Frank Emmert-Streib

	2009
28		Frank Emmert-Streib, Matthias Dehmer: Organizational Structure of the Transcriptional Regulatory Network of Yeast: Periodic Genes. Complex (1) 2009: 140-148
27		Matthias Dehmer, Frank Emmert-Streib: Towards Network Complexity. Complex (1) 2009: 707-714
26		Frank Emmert-Streib, Matthias Dehmer: Towards a Partitioning of the Input Space of Boolean Networks: Variable Selection Using Bagging. Complex (1) 2009: 715-723
25		Galina V. Glazko, Frank Emmert-Streib: Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets. Bioinformatics 25(18): 2348-2354 (2009)
	2008
24		Matthias Dehmer, Michael Drmota, Frank Emmert-Streib: Proceedings of the 2008 International Conference on Information Theory and Statistical Learning, ITSL 2008, Las Vegas, Nevada, USA, July 14-17, 2008 CSREA Press 2008
23		Frank Emmert-Streib, Andre Ribeiro: Optimize Observational Time Points to Maximize the Inferability of Gene Networks. BIOCOMP 2008: 55-60
22		Frank Emmert-Streib, Hamid R. Arabnia, Mary Qu Yang: Preface. Applied Artificial Intelligence 22(7&8): 617-618 (2008)
21		Matthias Dehmer, Frank Emmert-Streib, Tanja Gesell: A comparative analysis of multidimensional features of objects resembling sets of graphs. Applied Mathematics and Computation 196(1): 221-235 (2008)
20		Matthias Dehmer, Frank Emmert-Streib: Structural information content of networks: Graph entropy based on local vertex functionals. Computational Biology and Chemistry 32(2): 131-138 (2008)
	2007
19		Hamid R. Arabnia, Matthias Dehmer, Frank Emmert-Streib, Mary Qu Yang: Proceedings of the 2007 International Conference on Machine Learning; Models, Technologies & Applications, MLMTA 2007, June 25-28, 2007, Las Vegas Nevada, USA CSREA Press 2007
18		Frank Emmert-Streib, Matthias Dehmer: Optimization Procedure for Predicting Nonlinear Time Series Based on a Non-Gaussian Noise Model. MICAI 2007: 540-549
17		Matthias Dehmer, Frank Emmert-Streib, Andreas Zulauf: A Graph Mining Technique for Automatic Classification of Web Genre Data. MLMTA 2007: 10-16
16		Matthias Dehmer, Alexander Mehler, Frank Emmert-Streib: Graph-theoretical Characterizations of Generalized Trees. MLMTA 2007: 113-117
15		Frank Emmert-Streib, Matthias Dehmer: Topological mappings between graphs, trees and generalized trees. Applied Mathematics and Computation 186(2): 1326-1333 (2007)
14		Matthias Dehmer, Frank Emmert-Streib: Comparing large graphs efficiently by margins of feature vectors. Applied Mathematics and Computation 188(2): 1699-1710 (2007)
13		Frank Emmert-Streib, Matthias Dehmer: Information theoretic measures of UHG graphs with low computational complexity. Applied Mathematics and Computation 190(2): 1783-1794 (2007)
12		Matthias Dehmer, Frank Emmert-Streib: Structural similarity of directed universal hierarchical graphs: A low computational complexity approach. Applied Mathematics and Computation 194(1): 7-20 (2007)
11		Frank Emmert-Streib, Arcady R. Mushegian: A topological algorithm for identification of structural domains of proteins. BMC Bioinformatics 8: (2007)
10		Frank Emmert-Streib: The Chronic Fatigue Syndrome: A Comparative Pathway Analysis. Journal of Computational Biology 14(7): 961-972 (2007)
	2006
9		Frank Emmert-Streib, Matthias Dehmer: Theoretical Bounds for the Number of Inferable Edges in Sparse Random Networks. BIOCOMP 2006: 472-476
8		Frank Emmert-Streib, Matthias Dehmer, Chris Seidel: Influence of Prior Information on the Reconstruction of the Yeast Cell Cycle from Microarray Data. BIOCOMP 2006: 477-482
7		Frank Emmert-Streib: A Novel Stochastic Learning Rule for Neural Networks. ISNN (1) 2006: 414-423
6		Matthias Dehmer, Frank Emmert-Streib, Jürgen Kilian: A similarity measure for graphs with low computational complexity. Applied Mathematics and Computation 182(1): 447-459 (2006)
5		Frank Emmert-Streib: Algorithmic Computation of Knot Polynomials of Secondary Structure Elements of Proteins. Journal of Computational Biology 13(8): 1503-1512 (2006)
4		Frank Emmert-Streib: Influence of the neural network topology on the learning dynamics. Neurocomputing 69(10-12): 1179-1182 (2006)
	2005
3		Frank Emmert-Streib, Matthias Dehmer, Jürgen Kilian: Classification of Large Graphs by a Local Tree Decomposition. DMIN 2005: 200-207
2		Frank Emmert-Streib: A Neurobiologically Motivated Model for Self-organized Learning. MICAI 2005: 415-424
	2001
1		Jens R. Otterpohl, Frank Emmert-Streib, Klaus Pawelzik: A constrained HMM-based approach to the estimation of perceptual switching dynamics in pigeons. Neurocomputing 38-40: 1495-1501 (2001)

Coauthor Index

1	Hamid R. Arabnia	[19] [22]
2	Matthias Dehmer	[3] [6] [8] [9] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [24] [26] [27] [28]
3	Michael Drmota	[24]
4	Tanja Gesell	[21]
5	Galina V. Glazko	[25]
6	Jürgen Kilian	[3] [6]
7	Alexander Mehler	[16]
8	Arcady R. Mushegian	[11]
9	Jens R. Otterpohl	[1]
10	Klaus Pawelzik (Klaus R. Pawelzik)	[1]
11	Andre Ribeiro	[23]
12	Chris Seidel	[8]
13	Mary Qu Yang	[19] [22]
14	Andreas Zulauf	[17]

Colors in the list of coauthors