Zobrazeno 1 - 10
of 142
pro vyhledávání: '"M Borgwardt"'
Autor:
R Al-Obaidi, M Wilke, M Borgwardt, J Metje, A Moguilevski, N Engel, D Tolksdorf, A Raheem, T Kampen, S Mähl, I Yu Kiyan, E F Aziz
Publikováno v:
New Journal of Physics, Vol 17, Iss 9, p 093016 (2015)
The method of time-resolved XUV photoelectron spectroscopy is applied in a pump–probe experiment on a liquid micro-jet. We investigate how the XUV energy spectra of photoelectrons are influenced by the space charge created due to ionization of the
Externí odkaz:
https://doaj.org/article/a2aa30cc10924bdaa5263443091e89e6
Autor:
Kemal Avican, Jehad Aldahdooh, Matteo Togninalli, A. K. M. Firoj Mahmud, Jing Tang, Karsten M. Borgwardt, Mikael Rhen, Maria Fällman
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Bacterial stress responses are potential targets for new antimicrobials. Here, Avican et al. present global transcriptomes for 32 bacterial pathogens grown under 11 stress conditions, and identify common and unique regulatory responses, as well as pr
Externí odkaz:
https://doaj.org/article/528c32ad693d42ecb0d3a057d1175df3
Publikováno v:
Bioinformatics
While the search for associations between genetic markers and complex traits has led to the discovery of tens of thousands of trait-related genetic variants, the vast majority of these only explain a small fraction of observed phenotypic variation. O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a4f5e48d13516e23091f188bc7c99e7
https://hdl.handle.net/21.11116/0000-000C-F04F-D
https://hdl.handle.net/21.11116/0000-000C-F04F-D
Publikováno v:
Clinical Microbiology and Infection, 26 (10)
Clinical Microbiology and Infection
Clinical Microbiology and Infection
Background The matrix assisted laser desorption/ionization and time-of-flight mass spectrometry (MALDI-TOF MS) technology has revolutionized the field of microbiology by facilitating precise and rapid species identification. Recently, machine learnin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e32007ac5b86417ff72db114cfbd09bf
https://doi.org/10.1016/j.cmi.2020.03.014
https://doi.org/10.1016/j.cmi.2020.03.014
Autor:
Anja C Gumpinger, Karsten M. Borgwardt, Christian Beisel, Katrin Fischer, Laetitia Papaxanthos, Markus Jeschek, Yaakov Benenson, Simon Hoellerer
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
Nature Communications
Nature Communications, 11 (1)
Nature Communications
Nature Communications, 11 (1)
Predicting effects of gene regulatory elements (GREs) is a longstanding challenge in biology. Machine learning may address this, but requires large datasets linking GREs to their quantitative function. However, experimental methods to generate such d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::924dd0ac979d603ba9dd553fdd6f2237
https://doaj.org/article/5cdab11544394bd78e7fc3880bbaa8e2
https://doaj.org/article/5cdab11544394bd78e7fc3880bbaa8e2
Publikováno v:
Bioinformatics
Bioinformatics, 36 (1)
Bioinformatics, 36 (1)
Motivation Gaining a comprehensive understanding of the genetics underlying cancer development and progression is a central goal of biomedical research. Its accomplishment promises key mechanistic, diagnostic and therapeutic insights. One major step
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::612cdf944bf73fb9dbcff076d855ea05
http://europepmc.org/articles/PMC7355253
http://europepmc.org/articles/PMC7355253
Publikováno v:
Bioinformatics, 37 (1)
Bioinformatics
Bioinformatics
Motivation Correlating genetic loci with a disease phenotype is a common approach to improve our understanding of the genetics underlying complex diseases. Standard analyses mostly ignore two aspects, namely genetic heterogeneity and interactions bet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8df72b767f1b0d1926f8dc52e7fb2e4
https://doi.org/10.1093/bioinformatics/btaa581
https://doi.org/10.1093/bioinformatics/btaa581
Publikováno v:
Foundations and Trends® in Machine Learning
Graph-structured data are an integral part of many application domains, including chemoinformatics, computational biology, neuroimaging, and social network analysis. Over the last two decades, numerous graph kernels, i.e. kernel functions between gra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::512d61a8912a421a446186bae3302e45
https://doi.org/10.1561/2200000076
https://doi.org/10.1561/2200000076
Autor:
Sarah C Brüningk, Juliane Klatt, Madlen Stange, Alfredo Mari, Myrta Brunner, Tim-Christoph Roloff, Helena M B Seth-Smith, Michael Schweitzer, Karoline Leuzinger, Kirstine K Søgaard, Diana Albertos Torres, Alexander Gensch, Ann-Kathrin Schlotterbeck, Christian H Nickel, Nicole Ritz, Ulrich Heininger, Julia Bielicki, Katharina Rentsch, Simon Fuchs, Roland Bingisser, Martin Siegemund, Hans Pargger, Diana Ciardo, Olivier Dubuis, Andreas Buser, Sarah Tschudin-Sutter, Manuel Battegay, Rita Schneider-Sliwa, Karsten M Borgwardt, Hans H Hirsch, Adrian Egli
Publikováno v:
medRxiv
Virus Evolution
Virus Evolution
Background Transmission chains within small urban areas (accommodating∼30% of the European population) greatly contribute to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a focus for preventive measures to achi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::febfd1175c8a148402054adcdc291cac
https://edoc.unibas.ch/95288/
https://edoc.unibas.ch/95288/
Autor:
Karsten M. Borgwardt, Alejandro Tejada-Arranz, Michael F. Adamer, Fabienne Estermann, Sarah C. Brueningk, Marek Basler
Publikováno v:
Bioinformatics Advances. 2
MotivationWith the steadily increasing abundance of omics data produced all over the world under vastly different experimental conditions residing in public databases, a crucial step in many data-driven bioinformatics applications is that of data int
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76ab2157a6a9feb82346e321415fe9fd
https://doi.org/10.1093/bioadv/vbac071
https://doi.org/10.1093/bioadv/vbac071