Bohnsack, Katrin Sophie

M.Sc.

Positionen

Mitarbeiterin, Fachgruppe Mathematik, Fakultät Angewandte Computer- und Biowissenschaften

Forschungsschwerpunkt

Angewandte Informatik Forschungsschwerpunkt

Projektmitgliedschaft

Interpretierbare KI für die Analyse von Gene-Expressionsdaten finanziert durch Bundesministerium für Wirtschaft und Klimaschutz 2022 - 2025
Kl-unterstütze Optimierung des Einsatzes von NIR/MIR-Sensoren in der Landwirtschaft finanziert durch Bundesanstalt für Landwirtschaft und Ernährung 2021 - 2024
Nachwuchsforschergruppe MaLeKITA Maschinelles Lernen und KI in Theorie und Anwendungen, MaLeKITA Anwendungen Theorie finanziert durch Sächsische Aufbaubank 2020 - 2022

ausgewählte Publikationen

Journalartikel
- Multi-proximity based embedding scheme for learning vector quantization-based classification of biochemical structured data. Neurocomputing. 126632. 2023
- Alignment-free sequence comparison: A systematic survey from a machine learning perspective. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 119-135. 2022
- Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences. Neural Computing and Applications. 2021
- The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy. 1357. 2021
- Virxicon: a lexicon of viral sequences. Bioinformatics. 5507-5513. 2021
Konferenzpaper
- Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge. Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS. 357-367. 2024
- Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings. Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS. 59-69. 2023
- Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection. ESANN 2023 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 65-70. 2023
- Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features. ESANN 2022 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 445-450. 2022

Präsentationen auf Veranstaltungen

Teilnahme an Veranstaltungen

14th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization 2022

ORCID iD

https://orcid.org/0000-0002-2361-107X (bestätigt)

vollständiger Name

Katrin Sophie Bohnsack

KoautorInnen-Netzwerk

Koforscher-Netzwerk

Kontaktdaten

bohnsac1@hs-mittweida.de