Author

Daniel P. Gomari

Helmholtz Munich

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:metabolomics· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Research Focus:drug response / drug discovery· 1 Approach:statistical model· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Jan KrumsiekiD· 2 shared Anna HalamaiD· 1 shared Annalise SchweickartiD· 1 shared Elisa BenedettiiD· 1 shared Elisabeth M. PaiettaiD· 1 shared Hassen A. Al-AminiD· 1 shared Hugo Francisco FernandeziD· 1 shared Iman W. AchkariD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersSystems Biology

Jan KrumsiekORCID

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Author profile →

2 papers

Recent·Most cited

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets

Daniel P. Gomari, Iman W. Achkar, Elisa Benedetti, Jan Tabling, Anna Halama, Jan Krumsiek

piTracer identifies synergistic drug targets by analyzing metabolomics data to reconstruct molecular cascades and predict combination therapies.

bioRxiv · Apr 8, 2023 · PreprintSystems Biology

Variational autoencoders learn universal latent representations of metabolomics data

Daniel P. Gomari, Annalise Schweickart, Leandro C. A. Cerchietti, Elisabeth M. Paietta, Hugo Francisco Fernandez, Hassen A. Al-Amin, Karsten Suhre, Jan Krumsiek

This study trains a variational autoencoder on metabolomics data to learn nonlinear latent representations and validates its generalizability across different disease cohorts.

bioRxiv · Jan 14, 2021 · PreprintBioinformatics