Machine learning methods for predictive proteomics
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Contents
Citation
Barla A, Jurman G, Riccadonna S, Merler S, Chierici M, Furlanello C. Machine learning methods for predictive proteomics. Briefings in bioinformatics. 2008 Mar 1;9(2):119-28.
Summary
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Study outcomes
List the paper results concerning method comparison and benchmarking:
Outcome O1
The performance of ...
Outcome O1 is presented as Figure X in the original publication.
Outcome O2
...
Outcome O2 is presented as Figure X in the original publication.
Outcome On
...
Outcome On is presented as Figure X in the original publication.
Further outcomes
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Study design and evidence level
General aspects
You can describe general design aspects here. The study designs for describing specific outcomes are listed in the following subsections:
Design for Outcome O1
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
Design for Outcome O2
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
...
Design for Outcome O
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
Further comments and aspects
References
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