Chapter title |
Interpretation of Quantitative Shotgun Proteomic Data.
|
---|---|
Chapter number | 19 |
Book title |
Proteomics in Systems Biology
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3341-9_19 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3339-6, 978-1-4939-3341-9
|
Authors |
Aasebø, Elise, Berven, Frode S, Selheim, Frode, Barsnes, Harald, Vaudel, Marc, Elise Aasebø, Frode S. Berven, Frode Selheim, Harald Barsnes, Marc Vaudel |
Editors |
Jörg Reinders |
Abstract |
In quantitative proteomics, large lists of identified and quantified proteins are used to answer biological questions in a systemic approach. However, working with such extensive datasets can be challenging, especially when complex experimental designs are involved. Here, we demonstrate how to post-process large quantitative datasets, detect proteins of interest, and annotate the data with biological knowledge. The protocol presented can be achieved without advanced computational knowledge thanks to the user-friendly Perseus interface (available from the MaxQuant website, www.maxquant.org ). Various visualization techniques facilitating the interpretation of quantitative results in complex biological systems are also highlighted. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 3% |
South Africa | 1 | 3% |
Unknown | 33 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 9 | 26% |
Researcher | 7 | 20% |
Student > Master | 6 | 17% |
Professor > Associate Professor | 4 | 11% |
Student > Bachelor | 2 | 6% |
Other | 6 | 17% |
Unknown | 1 | 3% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 12 | 34% |
Agricultural and Biological Sciences | 10 | 29% |
Nursing and Health Professions | 2 | 6% |
Medicine and Dentistry | 2 | 6% |
Neuroscience | 2 | 6% |
Other | 4 | 11% |
Unknown | 3 | 9% |