Design and implementation of a machine learning algorithm to improve MaxQuant’s 
inference process of precursor fragment groups in data-independent shotgun 
proteomics

Restrepo Lopez, Juan Luis

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Thesis

Design and implementation of a machine learning algorithm to improve MaxQuant’s inference process of precursor fragment groups in data-independent shotgun proteomics

MPS-Authors

Restrepo Lopez, Juan Luis
Duderstadt, Karl / Structure and Dynamics of Molecular Machines, Max Planck Institute of Biochemistry, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Restrepo Lopez, J. L. (2021). Design and implementation of a machine learning algorithm to improve MaxQuant’s inference process of precursor fragment groups in data-independent shotgun proteomics. Master Thesis, Technische Universität, Fakultät für Physik, München.

Cite as: https://hdl.handle.net/21.11116/0000-000C-9B65-4

Abstract

There is no abstract available