Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Alexander eGoesmann"'
Autor:
Patrick eSobetzko, Lukas eJelonek, Marc eStrickert, Wenxia eHan, Alexander eGoesmann, Torsten eWaldminghaus
Publikováno v:
Frontiers in Microbiology, Vol 7 (2016)
Short DNA motifs are involved in a multitude of functions such as for example chromosome segregation, DNA replication or mismatch repair. Distribution of such motifs is often not random and the specific chromosomal pattern relates to the respective m
Externí odkaz:
https://doaj.org/article/0ac73b41fb2b42f98346334c7c23d5e9
Autor:
Daniel eLangenkaemper, Tobias eJakobi, Dustin eFeld, Lukas eJelonek, Alexander eGoesmann, Tim Wilhelm Nattkemper
Publikováno v:
Frontiers in Genetics, Vol 7 (2016)
Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly g
Externí odkaz:
https://doaj.org/article/b0b9059f497f4cca8f9454219124eac8
Autor:
Tilman Gunter Schultze, Rolf eHilker, Gopala Krishna Mannala, Katrin eGentil, Markus eWeigel, Neda eFarmani, Anita C. Windhorst, Alexander eGoesmann, Trinad eChakraborty, Torsten eHain
Publikováno v:
Frontiers in Microbiology, Vol 6 (2015)
Listeria monocytogenes is a bacterial pathogen and causative agent for the foodborne infection listeriosis, which is mainly a threat for pregnant, elderly or immunocompromised individuals. Due to its ability to invade and colonize diverse eukaryotic
Externí odkaz:
https://doaj.org/article/7e8b83ccc0924eb187d4ddb2f15044be
Autor:
Nikolas eKessler, Anja eBonte, Stefan P Albaum, Paul eMäder, Monika eMessmer, Alexander eGoesmann, Karsten eNiehaus, Georg eLangenkämper, Tim W Nattkemper
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 3 (2015)
We present results of our machine learning approach to the problem of classifying GC-MS data originating from wheat grains of different farming systems. The aim is to investigate the potential of learning algorithms to classify GC-MS data to be eithe
Externí odkaz:
https://doaj.org/article/b61689df3d574195a2c0d6e5fb585570
Autor:
Claire eBertelli, Sébastien eAeby, Bérénice eChassot, James eClulow, Olivier eHilfiker, Samuel eRappo, Sébastien eRitzmann, Paolo eSchumacher, Céline eTerrettaz, Paola eBenaglio, Laurent eFalquet, Laurent eFarinelli, Walid eGharib, Alexander eGoesmann, Keith eHarshman, Burkhard eLinke, Ryo eMiyazaki, Carlo eRivolta, Marc eRobinson-Rechavi, Jan Roelof eVan Der Meer, Gilbert eGreub
Publikováno v:
Frontiers in Microbiology, Vol 6 (2015)
With the widespread availability of high-throughput sequencing technologies, sequencing projects have become pervasive in the molecular life sciences. The huge bulk of data generated daily must be analyzed further by biologists with skills in bioinfo
Externí odkaz:
https://doaj.org/article/9fd0273f2b1746a0b86021b3a6f609a6