Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Laura Tolosi"'
Autor:
Sven-Eric Schelhorn, Matthias Fischer, Laura Tolosi, Janine Altmüller, Peter Nürnberg, Herbert Pfister, Thomas Lengauer, Frank Berthold
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 10, p e1003228 (2013)
In excess of 12% of human cancer incidents have a viral cofactor. Epidemiological studies of idiopathic human cancers indicate that additional tumor viruses remain to be discovered. Recent advances in sequencing technology have enabled systematic scr
Externí odkaz:
https://doaj.org/article/081e6b01964246ec902348d90bee5083
Autor:
Joern Kamradt, Volker Jung, Kerstin Wahrheit, Laura Tolosi, Joerg Rahnenfuehrer, Martin Schilling, Robert Walker, Sean Davis, Michael Stoeckle, Paul Meltzer, Bernd Wullich
Publikováno v:
PLoS ONE, Vol 2, Iss 8, p e769 (2007)
BACKGROUND: The purpose of this study was to prove the feasibility of a longmer oligonucleotide microarray platform to profile gene copy number alterations in prostate cancer cell lines and to quickly indicate novel candidate genes, which may play a
Externí odkaz:
https://doaj.org/article/2b5c87b477f940c0834a8c74d6f74817
Publikováno v:
Proceedings of the International AAAI Conference on Web and Social Media. 10:151-158
Recently, much attention has been given to models for identifying rumors in social media. Features that are helpful for automatic inference of credibility, veracity, reliability of information have been described. The ultimate goal is to train classi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08b50a12866d6a497074fbeb17b41d5b
https://doi.org/10.1609/icwsm.v10i2.14844
https://doi.org/10.1609/icwsm.v10i2.14844
Publikováno v:
Transactions on Computational Collective Intelligence XXVI ISBN: 9783319592671
Our goal is to build a Food and Drink (FD) gazetteer that can serve for classification of general, FD-related concepts, efficient faceted search or automated semantic enrichment. Fully supervised design of domain-specific models ex novo is not scalab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7a12bac1701b4d73108dfa92bcb3614
https://doi.org/10.1007/978-3-319-59268-8_9
https://doi.org/10.1007/978-3-319-59268-8_9
Publikováno v:
Machine Learning. 98:435-454
The classification models obtained via maximum likelihood-based training do not necessarily reach the optimal $$F_\beta $$Fs-measure for some user's choice of $$\beta $$s that is achievable with the chosen parametrization. In this work we link the we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5132e81748899fb98484243137bad4e1
https://doi.org/10.1007/s10994-014-5439-y
https://doi.org/10.1007/s10994-014-5439-y
Autor:
Konstantin Halachev, Jessica Theißen, Laura Tolosi, Thomas Lengauer, Barbara Hero, Frank Berthold
Publikováno v:
Bioinformatics. 29:1793-1800
Motivation: Recurrent DNA breakpoints in cancer genomes indicate the presence of critical functional elements for tumor development. Identifying them can help determine new therapeutic targets. High-dimensional DNA microarray experiments like arrayCG
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e944d4e7d83e320a82904ecbc55c91f
https://doi.org/10.1093/bioinformatics/btt300
https://doi.org/10.1093/bioinformatics/btt300
Autor:
Laura Tolosi, Thomas Lengauer
Publikováno v:
Bioinformatics. 27:1986-1994
Motivation: Classification and feature selection of genomics or transcriptomics data is often hampered by the large number of features as compared with the small number of samples available. Moreover, features represented by probes that either have s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0de3564cd8bbb84524fd331a638fb791
https://doi.org/10.1093/bioinformatics/btr300
https://doi.org/10.1093/bioinformatics/btr300
Publikováno v:
Bioinformatics. 26:1340-1347
Motivation: In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6340526e960b792f4ac092f54e0a8825
https://doi.org/10.1093/bioinformatics/btq134
https://doi.org/10.1093/bioinformatics/btq134
Autor:
Megan Hanna, Whei F. Moriarty, Craig H. Mermel, Levi A. Garraway, Jürgen Wolf, Adi F. Gazdar, Mirjam Koker, Heidi Greulich, John D. Minna, Tzu Hsiu Chen, Rameen Beroukhim, Jörg Rahnenführer, Takeshi Shimamura, Wendy Winckler, Martin L. Sos, Martin Peifer, Peter Frommolt, Isabel Stückrath, Derek Y. Chiang, Kathrin Michel, Stefanie Heynck, Roland T. Ullrich, Gad Getz, Matthew Meyerson, Stefanie Fischer, Roman K. Thomas, Florian Fischer, Daniel Rauh, Laura Tolosi, William M. Lin, Martin Hellmich, Luc Girard, Danan Li, Barbara A. Weir, Roeland Verhaak, Jordi Barretina, Kinjal Shah, Jonathan Weiss, Michael Peyton, Kwok-Kin Wong, Thomas Zander, Geoffrey I. Shapiro, Thomas LaFramboise
Publikováno v:
Journal of Clinical Investigation. 119:1727-1740
Somatic genetic alterations in cancers have been linked with response to targeted therapeutics by creation of specific dependency on activated oncogenic signaling pathways. However, no tools currently exist to systematically connect such genetic lesi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53549a9be5b265c7dcba9a3ab5bb3fff
https://doi.org/10.1172/jci37127
https://doi.org/10.1172/jci37127
Publikováno v:
Semantic Keyword-Based Search on Structured Data Sources ISBN: 9783319279312
International KEYSTONE Conference
International KEYSTONE Conference
Our goal is to build a Food and Drink FD gazetteer that can serve for classification of general, FD-related concepts, efficient faceted search or automated semantic enrichment. Fully supervised design of a domain-specific models ex novo is not scalab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63531caa1efbc7b3d598ee1d703b2d3e
https://doi.org/10.1007/978-3-319-27932-9_16
https://doi.org/10.1007/978-3-319-27932-9_16