Ghent University Academic Bibliography

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- PhD Thesis
- open access
Statistical methods for differential proteomics at peptide and protein level

Ludger Goeminne

(2019)
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Experimental design and data-analysis in label-free quantitative LC/MS proteomics : a tutorial with MSqRob

Ludger Goeminne, Kris Gevaert (UGent) and Lieven Clement (UGent)

(2018) JOURNAL OF PROTEOMICS. 171. p.23-36
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- Conference Paper
- C3
- open access
MSqRob : analysis of label-free proteomics data in an R/Shiny environment

Ludger Goeminne, Kris Gevaert (UGent) and Lieven Clement (UGent)

(2017) EuBIC Winter School, Abstracts.
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- Conference Paper
- C3
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Analyzing repeated measures designs in label-free proteomics with MSqRob (MCP 2016 15(2):657-68.)

Lieven Clement (UGent) , Ludger Goeminne, Emmy Van Quickelberghe (UGent) and Kris Gevaert (UGent)

(2017) EuBIC Winter School, Abstracts.
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- Conference Paper
- C3
- open access
MSqRob: analysis of label-free proteomics data in an R/Shiny environment

Ludger Goeminne, Emmy Van Quickelberghe (UGent) , Kris Gevaert (UGent) and Lieven Clement (UGent)

(2017) Proteomic Forum, Abstracts.
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- Conference Paper
- C3
Robust peptide-based models in quantitative proteomics

Ludger Goeminne, Klaas Vandepoele (UGent) , Kris Gevaert (UGent) and Lieven Clement (UGent)

(2015) Proteomic Forum, Abstracts.
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- Conference Paper
- C3
- open access
Peptide-level robust ridge regression modeling improves both sensitivity and specificity in quantitative proteomics

Ludger Goeminne, Lieven Clement (UGent) , Kris Gevaert (UGent) and Klaas Vandepoele (UGent)

(2015) MaxQuant summer school, 7th, Abstracts.

Academic Bibliography

Statistical methods for differential proteomics at peptide and protein level

Experimental design and data-analysis in label-free quantitative LC/MS proteomics : a tutorial with MSqRob

MSqRob : analysis of label-free proteomics data in an R/Shiny environment

Analyzing repeated measures designs in label-free proteomics with MSqRob (MCP 2016 15(2):657-68.)

MSqRob: analysis of label-free proteomics data in an R/Shiny environment

Robust peptide-based models in quantitative proteomics

Peptide-level robust ridge regression modeling improves both sensitivity and specificity in quantitative proteomics

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