysis

Mesh:

Substances:

Year:  2021        PMID: 34951658     DOI: 10.1007/s00216-021-03813-7

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


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