Publications

Marc Hellmuth, David Schaller, und Peter F. Stadler. Clustering systems of phylogenetic networks. Theory in Biosciences, (142)4:301–358, Springer Science and Business Media LLC, August 2023. [PUMA: Clustering networks phylogenetic systems zno] URL

Johannes R. Schmidt, Janine Haupt, Sina Riemschneider, Christoph Kämpf, Dennis Löffler, Conny Blumert, Kristin Reiche, Ulrike Koehl, Stefan Kalkhof, und Jörg Lehmann. Transcriptomic signatures reveal a shift towards an anti-inflammatory gene expression profile but also the induction of type I and type II interferon signaling networks through aryl hydrocarbon receptor activation in murine macrophages. Frontiers in Immunology, (14)Frontiers Media SA, Mai 2023. [PUMA: Transcriptomic activation anti-inflammatory aryl expression gene hydrocarbon induction interferon macrophages murine networks profile receptor signaling signatures through zno] URL

Aris Marcolongo, Mykhailo Vladymyrov, Sebastian Lienert, Nadav Peleg, Sigve Haug, und Jakob Zscheischler. Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks. Environmental Data Science, (1):e2, 2022. [PUMA: Convolutional Predicting data gross low primary production weather zno networks neural]

Jingyu Shao, Qing Wang, Asiri Wijesinghe, und Erhard Rahm. ErGAN: Generative adversarial networks for entity resolution. arXiv, 2020. [PUMA: ErGAN Generative adversarial entity networks resolution zno]

Lucas Schneider, Sara Laiouar-Pedari, Sara Kuntz, Eva Krieghoff-Henning, Achim Hekler, Jakob N Kather, Timo Gaiser, Stefan Fröhling, und Titus J Brinker. Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review. Eur. J. Cancer, (160):80--91, Elsevier BV, Januar 2022. [PUMA: Biomarker Cancer Convolutional Multimodal Omics fusion identification networks neural topic_lifescience zno]

Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman D Buelow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J Brinker, Firas Khader, Daniel Truhn, Nadine T Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, und Jakob Nikolas Kather. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, Juli 2022. [PUMA: Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep learning neural topic_lifescience transformers; zno artificial intelligence pathology networks]