| Chapter title |
Prediction of Proteases Involved in Peptide Generation
|
|---|---|
| Chapter number | 15 |
| Book title |
Protein Terminal Profiling
|
| Published in |
Methods in molecular biology, March 2017
|
| DOI | 10.1007/978-1-4939-6850-3_15 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6849-7, 978-1-4939-6850-3
|
| Authors |
Mercedes Arguello Casteleiro, Robert Stevens, Julie Klein |
| Editors |
Oliver Schilling |
| Abstract |
Clinical proteomics has led to the identification of a substantial number of disease-associated peptides and protein fragments in several conditions such as cancer, kidney, or cardiovascular diseases. In silico prediction tools that can facilitate linking of identified peptide biomarkers to predicted protease activity might therefore significantly contribute to the understanding of pathophysiological mechanisms of these diseases. Proteasix is an open-source, peptide-centric tool that can be used to predict in silico the proteases involved in naturally occurring peptide generation. From an input peptide list, Proteasix allows for automatic cleavage site reconstruction and protease associations. |
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Geographical breakdown
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|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 1 | 50% |
| Student > Master | 1 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 1 | 50% |
| Unknown | 1 | 50% |