| Chapter title |
Data Fusion in Metabolomics and Proteomics for Biomarker Discovery.
|
|---|---|
| Chapter number | 14 |
| Book title |
Statistical Analysis in Proteomics
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3106-4_14 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3105-7, 978-1-4939-3106-4
|
| Authors |
Blanchet, Lionel, Smolinska, Agnieszka, Lionel Blanchet, Agnieszka Smolinska |
| Abstract |
Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry. Each method has inherent advantages and drawbacks, but they are complementary in terms of biological information.The fusion of different measurements is a complex topic. We describe here a framework allowing combining multiple data sets, provided by different analytical platforms. For each platform, the relevant information is extracted in the first step. The obtained latent variables are then fused and further analyzed. The influence of the original variables is then calculated back and interpreted. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 20% |
| Germany | 1 | 20% |
| United States | 1 | 20% |
| Netherlands | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 5% |
| Unknown | 18 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 32% |
| Student > Ph. D. Student | 5 | 26% |
| Lecturer | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Student > Master | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 2 | 11% |
| Engineering | 2 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Computer Science | 1 | 5% |
| Physics and Astronomy | 1 | 5% |
| Other | 6 | 32% |
| Unknown | 6 | 32% |