Author

Marika Kaden

Hochschule MittweidaORCID 0000-0002-2849-3463Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:machine learning (classical)· 2 Research Focus:protein structure prediction· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Research Focus:gene regulatory network inference· 1 Assay:protein sequence· 1 Assay:protein structure· 1

Frequent Co-Authors

Thomas VillmanniD· 3 shared Christoph LeberechtiD· 2 shared Katrin Sophie BohnsackiD· 2 shared Mirko WeberiD· 2 shared Dirk LabuddeiD· 1 shared Florian KaiseriD· 1 shared Jacek BłażewicziD· 1 shared Julia AbeliD· 1 shared

Activity by Year

2019-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersBioinformatics

Thomas VillmannORCID

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3 papers

Recent·Most cited

Detection of native and mirror protein structures based on Ramachandran plot analysis by interpretable machine learning models

Julia Abel, Marika Kaden, Katrin Sophie Bohnsack, Mirko Weber, Christoph Leberecht, Thomas Villmann

The paper uses interpretable machine learning to classify protein structures as native or mirror based on Ramachandran plot analysis with high accuracy.

bioRxiv · Sep 3, 2020 · PreprintBioinformatics

Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models

Marika Kaden, Katrin Sophie Bohnsack, Mirko Weber, Mateusz Kudła, Kaja Gutowska, Jacek Błażewicz, Thomas Villmann

The paper applies interpretable machine learning to classify and analyze SARS-CoV-2 sequences, identifying potential new virus types through rejected classifications.

bioRxiv · May 15, 2020 · PreprintBioinformatics

Application of an Interpretable Classification Model on Early Folding Residues during Protein Folding

Sebastian Bittrich, Marika Kaden, Christoph Leberecht, Florian Kaiser, Thomas Villmann, Dirk Labudde

The paper applies GMLVQ to predict early folding residues in proteins, achieving 76.6% AUC and highlighting the importance of secondary structure and hydrophobic networks.

BioData Mining · Jan 5, 2019Peer-reviewedBioinformatics