Methodologies of Multi-Omics Data Integration and Data Mining Techniques and Applications /
This book features multi-omics big-data integration and data-mining techniques. In the omics age, paramount of multi-omics data from various sources is the new challenge we are facing, but it also provides clues for several biomedical or clinical applications. This book focuses on data integration a...
Wedi'i Gadw mewn:
| Awdur Corfforaethol: | |
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| Awduron Eraill: | |
| Fformat: | Electronig eLyfr |
| Iaith: | Saesneg |
| Cyhoeddwyd: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
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| Rhifyn: | 1st ed. 2023. |
| Cyfres: | Translational Bioinformatics,
19 |
| Pynciau: | |
| Mynediad Ar-lein: | https://doi.org/10.1007/978-981-19-8210-1 |
| Tagiau: |
Ychwanegu Tag
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Tabl Cynhwysion:
- Chapter 1. Introduction to multi-omics
- Part 1. Omics integration techniques
- Chapter 2. Biomedical applications: the need for multi-omics
- Chapter 3. Omics technologies and big data
- Chapter 4. Multi-omics data mining techniques: algorithms and software
- Part 2. Applications of multi-omics analyses
- Chapter 5. Multi-omics data analysis for cancer research: colorectal cancer, liver cancer and lung cancer
- Chapter 6. Multi-omics data analysis for inflammation disease research: correlation analysis, causal analysis and network analysis
- Chapter 7. Microbiome data analysis and interpretation: correlation inferences and dynamic pattern discovery
- Chapter 8. Current progress of bioinformatics for human health.