Subcellular Proteomics
Springer Netherlands
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Timeline
Mendeley readers
| Chapter title |
Automated, systematic determination of protein subcellular location using fluorescence microscopy.
|
|---|---|
| Chapter number | 12 |
| Book title |
Subcellular Proteomics
|
| Published in |
Sub cellular biochemistry, January 2007
|
| DOI | 10.1007/978-1-4020-5943-8_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4020-5942-1, 978-1-4020-5943-8
|
| Authors |
García Osuna, Elvira, Murphy, Robert F, Elvira García Osuna, Robert F. Murphy, Osuna, Elvira García, Murphy, Robert F. |
| Abstract |
Proteomics is the comprehensive study of all aspects of protein behavior. The subfield of location proteomics is concerned with the systematic analysis of the subcellular location of proteins. In order to perform high-resolution, high-throughput analysis of all protein location patterns, automation is needed both for acquisition and analysis. Automated methods for analyzing subcellular location patterns in fluorescence microscope images have been developed and shown to work well for static 2D and 3D images of single cells. This chapter reviews this work and describes current efforts to extend these approaches, including classification of temporal patterns and building of generative models to represent location patterns. |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 5 | 22% |
| Student > Ph. D. Student | 3 | 13% |
| Professor | 3 | 13% |
| Student > Doctoral Student | 2 | 9% |
| Student > Master | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 8 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 30% |
| Computer Science | 6 | 26% |
| Economics, Econometrics and Finance | 1 | 4% |
| Unknown | 9 | 39% |