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321.
Mewes, H.-W. et al.: MIPS: Curated databases and comprehensive secondary data resources in 2010. Nucleic Acids Res. 39, 1, D220-D224 (2010)
322.
Meyer-Bäse, A.* ; Theis, F.J. & Emmett, M.R.*: Robust stability analysis and design under consideration of multiple feedback loops of the tryptophan regulatory network of Escherichia coli. Adv. Exp. Med. Biol. 680, 189-197 (2010)
323.
Meyer-Bäse, A.* ; Plant, C.* ; Cappendijk, S.* & Theis, F.J.: Robust stability analysis of multi-time scale genetic regulatory networks under parametric uncertainties. In: Proceedings (BIOCOMP'10 - The 2010 International Conference on Bioinformatics & Computational Biology). Las Vegas (Nevada): CSREA Press, 2010.
324.
Plant, C.* ; Theis, F.J. ; Meyer-Bäse, A.* & Böhm, C.*: Information-theoretic model selection for independent components. In: Vigneron, V.* ; Zarzoso, V.* ; Moreau, E.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Berlin: Springer, 2010. 254-262 (Lecture Notes Comp. Sci. ; 6365)
325.
Ruepp, A. et al.: PhenomiR: A knowledgebase for microRNA expression in diseases and biological processes. Genome Biol. 11:R6 (2010)
326.
Theis, F.J. ; Müller, N.S.* ; Plant, C.* & Böhm, C.*: Robust second-order source separation identifies experimental responses in biomedical imaging. In: Vigneron, V.* [Eds.]: Proceedings (Latent variable analysis and signal separation : 9th international conference, 27-30 September 2010, St. Malo, France). Heidelberg: Springer, 2010. 466-473 (LNCS; 6365)
327.
Theis, F.J.: Colored subspace analysis: Dimension reduction based on a signal's autocorrelation structure. IEEE Trans. Circuits Syst. I-Regul. Pap. 57, 1463-1474 (2010)
328.
Theis, F.J. & Meyer-Bäse, A.: Foundations of medical imaging and signal recording. In: Biomedical Signal Analysis - Contemporary Methods and Applications. Cambridge, MA: MIT Press, 2010. 1-28
329.
Theis, F.J. & Meyer- Bäse, A.*: Biomedical signal analysis: Contemporary methods and applications. Cambridge, Mass.: MIT Press, 2010. 432 S.
330.
Thiemann, C.* ; Theis, F.J. ; Grady, D.* ; Brune, R.* & Brockmann, D.*: The structure of borders in a small world. PLoS ONE 5:e15422 (2010)
331.
Wittmann, D.M. ; Marr, C. & Theis, F.J.: Biologically meaningful update rules increase the critical connectivity of generalized Kauffman networks. J. Theor. Biol. 266, 436-448 (2010)
332.
Blöchl, F. & Theis, F.J.: Estimating hidden influences in metabolic and gene regulatory networks. In: Adali, T.* [Eds.]: Independent Component Analysis and Signal Separation. Berlin: Springer, 2009. 387-394 (Lecture Notes Comp. Sci. ; 5441)
333.
Georgiev, P.G.* & Theis, F.J.: Optimization techniques for data representions with biomedical applications. In: Romejin, H.E.* ; Pardalos, P.M.* [Eds.]: Handbook of Optimization in Medicine. New York: Springer, 2009. 1-38 (Springer Optimization and Its Applications ; 26)
334.
Georgiev, P.G.* & Theis, F.J.: Optimization techniques for data representations with biomedical applications. In: Pardalos, P.M.* ; Romejin, H.E.* [Eds.]: Handbook of Optimization in Medicine. New York: Springer Science + Business Media B.V., 2009. 253-290
335.
Gruber, P.* ; Gutch, H.W.* & Theis, F.J.: Hierarchical extraction of independent subspaces of unknown dimensions. In: Adali, T.* [Eds.]: Independent Component Analysis and Signal Separation. Berlin: Springer, 2009. 259-266 (Lecture Notes Comp. Sci. ; 5441)
336.
Gruber, P. ; Meyer-Bäse, A.* ; Foo, S.* & Theis, F.J.: ICA, kernel methods and nonnegativity: New paradigms for dynamical component analysis of fMRI data. Eng. Appl. Artif. Intel. 22, 497-504 (2009)
337.
Klamt, S.* ; Haus, U.-U.* & Theis, F.J.: Hypergraphs and cellular networks. PLoS Comput. Biol. 5:e1000385 (2009)
338.
Neher, R.A.* et al.: Blind source separation techniques for the decomposition of multiply labeled fluorescence images. Biophys. J. 96, 3791-3800 (2009)
339.
Theis, F.J. ; Cason, T.P.* & Absil, P.A.*: Soft dimension reduction for ICA by joint diagonalization on the Stiefel manifold. In: Adali, T.* [Eds.]: Independent Component Analysis and Signal Separation. Berlin: Springer, 2009. 354-361 (Lecture Notes Comp. Sci. ; 5441)
340.
Theis, F.J. ; Neher, R.* & Zeug, A.*: Blind decomposition of spectral imaging microscopy: A study on artificial and real test data. In: Adali, T.* [Eds.]: Proceedings (Independent Component Analysis and Signal Separation). Berlin: Springer, 2009. 548-556 (Lecture Notes in Computer Science ; 5441)