Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies

Revision as of 08:50, 25 February 2020 by Bwday (talk | contribs) (Paper name)

== Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies == Cosmin Lazar, Laurent Gatto, Myriam Ferro, Christophe Bruley and Thomas Burger (2016): Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies. Journal of Proteome Research, 15:1116–1125.

Authors, title, year, journal, volume, pages etc in any possible citation style. [1]


1 Summary

Briefly describe the scope of the paper, i.e. the field of research and/or application.

2 Study outcomes

List the paper results concerning method comparison and benchmarking:

2.1 Outcome O1

The performance of ...

Outcome O1 is presented as Figure X in the original publication.

2.2 Outcome O2

...

Outcome O2 is presented as Figure X in the original publication.

2.3 Outcome On

...

Outcome On is presented as Figure X in the original publication.

2.4 Further outcomes

If intended, you can add further outcomes here.


3 Study design and evidence level

3.1 General aspects

You can describe general design aspects here. The study designs for describing specific outcomes are listed in the following subsections:

3.2 Design for Outcome O1

  • The outcome was generated for ...
  • Configuration parameters were chosen ...
  • ...

3.3 Design for Outcome O2

  • The outcome was generated for ...
  • Configuration parameters were chosen ...
  • ...

...

3.4 Design for Outcome O

  • The outcome was generated for ...
  • Configuration parameters were chosen ...
  • ...

4 Further comments and aspects

5 References

The list of cited or related literature is placed here.