Data Analysis for Omic Sciences: Methods and Applications
Nonfiction, Science & Nature, Science, Chemistry, Analytic
| Author: | Joaquim Jaumot, Carmen Bedia, Romà Tauler | ISBN: | 9780444640451 |
| Publisher: | Elsevier Science | Publication: | September 22, 2018 |
| Imprint: | Elsevier | Language: | English |
| Author: | Joaquim Jaumot, Carmen Bedia, Romà Tauler |
| ISBN: | 9780444640451 |
| Publisher: | Elsevier Science |
| Publication: | September 22, 2018 |
| Imprint: | Elsevier |
| Language: | English |
Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more.
- Presents the best reference book for omics data analysis
- Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools
- Includes examples of applications in research fields, such as environmental, biomedical and food analysis
Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more.
- Presents the best reference book for omics data analysis
- Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools
- Includes examples of applications in research fields, such as environmental, biomedical and food analysis
