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Data analysis methods for defining biomarkers from omics data
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DOI：10.1007/s00216-021-03813-7.png)
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摘要
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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.
Keyword:
Omics data analysis
Biomarker discovery
Molecular biomarkers
Combinatorial features
Network analysis
期刊
IF:
3.8
论文数:
1.8W
被引数:
3.5W
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