(Q51727522)

English

The principle of exhaustiveness versus the principle of parsimony: a new approach for the identification of biomarkers from proteomic spot volume datasets based on principal component analysis.

scientific article published on 21 January 2010

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scholarly article

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

The principle of exhaustiveness versus the principle of parsimony: a new approach for the identification of biomarkers from proteomic spot volume datasets based on principal component analysis. (English)

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

principal component analysis

0 references

1 reference

based on heuristic

inferred from title

4

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

2

object named as

Elisa Robotti

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

author name string

Emilio Marengo

1

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

Marco Bobba

3

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

language of work or name

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publication date

21 January 2010

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

Analytical and Bioanalytical Chemistry

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Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

397

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

1

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

25-41

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

https://scigraph.springernature.com/pub.10.1007/s00216-009-3390-8

0 references

The association of 83 plasma proteins with CHD mortality, BMI, HDL-, and total-cholesterol in men: applying multivariate statistics to identify proteins with prognostic value and biological relevance

1 reference

https://api.crossref.org/works/10.1007%2FS00216-009-3390-8

21 January 2018

Methods of quantitative proteomics and their application to plant organelle characterization

1 reference

https://api.crossref.org/works/10.1007%2FS00216-009-3390-8

21 January 2018

Evaluation of the variables characterized by significant discriminating power in the application of SIMCA classification method to proteomic studies

1 reference

https://api.crossref.org/works/10.1007%2FS00216-009-3390-8

21 January 2018

Study of proteomic changes associated with healthy and tumoral murine samples in neuroblastoma by principal component analysis and classification methods.

1 reference

https://api.crossref.org/works/10.1007%2FS00216-009-3390-8

21 January 2018

Application of partial least squares discriminant analysis and variable selection procedures: a 2D-PAGE proteomic study.

1 reference

https://api.crossref.org/works/10.1007%2FS00216-009-3390-8

21 January 2018

Identifiers

10.1007/S00216-009-3390-8

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

PubMed publication ID

1 reference

Europe PubMed Central

PubMed publication ID

10 April 2018

http://europepmc.org/abstract/MED/20091299

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