| Chapter title |
Protein Structure Databases.
|
|---|---|
| Chapter number | 2 |
| Book title |
Data Mining Techniques for the Life Sciences
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3572-7_2 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3570-3, 978-1-4939-3572-7
|
| Authors |
Roman A. Laskowski |
| Editors |
Oliviero Carugo, Frank Eisenhaber |
| Abstract |
Web-based protein structure databases come in a wide variety of types and levels of information content. Those having the most general interest are the various atlases that describe each experimentally determined protein structure and provide useful links, analyses, and schematic diagrams relating to its 3D structure and biological function. Also of great interest are the databases that classify 3D structures by their folds as these can reveal evolutionary relationships which may be hard to detect from sequence comparison alone. Related to these are the numerous servers that compare folds-particularly useful for newly solved structures, and especially those of unknown function. Beyond these are a vast number of databases for the more specialized user, dealing with specific families, diseases, structural features, and so on. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 18% |
| Researcher | 4 | 18% |
| Other | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Ph. D. Student | 2 | 9% |
| Other | 4 | 18% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 36% |
| Agricultural and Biological Sciences | 8 | 36% |
| Chemistry | 2 | 9% |
| Computer Science | 1 | 5% |
| Engineering | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 2 | 9% |