used to generate a model of ER-stress in vivo. For this, C57B6/J mice received a single intraperitoneal injection of tunicamycin (5 mg/kg), dissolved in 150 mM glucose / 5% DMSO to a concentration of 0 [...] Number of cycle repetitions 1 94 2m 2 94 30s 3 58 1m 4 72 1m 5 72 10m 2 39 6 4 --- 65 USA). Spectrophotometric analysis was used for quantification of cRNA with acceptable A260/A280 ratio of 1.9 to 2.1. After [...] in ice cold radioimmunoprecipitation (RIPA) buffer (2% NP40, 0.5% DOC, 0.1% SDS, 250 mM NaCl, 2.5 mM EDTA, 50 mM Tris pH 7.2) supplemented with protease inhibitors (Protease inhibitor cocktail) and p …

Conference Publications - Chair 3 - Department of Computer Science - TU Dortmund

2007-12 [ WLB07b ] Horst F. Wedde, Sebastian Lehnhoff, Bernhard van Bonn, Z. Bay, S. Becker, S. Boettcher, C. Brunner, A. Buescher, T. Fuerst, A. M. Lazarescu, E. Rotaru, S. Senge, B. Steinbach, F. Yilmaz [...] 2007-09 [ WLB07a ] Horst F. Wedde, Sebastian Lehnhoff, Bernhard van Bonn, Z. Bay, S. Becker, S. Boettcher, C. Brunner, A. Buescher, T. Fuerst, A. M. Lazarescu, E. Rotaru, S. Senge, B. Steinbach, F. Yilmaz [...] Lehnhoff, Bernhard van Bonn, Z. Bay, S. Becker, S. Boettcher, C. Brunner, A. Buescher, T. Fuerst, A. M. Lazarescu, E. Rotaru, S. Senge, B. Steinbach, F. Yilmaz und T. Zimmermann Highly Dynamic and Scalable VANET …

Konferenzpublikationen - Lehrstuhl 3 - Fakultät für Informatik - TU Dortmund

2007-12 [ WLB07b ] Horst F. Wedde, Sebastian Lehnhoff, Bernhard van Bonn, Z. Bay, S. Becker, S. Boettcher, C. Brunner, A. Buescher, T. Fuerst, A. M. Lazarescu, E. Rotaru, S. Senge, B. Steinbach, F. Yilmaz [...] 2007-09 [ WLB07a ] Horst F. Wedde, Sebastian Lehnhoff, Bernhard van Bonn, Z. Bay, S. Becker, S. Boettcher, C. Brunner, A. Buescher, T. Fuerst, A. M. Lazarescu, E. Rotaru, S. Senge, B. Steinbach, F. Yilmaz [...] Lehnhoff, Bernhard van Bonn, Z. Bay, S. Becker, S. Boettcher, C. Brunner, A. Buescher, T. Fuerst, A. M. Lazarescu, E. Rotaru, S. Senge, B. Steinbach, F. Yilmaz und T. Zimmermann Highly Dynamic and Scalable VANET …

SVM – Extensions – Lecture Notes

Vapnik, V. 1995. Extracting support data for a given task. Knowledge discovery and data mining (KDD-95) (1995), 252–257. [SmSc04] Smola, A.J. and Schölkopf, B. 2004. A tutorial on support vector regression. [...] (2004), 199–222. DOI: 10.1023/B:STCO.0000035301.49549.88 [SPSS01] Schölkopf, B., Platt, J.C., Shawe-Taylor, J., Smola, A.J. and Williamson, R.C. 2001. Estimating the support of a high-dimensional distribution [...] Ben-Hur, A., Horn, D., Siegelmann, H.T. and Vapnik, V. 2000. A support vector method for clustering. Advances in neural information processing systems (NIPS) (2000), 367–373. [BHSV01] Ben-Hur, A., Horn, …

SVM – Extensions – Lecture Notes

Vapnik, V. 1995. Extracting support data for a given task. Knowledge discovery and data mining (KDD-95) (1995), 252–257. [SmSc04] Smola, A.J. and Schölkopf, B. 2004. A tutorial on support vector regression. [...] (2004), 199–222. DOI: 10.1023/B:STCO.0000035301.49549.88 [SPSS01] Schölkopf, B., Platt, J.C., Shawe-Taylor, J., Smola, A.J. and Williamson, R.C. 2001. Estimating the support of a high-dimensional distribution [...] Ben-Hur, A., Horn, D., Siegelmann, H.T. and Vapnik, V. 2000. A support vector method for clustering. Advances in neural information processing systems (NIPS) (2000), 367–373. [BHSV01] Ben-Hur, A., Horn, …