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Number of items: 4.

Tarca, A. L. ; Lauria, M. ; Unger, M. ; Bilal, E. ; Boue, S. ; Kumar Dey, K. ; Hoeng, J. ; Koeppl, H. ; Martin, F. ; Meyer, P. ; Nandy, P. ; Norel, R. ; Peitsch, M. ; Rice, J. ; Romero, R. ; Stolovitzky, G. ; Talikka, M. ; Xiang, Y. ; Zechner, C. (2013):
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge.
In: Bioinformatics (Oxford, England), 29 (22), pp. 2892-2899. [Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Dey, K. ; Koeppl, H. (2013):
Learning diagnostic signatures from microarray data using Ll-regularized logistic regression.
In: Systems Biomedicine, 1 (4), Taylor & Francis, [Article]

Zechner, C. ; Nandy, P. ; Unger, M. ; Koeppl, H. (2012):
Optimal variational perturbations for the inference of stochastic reaction dynamics.
pp. 5336-5341, IEEE, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), [Conference or Workshop Item]

Nandy, P. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2012):
Optimal Perturbations for the Identification of Stochastic Reaction Dynamics.
pp. 686-691, Elsevier, 16th IFAC Symposium on System Identification, [Conference or Workshop Item]

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