Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Roman Schulte-Sasse"'
Autor:
Hans Juergen Grote, Beatriz Pérez, Sharon Ruane, Lukas Ruff, Maximilian Alber, Annika F Fink, Roman Schulte-Sasse, Martin Bauw, Deepti Agrawal, Mariam Sadeq, Yae Ohata, Thomas Mrowiec
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 11, Iss Suppl 1 (2023)
Externí odkaz:
https://doaj.org/article/3ccf3f5395bf415188d21d861dfda261
Publikováno v:
Nature Machine Intelligence. 3:513-526
The increase in available high-throughput molecular data creates computational challenges for the identification of cancer genes. Genetic as well as non-genetic causes contribute to tumorigenesis, and this necessitates the development of predictive m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::406d9dadf856c5fd26b200e0890c5e91
https://doi.org/10.1038/s42256-021-00325-y
https://doi.org/10.1038/s42256-021-00325-y
Autor:
Thomas Mrowiec, Sharon Ruane, Simon Schallenberg, Gabriel Dernbach, Rumyana Todorova, Cornelius Böhm, Walter de Back, Blanca Pablos, Roman Schulte-Sasse, Ivana Trajanovska, Adelaida Creosteanu, Emil Barbuta, Marcus Otte, Christian Ihling, Hans Juergen Grote, Juergen Scheuenpflug, Viktor Matyas, Maximilian Alber, Frederick Klauschen
Publikováno v:
Cancer Research. 82:457-457
Background: Automated cell-level characterization of the tumor microenvironment (TME) at scale is key to data-driven immuno-oncology. Artificial intelligence (AI)-powered analysis of hematoxylin and eosin (H&E) images scales and has recently been tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8941b464ed1dc3d51b46227e4b5283ef
https://doi.org/10.1158/1538-7445.am2022-457
https://doi.org/10.1158/1538-7445.am2022-457
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions ISBN: 9783030304928
ICANN (Workshop)
ICANN (Workshop)
Despite the vast increase of high-throughput molecular data, the prediction of important disease genes and the underlying molecular mechanisms of multi-factorial diseases remains a challenging task. In this work we use a powerful deep learning classi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b84f0cd54d676f01f6e1ea9e4f250595
https://doi.org/10.1007/978-3-030-30493-5_60
https://doi.org/10.1007/978-3-030-30493-5_60
Autor:
Erika C. Urdaneta, Roman Schulte-Sasse, Annkatrin Bressin, Davide Figini, Annalisa Marsico, Benedikt M. Beckmann
Publikováno v:
Nucleic Acids Res. 47, 4406-4417 (2019)
Nucleic Acids Research
Nucleic Acids Research
In recent years hundreds of novel RNA-binding proteins (RBPs) have been identified leading to the discovery of novel RNA-binding domains (RBDs). Furthermore, unstructured or disordered low-complexity regions of RBPs have been identified to play an im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63aaf9874e65f51b064552961b48a44f
https://doi.org/10.1101/466151
https://doi.org/10.1101/466151
Autor:
Roman Schulte-Sasse, Wolfgang Kopp
Transcription factors (TFs) are important contributors to gene regulation. They specifically bind to short DNA stretches known as transcription factor binding sites (TFBSs), which are contained in regulatory regions (e.g. promoters), and thereby infl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bae9d8ee78a927e13523fa24a4c8ea93
https://doi.org/10.1101/183095
https://doi.org/10.1101/183095