| Chapter title |
Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data.
|
|---|---|
| Chapter number | 3 |
| Book title |
Proteome Bioinformatics
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6740-7_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6738-4, 978-1-4939-6740-7
|
| Authors |
Dhirendra Kumar, Amit Kumar Yadav, Debasis Dash, Kumar, Dhirendra, Yadav, Amit Kumar, Dash, Debasis |
| Editors |
Shivakumar Keerthikumar, Suresh Mathivanan |
| Abstract |
Database searching is the preferred method for protein identification from digital spectra of mass to charge ratios (m/z) detected for protein samples through mass spectrometers. The search database is one of the major influencing factors in discovering proteins present in the sample and thus in deriving biological conclusions. In most cases the choice of search database is arbitrary. Here we describe common search databases used in proteomic studies and their impact on final list of identified proteins. We also elaborate upon factors like composition and size of the search database that can influence the protein identification process. In conclusion, we suggest that choice of the database depends on the type of inferences to be derived from proteomics data. However, making additional efforts to build a compact and concise database for a targeted question should generally be rewarding in achieving confident protein identifications. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 40% |
| United Kingdom | 1 | 20% |
| India | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 47 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 26% |
| Researcher | 6 | 13% |
| Student > Doctoral Student | 5 | 11% |
| Student > Master | 5 | 11% |
| Student > Bachelor | 3 | 6% |
| Other | 8 | 17% |
| Unknown | 8 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 40% |
| Agricultural and Biological Sciences | 6 | 13% |
| Chemistry | 4 | 9% |
| Unspecified | 1 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 6 | 13% |
| Unknown | 10 | 21% |