| Chapter title |
Introduction to Clinical Proteomics
|
|---|---|
| Chapter number | 20 |
| Book title |
Modern Proteomics – Sample Preparation, Analysis and Practical Applications
|
| Published in |
Advances in experimental medicine and biology, December 2016
|
| DOI | 10.1007/978-3-319-41448-5_20 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-941446-1, 978-3-31-941448-5
|
| Authors |
John E. Wiktorowicz, Allan R. Brasier |
| Editors |
Hamid Mirzaei, Martin Carrasco |
| Abstract |
Within the context of this section, biomarkers are defined as a panel of proteins and peptides that are predictive of the risk for developing a pathological condition. It is important to note here that the use of the descriptor 'panel' is purposeful in that single "biomarkers" are rarely sufficient to permit accurate prediction of a pathological condition. More specifically, the primary application of a biomarker panel is that it serves as a molecular indicator of the severity of a disease or its early response to treatment. In this way, biomarkers enable the application of precision medicine, an approach that tailors specific interventions to those individuals that would most benefit. For a recent comprehensive review of the proteomic-based biomarker development process with a focus on bladder cancer, the reader is directed to Frantzi et al. [Clin Transl Med 3:7, 2014], or a special issue with multiple reviews [Stuhler and Poschmann, Biochim Biophys Acta Proteins Proteomics 1844:859-1058, Elsevier, B V, 2014]. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 3 | 23% |
| Other | 2 | 15% |
| Unspecified | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Lecturer > Senior Lecturer | 1 | 8% |
| Other | 2 | 15% |
| Unknown | 3 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 23% |
| Biochemistry, Genetics and Molecular Biology | 2 | 15% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Unspecified | 1 | 8% |
| Chemistry | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 31% |