Marc Strickert Vis

*	2009
30		Michael Seifert, Ali Banaei, Jens Keilwagen, Michael Florian Mette, Andreas Houben, François Roudier, Vincent Colot, Ivo Grosse, Marc Strickert: Array-based Genome Comparison of Arabidopsis Ecotypes using Hidden Markov Models. BIOSIGNALS 2009: 3-11
29	EE	Marc Strickert, Jens Keilwagen, Frank-Michael Schleif, Thomas Villmann, Michael Biehl: Matrix Metric Adaptation Linear Discriminant Analysis of Biomedical Data. IWANN (1) 2009: 933-940
28	EE	Michael Seifert, Jens Keilwagen, Marc Strickert, Ivo Grosse: Utilizing gene pair orientations for HMM-based analysis of promoter array ChIP-chip data. Bioinformatics 25(16): 2118-2125 (2009)
	2008
27	EE	Marc Strickert, Petra Schneider, Jens Keilwagen, Thomas Villmann, Michael Biehl, Barbara Hammer: Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics. ANNPR 2008: 78-89
26		Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer: Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203
25	EE	Marc Strickert, Frank-Michael Schleif, Thomas Villmann: Metric adaptation for supervised attribute rating. ESANN 2008: 31-36
24		Michael Seifert, Jens Keilwagen, Marc Strickert, Ivo Grosse: Utilizing Promoter Pair Orientations for HMM-based Analysis of ChIP-chip Data. German Conference on Bioinformatics 2008: 116-127
	2007
23	EE	Thomas Villmann, Marc Strickert, Cornelia Brüß, Frank-Michael Schleif, Udo Seiffert: Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. ESANN 2007: 103-108
22	EE	Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert: Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882
21	EE	Marc Strickert, Udo Seiffert: Correlation-based Data Representation. Similarity-based Clustering and its Application to Medicine and Biology 2007
20	EE	Marc Strickert, Nese Sreenivasulu, Björn Usadel, Udo Seiffert: Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue. BMC Bioinformatics 8: (2007)
	2006
19	EE	Marc Strickert, Nese Sreenivasulu, Silke Peterek, Winfriede Weschke, Hans-Peter Mock, Udo Seiffert: Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data. ANNPR 2006: 274-285
18	EE	Cornelia Brüß, Marc Strickert, Udo Seiffert: Towards Automatic Segmentation of Serial High-Resolution Images. Bildverarbeitung für die Medizin 2006: 126-130
17	EE	Marc Strickert, Nese Sreenivasulu, Udo Seiffert: Sanger-driven MDSLocalize - a comparative study for genomic data. ESANN 2006: 265-270
16	EE	Marc Strickert, Udo Seiffert, Nese Sreenivasulu, Winfriede Weschke, Thomas Villmann, Barbara Hammer: Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis. Neurocomputing 69(7-9): 651-659 (2006)
	2005
15	EE	Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Relevance learning for mental disease classification. ESANN 2005: 139-144
14	EE	Marc Strickert, Nese Sreenivasulu, Winfriede Weschke, Udo Seiffert, Thomas Villmann: Generalized Relevance LVQ with Correlation Measures for Biological Data. ESANN 2005: 331-338
13	EE	Marc Strickert, Stefan Teichmann, Nese Sreenivasulu, Udo Seiffert: High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data. ICANN (1) 2005: 625-633
12	EE	Barbara Hammer, Marc Strickert, Thomas Villmann: Supervised Neural Gas with General Similarity Measure. Neural Processing Letters 21(1): 21-44 (2005)
11	EE	Barbara Hammer, Marc Strickert, Thomas Villmann: On the Generalization Ability of GRLVQ Networks. Neural Processing Letters 21(2): 109-120 (2005)
10	EE	Marc Strickert, Barbara Hammer, Sebastian Blohm: Unsupervised recursive sequence processing. Neurocomputing 63: 69-97 (2005)
9	EE	Marc Strickert, Barbara Hammer: Merge SOM for temporal data. Neurocomputing 64: 39-71 (2005)
	2004
8	EE	Marc Strickert, Barbara Hammer: Self-organizing context learning. ESANN 2004: 39-44
7	EE	Barbara Hammer, Marc Strickert, Thomas Villmann: Relevance LVQ versus SVM. ICAISC 2004: 592-597
6	EE	Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert: Recursive self-organizing network models. Neural Networks 17(8-9): 1061-1085 (2004)
5	EE	Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert: A general framework for unsupervised processing of structured data. Neurocomputing 57: 3-35 (2004)
	2003
4	EE	Marc Strickert, Barbara Hammer: Unsupervised Recursive Sequence Processing. ESANN 2003: 27-32
	2002
3	EE	Barbara Hammer, Marc Strickert, Thomas Villmann: Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376
2	EE	Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883
	2001
1	EE	Marc Strickert, Thorsten Bojer, Barbara Hammer: Generalized Relevance LVQ for Time Series. ICANN 2001: 677-683

Coauthor Index

1	Ali Banaei	[30]
2	Michael Biehl	[27] [29]
3	Sebastian Blohm	[10]
4	Thorsten Bojer	[1]
5	Cornelia Brüß	[18] [23]
6	Vincent Colot	[30]
7	Ivo Grosse	[24] [28] [30]
8	Barbara Hammer	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [15] [16] [22] [26] [27]
9	Alexander Hasenfuss (Alexander Hasenfuß)	[22]
10	Andreas Houben	[30]
11	Jens Keilwagen	[24] [27] [28] [29] [30]
12	Michael Florian Mette	[30]
13	Alessio Micheli	[5] [6]
14	Hans-Peter Mock	[19]
15	Silke Peterek	[19]
16	Andreas Rechtien	[2] [15]
17	François Roudier	[30]
18	Frank-Michael Schleif	[22] [23] [25] [29]
19	Petra Schneider	[27]
20	Michael Seifert	[24] [28] [30]
21	Udo Seiffert	[13] [14] [16] [17] [18] [19] [20] [21] [22] [23]
22	Alessandro Sperduti	[5] [6]
23	Nese Sreenivasulu	[13] [14] [16] [17] [19] [20] [26]
24	Stefan Teichmann	[13]
25	Björn Usadel	[20]
26	Thomas Villmann	[2] [3] [7] [11] [12] [14] [15] [16] [22] [23] [25] [26] [27] [29]
27	Winfriede Weschke	[14] [16] [19]