TY  - JOUR
A1  - Kurulgan Demirci, Eylem
A1  - Demirci, T.
A1  - Trzewik, Jürgen
A1  - Linder, Peter
A1  - Karakulah, G.
A1  - Artmann, Gerhard
A1  - Sakizli, M.
A1  - Temiz Artmann, Aysegül
T1  - Genome-Wide Gene Expression Analysis of NIH 3T3 Cell Line Under Mechanical Stimulation
JF  - Cellular and molecular bioengineering. 4 (2011), H. 1
Y1  - 2011
SN  - 1865-5025
SP  - 46
EP  - 55
PB  - Springer
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Huck, Christina
A1  - Jolly, Christina
A1  - Wagner, Patrick
A1  - Poghossian, Arshak
A1  - Schöning, Michael Josef
T1  - One-chip integrated dual amperometric/field-effect sensor for the detection of dissolved hydrogen
JF  - Procedia Engineering. 25 (2011)
Y1  - 2011
SN  - 1877-7058
N1  - EurosensorsXXV ; Proc. Eurosensors XXV, September 4-7, 2011, Athens, Greece
SP  - 1161
EP  - 1164
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Bialonski, Stephan
A1  - Wendler, Martin
A1  - Lehnertz, Klaus
T1  - Unraveling spurious properties of interaction networks with tailored random networks
JF  - Plos one
N2  - We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.
Y1  - 2011
U6  - https://doi.org/10.1371/journal.pone.0022826
VL  - 6
IS  - 8
PB  - Plos
CY  - San Francisco
ER  - 
TY  - JOUR
A1  - Arida, Hassan A.
A1  - Al-Haddad, Ameera
A1  - Schöning, Michael Josef
T1  - New Solid-State Organic Membrane Based Lead-Selective Micro-Electrode
JF  - International Journal of Electrochemical Science. 6 (2011), H. 9
Y1  - 2011
SN  - 1452-3981
SP  - 3858
EP  - 3867
ER  - 
TY  - JOUR
A1  - Grinsven, Bart van
A1  - Vanden Bon, Natalie
A1  - Grieten, Lars
A1  - Murib, Mohammed Sharif
A1  - Janssen, Stoffel Dominique
A1  - Haenen, Ken
A1  - Schneider, E.
A1  - Ingebrandt, Sven
A1  - Schöning, Michael Josef
A1  - Vermeeren, Veronique
A1  - Ameloot, Marcel
A1  - Michiels, Luc
A1  - Thoelen, Ronald
A1  - De Ceuninck, Ward A.
A1  - Wagner, Patrick
T1  - Rapid assessment of the stability of DNA duplexes by impedimetric real-time monitoring of chemically induced denaturation
JF  - Lab on a Chip
Y1  - 2011
SN  - 1473-0197
VL  - 11
IS  - 9
SP  - 1656
EP  - 1663
PB  - Royal Society of Chemistry (RSC)
CY  - Cambridge
ER  -