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Akademický článek

Tetrahydrobiopterin protects soluble guanylate cyclase against oxidative inactivation

Autor: Schmidt Kurt, Werner Ernst R., Mayer Bernd

Publikováno v: Pteridines, Vol 24, Iss 1, Pp 47-50 (2013)

Tetrahydrobiopterin (BH4) is a major endogenous vasoprotective agent that improves endothelial function by increasing nitric oxide (NO) synthesis and scavenging of superoxide and peroxynitrite. Accordingly, administration of BH4 is considered as a pr

Externí odkaz: https://doaj.org/article/50b71336357d4ae0823c5a482ae5fb33

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Akademický článek

In-silico human genomics with GeneCards

Autor: Stelzer Gil, Dalah Irina, Stein Tsippi, Satanower Yigeal, Rosen Naomi, Nativ Noam, Oz-Levi Danit, Olender Tsviya, Belinky Frida, Bahir Iris, Krug Hagit, Perco Paul, Mayer Bernd, Kolker Eugene, Safran Marilyn, Lancet Doron

Publikováno v: Human Genomics, Vol 5, Iss 6, Pp 709-717 (2011)

Abstract Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org). This human gene compendium was created to help t

Externí odkaz: https://doaj.org/article/bef8d9048b6e4d2d92113f6db1079779

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Akademický článek

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Akademický článek

Chemoresistance acquisition induces a global shift of expression of aniogenesis-associated genes and increased pro-angogenic activity in neuroblastoma cells

Autor: Doerr Hans W, Hinsch Nora, Mayer Bernd, Breitling Rainer, Suhan Tatyana, Barth Susanne, Klassert Denise, Michaelis Martin, Cinatl Jaroslav, Cinatl Jindrich

Publikováno v: Molecular Cancer, Vol 8, Iss 1, p 80 (2009)

Abstract Background Chemoresistance acquisition may influence cancer cell biology. Here, bioinformatics analysis of gene expression data was used to identify chemoresistance-associated changes in neuroblastoma biology. Results Bioinformatics analysis

Externí odkaz: https://doaj.org/article/548e5fb2f7e74fe2b6a5ccab32610e1c

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Akademický článek

Characterization of protein-interaction networks in tumors

Autor: Lukas Arno, Perco Paul, Platzer Alexander, Mayer Bernd

Publikováno v: BMC Bioinformatics, Vol 8, Iss 1, p 224 (2007)

Abstract Background Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be formally represented as graphs, and approximating PINs as undirect

Externí odkaz: https://doaj.org/article/8bc0b142df014f3f863402247595356a

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