Machine learning methods for predictive proteomics
Contents
1 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.
2 Summary
Briefly describe the scope of the paper, i.e. the field of research and/or application.
3 Study outcomes
List the paper results concerning method comparison and benchmarking:
3.1 Outcome O1
The performance of ...
Outcome O1 is presented as Figure X in the original publication.
3.2 Outcome O2
...
Outcome O2 is presented as Figure X in the original publication.
3.3 Outcome On
...
Outcome On is presented as Figure X in the original publication.
3.4 Further outcomes
If intended, you can add further outcomes here.
4 Study design and evidence level
4.1 General aspects
You can describe general design aspects here. The study designs for describing specific outcomes are listed in the following subsections:
4.2 Design for Outcome O1
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
4.3 Design for Outcome O2
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
...
4.4 Design for Outcome O
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
5 Further comments and aspects
6 References
The list of cited or related literature is placed here.
