Sebastian Vlaic
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Explore the profile of Sebastian Vlaic including associated specialties, affiliations and a list of published articles.
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17
Citations
197
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Recent Articles
11.
Guthke R, Gerber S, Conrad T, Vlaic S, Durmus S, Cakir T, et al.
Front Microbiol
. 2016 May;
7:570.
PMID: 27148247
In the emerging field of systems biology of fungal infection, one of the central roles belongs to the modeling of gene regulatory networks (GRNs). Utilizing omics-data, GRNs can be predicted...
12.
Feuer R, Vlaic S, Arlt J, Sawodny O, Dahmen U, Zanger U, et al.
PLoS One
. 2015 Sep;
10(9):e0135852.
PMID: 26325269
Background: Gene expression analysis is an essential part of biological and medical investigations. Quantitative real-time PCR (qPCR) is characterized with excellent sensitivity, dynamic range, reproducibility and is still regarded to...
13.
Bottger J, Arnold K, Thiel C, Rennert C, Aleithe S, Hofmann U, et al.
Arch Toxicol
. 2015 Aug;
89(9):1579-88.
PMID: 26233687
Primary hepatocyte cell cultures are widely used for studying hepatic diseases with alterations in hepatic glucose and lipid metabolism, such as diabetes and non-alcoholic fatty liver disease. Therefore, small interfering...
14.
Kupfer P, Huber R, Weber M, Vlaic S, Haupl T, Koczan D, et al.
BMC Med Genomics
. 2014 Jul;
7:40.
PMID: 24989895
Background: Network inference of gene expression data is an important challenge in systems biology. Novel algorithms may provide more detailed gene regulatory networks (GRN) for complex, chronic inflammatory diseases such...
15.
GRN2SBML: automated encoding and annotation of inferred gene regulatory networks complying with SBML
Vlaic S, Hoffmann B, Kupfer P, Weber M, Drager A
Bioinformatics
. 2013 Jun;
29(17):2216-7.
PMID: 23803467
Unlabelled: GRN2SBML automatically encodes gene regulatory networks derived from several inference tools in systems biology markup language. Providing a graphical user interface, the networks can be annotated via the simple...
16.
Weber M, Henkel S, Vlaic S, Guthke R, van Zoelen E, Driesch D
BMC Syst Biol
. 2013 Jan;
7:1.
PMID: 23280066
Background: Inference of gene-regulatory networks (GRNs) is important for understanding behaviour and potential treatment of biological systems. Knowledge about GRNs gained from transcriptome analysis can be increased by multiple experiments...
17.
Vlaic S, Schmidt-Heck W, Matz-Soja M, Marbach E, Linde J, Meyer-Baese A, et al.
BMC Syst Biol
. 2012 Nov;
6:147.
PMID: 23190768
Background: Network inference is an important tool to reveal the underlying interactions of biological systems. In the liver, a complex system of transcription factors is active to distribute signals and...