Machine learning methods for predictive proteomics

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.

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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 ...
• ...

6 References

The list of cited or related literature is placed here.