| Chapter title |
Fifteen Years of Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC)
|
|---|---|
| Chapter number | 1 |
| Book title |
Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC)
|
| Published in |
Methods in molecular biology, January 2014
|
| DOI | 10.1007/978-1-4939-1142-4_1 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-1141-7, 978-1-4939-1142-4
|
| Authors |
Matthias Mann |
| Abstract |
Here I describe the history of the Stable Isotope Labeling by Amino Acids in Cell culture (SILAC) technology. Although published in 2002, it had already been developed and used in my laboratory for a number of years. From the beginning, it was applied to challenging problems in cell signaling that were considered out of reach for proteomics at the time. It was also used to pioneer proteomic interactomics, time series and dynamic posttranslational modification studies. While initially developed for metabolically accessible systems, such as cell lines, it was subsequently extended to whole animal labeling as well as to clinical applications-in the form or spike-in or super-SILAC. New formats and applications for SILAC labeling continue to be developed, for instance for protein-turnover studies. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Sweden | 1 | <1% |
| Brazil | 1 | <1% |
| Belgium | 1 | <1% |
| United Kingdom | 1 | <1% |
| Unknown | 171 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 69 | 39% |
| Researcher | 29 | 16% |
| Student > Master | 22 | 12% |
| Student > Bachelor | 18 | 10% |
| Professor > Associate Professor | 8 | 4% |
| Other | 18 | 10% |
| Unknown | 14 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 78 | 44% |
| Biochemistry, Genetics and Molecular Biology | 53 | 30% |
| Chemistry | 13 | 7% |
| Neuroscience | 5 | 3% |
| Immunology and Microbiology | 4 | 2% |
| Other | 7 | 4% |
| Unknown | 18 | 10% |