Author

Annelaura Bach Nielsen

University of CopenhagenORCID 0009-0005-2855-208XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1 Research Focus:imputation· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Lars Juhl JenseniD· 2 shared Lili NiuiD· 2 shared Matthias ManniD· 2 shared Alberto SantosiD· 1 shared Ana R. Colaço· 1 shared Fabian CosciaiD· 1 shared Filip Oskar MundtiD· 1 shared Henry Emanuel WebeliD· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBioinformatics

Lars Juhl JensenORCID

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2 papers

Recent·Most cited

BioinformaticsNature CommunicationsPeer-reviewedJun 26, 2024

Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning

Henry Emanuel Webel, Lili Niu, Annelaura Bach Nielsen…·Simon Rasmussen

This paper introduces a deep learning method for imputing missing values in label-free quantitative proteomics data and shows its effectiveness in identifying differentially abundant proteins in alcohol-related liver disease.

65 citationstop 1%

humanproteomics

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BioinformaticsbioRxivPreprintMay 9, 2020

Clinical Knowledge Graph Integrates Proteomics Data into Clinical Decision-Making

Alberto Santos, Ana R. Colaço, Annelaura Bach Nielsen…·Matthias Mann

The Clinical Knowledge Graph (CKG) links over 16 million nodes and 220 million relationships with statistical and machine learning workflows to accelerate proteomics data analysis and clinical biomarker interpretation.

58 citations

proteomicsstatistical model

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