Zobrazeno 1 - 10
of 304
pro vyhledávání: '"Jansen Ritsert C"'
Publikováno v:
BMC Bioinformatics, Vol 11, Iss 1, p 497 (2010)
Abstract Background Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differentially expressed genes between two conditions, the field of dif
Externí odkaz:
https://doaj.org/article/379060c464704520944c31dfd8ac6697
Autor:
Bonin Michael, Wild David L, Rand David A, Dijkhuizen Lubbert, Jansen Ritsert C, Challis Gregory L, Legaie Roxane, Gaze William H, Iqbal Mudassar, Thomas Louise, Nentwich Merle, Rodríguez-García Antonio, Juarez-Hermosillo Miguel A, Morrissey Edward R, Omara Walid AM, Moore Jonathan, Merlo Maria E, Alam Mohammad T, Sletta Håvard, Jakobsen Øyvind M, Wentzel Alexander, Bruheim Per, Herbig Alexander, Battke Florian, Nieselt Kay, Reuther Jens, Wohlleben Wolfgang, Smith Margaret CM, Burroughs Nigel J, Martín Juan F, Hodgson David A, Takano Eriko, Breitling Rainer, Ellingsen Trond E, Wellington Elizabeth MH
Publikováno v:
BMC Genomics, Vol 11, Iss 1, p 10 (2010)
Abstract Background During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a
Externí odkaz:
https://doaj.org/article/aefdd039c17547fbb95acebc73dd8884
Publikováno v:
BMC Bioinformatics, Vol 10, Iss 1, p 188 (2009)
Abstract Background High-dimensional biomolecular profiling of genetically different individuals in one or more environmental conditions is an increasingly popular strategy for exploring the functioning of complex biological systems. The optimal desi
Externí odkaz:
https://doaj.org/article/68f71fc0acaf4ffbb17fcda2a315ab74
Autor:
Dinesen Lotte C, Swertz Morris A, Bruinenberg Marcel, Jansen Ritsert C, Trynka Gosia, Heap Graham A, Hunt Karen A, Wijmenga Cisca, vanHeel David A, Franke Lude
Publikováno v:
BMC Medical Genomics, Vol 2, Iss 1, p 1 (2009)
Abstract Background Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown. Methods We correl
Externí odkaz:
https://doaj.org/article/00ad231591ab48929d1c1fefe767dbf4
Publikováno v:
BMC Bioinformatics, Vol 9, Iss 1, p 390 (2008)
Abstract Background R is the preferred tool for statistical analysis of many bioinformaticians due in part to the increasing number of freely available analytical methods. Such methods can be quickly reused and adapted to each particular experiment.
Externí odkaz:
https://doaj.org/article/e1e7d51b69c1425face504776a915f06
Autor:
Nap Jan-Peter, Breitling Rainer, de Haan Gerald, Bystrykh Leonid V, Hardonk Menno, Terpstra Peter, Alberts Rudi, Jansen Ritsert C
Publikováno v:
BMC Bioinformatics, Vol 8, Iss 1, p 132 (2007)
Abstract Background The Affymetrix GeneChip technology uses multiple probes per gene to measure its expression level. Individual probe signals can vary widely, which hampers proper interpretation. This variation can be caused by probes that do not pr
Externí odkaz:
https://doaj.org/article/971318f6b5734b7c85ec4614e1b1571d