Dr. Cornelia Meckbach
Wissenschaftliche Mitarbeiterin
Aktuelle Homepage:
https://www.thm.de/mni/cornelia-meckbachForschungsinteressen
- Anwendung von maschinellem Lernen auf Bild- und Videodaten (z.B. die visuelle Gewichtsschätzung von Schweinen)
- Statistische Auswertungen von Sensordaten
- Anwendung von informationstheoretische Methoden zur Erstellung und Analyse von sozialen Netzwerken
Mitgliedschaften und Gremienarbeiten
- Campus-Institut Data Science Göttingen (CIDAS)
Wissenschaftliche Abschlüsse
2019 Dr. rer. nat. in Informatik (Georg-August-Universität Göttingen)
Titel: Information theoretical approaches for the identification of potentially cooperating transcription factors
2015 M.Sc. Angewandte Informatik (Georg-August-Universität Göttingen)
2012 B.Sc. Biologie (Georg-August-Universität Göttingen)
Publikationen
- Meckbach, C.; Elsholz, S.; Siede, C.; Traulsen, I. An Information-Theoretic Approach to Detect the Associations of GPS-Tracked Heifers in Pasture. Sensors 2021, 21, 7585. https://doi.org/10.3390/s21227585
- Küster S, Nolte P, Meckbach C, Stock B and Traulsen I (2021) Automatic Behavior and Posture Detection of Sows in Loose Farrowing Pens Based on 2D-Video Images. Front. Anim. Sci. 2:758165. doi: 10.3389/fanim.2021.758165
- Meckbach. C, Tiesmeyer, V, Traulsen I (2021). A promisong approach towards precise animal weight monitoring using convolutional neural networks. Computers and Electronics in Agriculture, 183:106056
- Steuernagel, L, Meckbach, C, Heinrich, F, Zeidler, S, Schmitt, AO, Gültas, M (2019). Computational identification of tissue-specific transcription factor cooperation in ten cattle tissues. PLoS ONE, 14, 5:e0216475.
- Meckbach, C, Wingender, E, Gültas, M (2018). Removing Background Cooccurrences of Transcription Factor Binding Sites Greatly Improves the Prediction of Specific Transcription Factor Cooperations. Front Genet,9:189.
- Dang, T.K.L., Meckbach, C., Tacke, R., Waack, S. and Gültas, M (2016). A novel sequence-based feature for the identification of DNA-binding sites in proteins using Jensen–Shannon Divergence. Entropy 18:379.
- Zeidler,S,Meckbach, C,Tacke,R,Raad,FS,Roa,A,Uchida,S,Zimmermann,WH, Wingender, E, Gültas, M (2016). Computational Detection of Stage-Specific Transcription Factor Clusters during Heart Development. Front Genet, 7:33.
- Meckbach, C, Tacke, R, Hua, X, Waack, S, Wingender, E, Gültas, M (2015). PCTraFF: identification of potentially collaborating transcription factors using pointwise mutual information. BMC Bioinformatics, 16:400.
- Gültas M, Düzgün G, Herzog S, Jäger SJ, Meckbach C, Wingender E, Waack S. (2014). Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming. BMC Bioinformatics, 15:96.