Chapter title |
Proteotypic Peptides and Their Applications.
|
---|---|
Chapter number | 8 |
Book title |
Proteome Bioinformatics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6740-7_8 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6738-4, 978-1-4939-6740-7
|
Authors |
Shivakumar Keerthikumar, Suresh Mathivanan, Keerthikumar, Shivakumar, Mathivanan, Suresh |
Editors |
Shivakumar Keerthikumar, Suresh Mathivanan |
Abstract |
Recent advances in mass spectrometry based proteomic techniques and publicly available large proteomic repositories are being exploited to characterize the proteome of multiple organisms. While humongous amount of proteomic data is being acquired and analyzed, many biological questions still remain unanswered. Proteotypic peptides which uniquely represent target proteins or a protein isoform are used as an alternative strategy for protein identification in the field of immunological methods and targeted proteomic techniques. Using different computational approaches, resources and techniques used in the identification of proteotypic peptides of target proteins is discussed here. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 24 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 4 | 17% |
Student > Master | 3 | 13% |
Student > Bachelor | 2 | 8% |
Professor > Associate Professor | 2 | 8% |
Student > Ph. D. Student | 1 | 4% |
Other | 1 | 4% |
Unknown | 11 | 46% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 7 | 29% |
Agricultural and Biological Sciences | 3 | 13% |
Medicine and Dentistry | 2 | 8% |
Computer Science | 1 | 4% |
Unknown | 11 | 46% |