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AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
Banaei, A., Seifert, M., Czauderna, T., Strickert, M., Colot, V., Mette, M.F. & Houben, A. Analysis of chromatin modifications in crosses of Arabidopsis thaliana inbred lines 2008 Poster at the institute day of the IPK  misc  
Bojer, T., Hammer, B., Strickert, M. & Villmann, T. Determining Relevant Input Dimensions for the Self-Organizing Map 2003 Neural Networks and Soft Computing (Proc. ICNNSC 2002), pp. 388-393  incollection  
Brüß, C., Strickert, M. & Seiffert, U. Towards Automatic Segmentation of Serial High-Resolution Images 2006 Bildverarbeitung für die Medizin 2006 - Algorithmen, Systeme, Anwendungen, pp. 126-130  inproceedings  
Fester, T., Schreiber, F. & Strickert, M. CUDA-based multi-core implementation of MDS-based bioinformatics algorithms 2009 German Conference on Bioinformatics, pp. 67-79  inproceedings URL 
Gohr, A., Grau, J., Keilwagen, J., Mohr, M., Seifert, M., Grosse, I. & Posch, S. JSTACS -- A Java framework for statistical analysis and classification of biological sequences 2008 Poster at the German Conference on Bioinformatics  misc  
Grau, J., Boronczyk, D., Keilwagen, J., Posch, S. & Grosse, I. Maximum conditional likelihood decomposition 2008 Poster at the German Conference on Bioinformatics  misc  
Grau, J., Keilwagen, J., Grosse, I. & Posch, S. On the relevance of model orders to discriminative learning of Markov models 2007 LWA: Lernen -- Wissen -- Adaption, pp. 61-66  inproceedings  
Grau, J., Keilwagen, J., Kel, A., Grosse, I. & Posch, S. Supervised posteriors for DNA-motif classification 2007 German Conference on Bioinformatics, pp. 123-134  inproceedings  
Grau, J., Porsch, M., Lemnian, I., Keilwagen, J., Grosse, I. & Posch, S. Predicting nucleosome positioning from DNA sequence 2009 Poster at the German Conference on Bioinformatics  misc  
Hammer, B., Hasenfuß, A., Rossi, F. & Strickert, M. Topographic Processing of Relational Data 2007 Proceedings of the 6th International Workshop on Self-Organizing Maps (WSOM)  inproceedings URL 
Hammer, B., Hasenfuß, A., Schleif, F.-M., Villmann, T. & Strickert, M. Intuitive Clustering of Biological Data 2007 Proceedings of the International Joint Conference on Artificial Neural Networks (IJCNN 2007)  inproceedings URL 
Hammer, B., Micheli, A., Sperduti, A. & Strickert, M. A general framework for unsupervised processing of structured data 2004 Neurocomputing
Vol. 57, pp. 3-35 
article  
Hammer, B., Micheli, A., Sperduti, A. & Strickert, M. Recursive self-organizing network models 2004 Neural Networks, invited article
Vol. 17(8-9), pp. 1061-1086 
article  
Hammer, B., Rechtien, A., Strickert, M. & Villmann, T. Vector Quantization with Rule Extraction for Mixed Domain Data 2003   techreport  
Hammer, B., Rechtien, A., Strickert, M. & Villmann, T. Rule extraction from self-organizing maps 2002 Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp. 370-375  inproceedings  
Hammer, B., Strickert, M. & Villmann, T. On the generalization ability of GRLVQ-networks 2005 Neural Processing Letters
Vol. 21(2), pp. 109-120 
article  
Hammer, B., Strickert, M. & Villmann, T. Prototype based recognition of splice sites 2005 Bioinformatics using computational intelligence paradigms, pp. 25-55  incollection  
Hammer, B., Strickert, M. & Villmann, T. Supervised neural gas with general similarity measure 2005 Neural Processing Letters
Vol. 21, pp. 21-44 
article  
Hammer, B., Strickert, M. & Villmann, T. Relevance LVQ versus SVM 2004 Proceedings of ICAISC 2004, Lecture Notes in Computer Science
Vol. 3070, pp. 592-597 
article  
Hammer, B., Strickert, M. & Villmann, T. Learning vector quantization for multimodal data 2002 Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp. 370-375  inproceedings  
Keilwagen, J. Erkennung von DNA-Bindungsstellen mit Maximum Entropie Modellen 2005 School: Martin-Luther-Universität  mastersthesis  
Keilwagen, J., Azhaguvel, P., Stracke, S., Graner, A., Stein, N. & Grosse, I. Predicting the number of haplotypes by an integration of marker, passport, and phenotypic data 2007 Poster at the International Conference on Intelligent Systems for Molecular Biology  misc  
Keilwagen, J., Azhaguvel, P., Stracke, S., Graner, A., Stein, N. & Grosse, I. Predicting the number of haplotypes by an integration of marker, passport, and phenotypic data 2007 Talk at the Plant Science Student Conference  misc  
Keilwagen, J., Baumbach, J., Kohl, T.A. & Grosse, I. MotifAdjuster: a tool for computational reassessment of transcription factor binding site annotations 2009 Genome Biology
Vol. 10(5), pp. R46 
article DOI URL 
Keilwagen, J., Baumbach, J., Kohl, T. & Grosse, I. MotifAdjuster: a tool for computational reassessment of transcription factor binding site annotations 2009 Poster at the German Conference on Bioinformatics  misc  
Keilwagen, J., Grau, J., Grosse, I., Strickert, M. & Posch, S. A discriminative approach for de-novo motif discovery 2009 Poster at the institute day of the IPK  misc  
Keilwagen, J., Grau, J., Grosse, I., Strickert, M. & Posch, S. A discriminative approach for de-novo motif discovery 2008 Poster at the German Conference on Bioinformatics  misc  
Keilwagen, J., Grau, J., Paponov, I.A., Posch, S., Strickert, M. & Grosse, I. De-novo discovery of differentially abundant transcription factor binding sites including their positional preference. 2011 PLoS Comput Biol
Vol. 7(2), pp. e1001070 
article DOI URL 
Keilwagen, J., Grau, J., Posch, S. & Grosse, I. Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis. 2010 BMC Bioinformatics
Vol. 11(1), pp. 149 
article DOI URL 
Keilwagen, J., Grau, J., Posch, S. & Grosse, I. How to assess de-novo motif discovery approaches? 2009 Poster at the German Conference on Bioinformatics  misc  
Keilwagen, J., Grau, J., Posch, S. & Grosse, I. Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis 2009 Poster at the German Conference on Bioinformatics  misc  
Keilwagen, J., Grau, J., Posch, S. & Grosse, I. Recognition of splice sites using maximum conditional likelihood 2007 LWA: Lernen - Wissen - Adaption, pp. 67-72  inproceedings  
Keilwagen, J., Grau, J., Posch, S., Strickert, M. & Grosse, I. Unifying generative and discriminative learning principles 2010 BMC Bioinformatics
Vol. 11(1), pp. 98 
article DOI URL 
Keilwagen, J., Grau, J., Posch, S., Strickert, M. & Grosse, I. GenDisMix: Combining generative and discriminative learning approaches for the recognition of sequence motif 2009 Poster at the German Conference on Bioinformatics  misc  
Keilwagen, J., Seifert, M., Grau, J., Posch, S., Strickert, M. & Grosse, I. De-novo motif discovery of unknown motif combinations 2008 Poster at the Plant Science Student Conference  misc  
Moghaddam, A.M.B., Roudier, F., Seifert, M., Bérard, C., Magniette, M.-L.M., Ashtiyani, R.K., Houben, A., Colot, V. & Mette, M.F. Additive inheritance of histone modifications in Arabidopsis thaliana intraspecific hybrids. 2011 Plant J  article DOI URL 
Posch, S., Grau, J., Gohr, A., Keilwagen, J. & Grosse, I. Probabilistic Approaches to Transcription Factor Binding Site Prediction 2010 Methods in Molecular Biology, pp. Editorially accepted  incollection  
Seifert, M. Utilizing promoter pair orientations for HMM-based analysis of ChIP-chip data 2008 Talk at the GCB 2008 in Dresden  misc  
Seifert, M. Markov Models and Hidden Markov Models for sequence analysis -- part 1 2007 Lecture at the Martin Luther University  misc  
Seifert, M. Markov Models and Hidden Markov Models for sequence analysis -- part 2 2007 Lecture at the Martin Luther University  misc  
Seifert, M. Analysing Microarray Data Using Homogeneous And Inhomogeneous Hidden Markov Models 2006 School: Martin Luther University  mastersthesis  
Seifert, M. Anwendungen von Hidden Markov Modellen zur Sequenzanalyse 2006 Lecture at the Martin Luther University  misc  
Seifert, M. Analyse von Genexpressionsprofilen mit Hidden Markov Modellen 2006 Lecture at the Martin Luther University  misc  
Seifert, M., Banaei, A., Keilwagen, J., Mette, M., Houben, A., Roudier, F., Colot, V., Grosse, I. & Strickert, M. Array-based Genome Comparison of Arabidopsis Ecotypes Using Hidden Markov Models 2009 Proceedings of the 2nd International Conference on Bio-inspired Systems and Signal Processing (Biosignals 2009), pp. 3-11  inproceedings  
Seifert, M., Banaei, A., Keilwagen, J., Roudier, F., Colot, V., Mette, F., Houben, A., Grosse, I. & Strickert, M. Hidden Markov Models support array-based prediction of DNA copy number variants in Arabidopsis ecotypes 2008 Poster at the 2nd Conference on Machine Learning in Systems Biology (MLSB), Brussels, Belgium  misc  
Seifert, M., Banaei, A., Keilwagen, J., Roudier, F., V. Mette, M.F., Houben, A., Grosse, I. & Strickert, M. Array-based prediction of DNA copy number variants for Arabidopsis ecotypes using Hidden Markov Models 2008 Poster at the institute day of the IPK  misc  
Seifert, M., Banaei, A., Keilwagen, J., Roudier, F., V. Mette, M.F., Houben, A., Grosse, I. & Strickert, M. Array-based prediction of DNA copy number variants for Arabidopsis ecotypes using Hidden Markov Models 2008 Poster at the GCB 2008 in Dresden  misc  
Seifert, M., Banaei, A., Keilwagen, J., Roudier, F., V. Mette, M.F., Houben, A., Grosse, I. & Strickert, M. Array-based prediction of DNA copy number variants for Arabidopsis ecotypes using Hidden Markov Models 2008 Poster at the 4th EMBO Conference: From Functional Genomics to Systems Biology in Heidelberg  misc  
Seifert, M. & Grosse, I. Analysis of chromosomal imbalances and gene expression levels in human breast cancer 2007 Poster at the conference Systems Biology: Global Regulation Of Gene Expression at the Cold Spring Habor Laboratory  misc  
Seifert, M. & Grosse, I. Analysis of copy number variations and gene expression levels in human breast cancer 2007 Poster at the conference Functional Genomics & Systems Biology in Hinxton (UK)  misc  
Seifert, M. & Grosse, I. Genome-wide detection of ABI3 target genes in Arabidopsis thaliana form ChIP-chip data using Hidden Markov Models 2007 Talk at the Plant Science Student Conference 2007 in Halle at the IBP  misc  
Seifert, M. & Grosse, I. Analysis of chromosomal imbalances and gene expression levels in human breast cancer 2007 Poster at the 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB) in Vienna  misc  
Seifert, M. & Grosse, I. Linking chromosomal distances of genes to microarray profiles - a novel strategy to analyze the effects of chromosomal imbablances on gene expression levels 2006 Talk at the conference of Data Warehouse Technologies in Bioinformatics  misc  
Seifert, M., Keilwagen, J., Strickert, M. & Grosse, I. Utilizing gene pair orientations for HMM-based analysis of promoter array ChIP-chip data 2009 Bioinformatics
Vol. 25(16), pp. 2118-2125 
article DOI URL 
Seifert, M., Keilwagen, J., Strickert, M. & Grosse, I. Utilizing promoter pair orientations for HMM-based analysis of ChIP-chip data 2008
Vol. 136German Conference on Bioinformatics, pp. 116-127 
inproceedings  
Seifert, M., Mohr, M., Keilwagen, J., Hähnel, U., Mönke, G., Vorwieger, A., Viehöver, P., Linh, T.M., Tewes, A., Czihal, A., Kel, A., Weisshaar, B., Bäumlein, H., Conrad, U., Altschmied, L. & Grosse, I. Analyzing ChIP-chip data of the project ARABIDOSEED in the context of expression data and sequence data 2007 Poster at the 6th Plant GEM in Puerto de la Cruz (Tenerife)  misc  
Seifert, M., Mohr, M., Vorwieger, A., Czihal, A., Mönke, G., Linh, T.M., Hähnel, U., Altschmied, L., Conrad, U., Bäumlein, H. & Grosse, I. Analyzing ChIP-chip data of Arabidopsis thaliana in the context of expression data and sequence data 2007 Poster at the GCB 2007 in Potsdam  misc  
Seifert, M., Mohr, M., Vorwieger, A., Czihal, A., Mönke, G., Linh, T.M., Hähnel, U., Altschmied, L., Conrad, U., Bäumlein, H. & Grosse, I. Analyzing ChIP-chip data of Arabidopsis thaliana in the context of expression data and whole sequence data 2007 Poster at the conference Functional Genomics & and Systems Biology in Hinxton (UK)  misc  
Seifert, M., Strickert, M., Schliep, A. & Grosse, I. Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models. 2011 Bioinformatics
Vol. 27(12), pp. 1645-1652 
article DOI URL 
Sinha, R., Lenser, T., Jahn, N., Gausmann, U., Friedel, S., Szafranski, K., Huse, K., Rosenstiel, P., Hampe, J., Schuster, S., Hiller, M., Backofen, R. & Platzer, M. TassDB2 - A comprehensive database of subtle alternative splicing events. 2010 BMC Bioinformatics
Vol. 11(1), pp. 216 
article DOI URL 
Sreenivasulu, N., Radchuk, V., Strickert, M., Miersch, O., Weschke, W. & Wobus, U. Gene expression patterns reveal tissue-specific signaling networks controlling programmed cell death and ABA-regulated maturation in developing barley seeds 2006 The Plant Journal
Vol. 47(2), pp. 310-327 
article  
Sreenivasulu, N., Usadel, B., Winter, A., Radchuk, V., Scholz, U., Stein, N., Weschke, W., Strickert, M., Close, T.J., Stitt, M., Graner, A. & Wobus, U. Barley grain maturation and germination: Metabolic pathway and regulatory network commonalities and differences highlighted by new MapMan/PageMan profiling tools 2008 Plant Physiology, pp. 107.111781  article DOI URL 
Strickert, M. Self-Organizing Neural Networks for Sequence Processing 2004 School: Institute of Computer Science, Universität Osnabrück, Supervisors: Prof. Hammer (Osnabrück), Prof. Ritter (Bielefeld)  phdthesis URL 
Strickert, M. Treatment of Time Series from Ecosystems: Analysis and Modelling by the Example of Daily Rainfall and Runoff Data Recorded at St. Arnold, Germany. 2000   mastersthesis URL 
Strickert, M., Bojer, T. & Hammer, B. Generalized relevance LVQ for time series 2001 Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp. 677-683  inproceedings DOI  
Strickert, M., Czauderna, T., Peterek, S., Matros, A., Mock, H.-P. & Seiffert, U. Full-length HPLC signal clustering and biomarker identification in tomato plants 2006 Applied Artificial Intelligence, pp. 549-556  inproceedings  
Strickert, M. & Hammer, B. Merge SOM for temporal data 2005 Neurocomputing
Vol. 64, pp. 39-71 
article DOI  
Strickert, M. & Hammer, B. Self-Organizing Context Learning 2004 European Symposium on Artificial Neural Networks (ESANN), pp. 39-44  inproceedings URL 
Strickert, M. & Hammer, B. Unsupervised recursive sequence processing 2003 European Symposium on Artificial Neural Networks (ESANN), pp. 27-32  inproceedings URL 
Strickert, M. & Hammer, B. Neural Gas for Sequences 2003 Proceedings of the Workshop on Self-Organizing Networks (WSOM), pp. 53-58  inproceedings URL 
Strickert, M., Keilwagen, J., Schleif, F.M., Villmann, T. & Biehl, M. Matrix Metric Adaptation Linear Discriminant Analysis of Biomedical Data 2009
Vol. 5517Bio-Inspired Systems: Computational and Ambient Intelligence, pp. 933-940 
inproceedings DOI  
Strickert, M., Schleif, F.-M. & Seiffert, U. Gradients of Pearson Correlation for Analysis of Biomedical Data 2007 Proceedings of the 9th Argentine Symposium on Artificial Intelligence (ASAI 2007), pp. 139-150  inproceedings  
Strickert, M., Schleif, F.-M., Seiffert, U. & Villmann, T. Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data 2008 Inteligencia Artificial, Revista Iberoamericana de IA
Vol. 12(37), pp. 37-44 
article URL 
Strickert, M., Schleif, F.-M. & Villmann, T. Metric adaptation for supervised attribute rating 2008 European Symposium on Artificial Neural Networks (ESANN), pp. 31-36  inproceedings URL 
Strickert, M., Schleif, F.-M. & Villmann, T. Metric adaptation for supervised attribute rating 2008 Talk at the European Symposium on Artificial Neural Networks (ESANN)  misc  
Strickert, M., Schleif, F.-M., Villmann, T. & Seiffert, U. Similarity-Based Clustering - Recent Developments and Biomedical Applications 2009
Vol. 5400Similarity-Based Clustering -- Recent Developments and Biomedical Applications, pp. 70-91 
inbook DOI  
Strickert, M., Schneider, P., Keilwagen, J., Villmann, T., Biehl, M. & Hammer, B. Discriminatory data mapping by matrix-based supervised learning metrics 2008 Lecture Notes in Computer Science, LNCS 5065, pp. 78-89  inproceedings DOI  
Strickert, M., Seiffert, U., Sreenivasulu, N., Weschke, W., Villmann, T. & Hammer, B. Generalized Relevance LVQ (GRLVQ) with Correlation Measures for Gene Expression Data 2006 Neurocomputing
Vol. 69, pp. 651-659 
article  
Strickert, M., Soto, A., Keilwagen, J. & Vazquez, G. Towards matrix-based selection of feature pairs for efficient ADMET prediction 2009 Proceedings of the 9th Argentine Symposium on Artificial Intelligence (ASAI 2009), pp. 83-94  inproceedings URL 
Strickert, M., Sreenivasulu, N., Peterek, S., Weschke, W., Mock, H.-P. & Seiffert, U. Unsupervised feature selection for biomarker identification in chromatography and gene expression data 2006 Artificial Neural Networks in Pattern Recognition, LNAI 4087, pp. 274-285  inproceedings DOI  
Strickert, M., Sreenivasulu, N. & Seiffert, U. Sanger-driven MDSLocalize - A comparative study for Genomic Data 2006 European Symposium on Artificial Neural Networks (ESANN), pp. 265-270  inproceedings URL 
Strickert, M., Sreenivasulu, N., Usadel, B. & Seiffert, U. Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue 2007 BMC Bioinformatics
Vol. 8(165) 
article DOI URL 
Strickert, M., Sreenivasulu, N., Villmann, T. & Hammer, B. Robust centroid-based clustering using derivatives of Pearson correlation 2008 Proceedings of the International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC/BIOSIGNALS), pp. 197-203  inproceedings URL 
Strickert, M., Teichmann, S., Sreenivasulu, N. & Seiffert, U. 'DiPPP' Online Self-Improving Linear Map for Distance-Preserving Data Analysis 2005 Proceedings of the Workshop on Self-Organizing Networks (WSOM), pp. 661-668  inproceedings URL 
Strickert, M., Teichmann, S., Sreenivasulu, N. & Seiffert, U. High-Throughput Multi-Dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data 2005 Artificial Neural Networks: Biological Inspirations, Part I, LNCS 3696, pp. 625-634  inproceedings DOI  
Strickert, M., Witzel, K., Keilwagen, J., Mock, H.-P., Schneider, P. & Biehl, M. Adaptive matrix metrics for attribute dependence analysis in differential high-throughput data 2008 Proceedings of the fifth international Workshop on Computational Systems Biology (WCSB), pp. 181-184  inproceedings URL 
Strickert, M., Witzel, K., Mock, H.-P., Schleif, F.-M. & Villmann, T. Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments 2007 Proceedings of Machine Learning in Systems Biology (MLSB 2007)  inproceedings  
Thiel, J., Rolletschek, H., Friedel, S., Lunn, J.E., Nguyen, T.H., Feil, R., Tschiersch, H., Müller, M. & Borisjuk, L. Seed-specific elevation of non-symbiotic hemoglobin AtHb1: beneficial effects and underlying molecular networks in Arabidopsis thaliana. 2011 BMC Plant Biol
Vol. 11, pp. 48 
article DOI URL 
Thiel, J., Weier, D., Sreenivasulu, N., Strickert, M., Weichert, N., Melzer, M., Czauderna, T., Wobus, U., Weber, H. & Weschke, W. Different hormonal regulation of cellular differentiation and function in nucellar projection and endosperm transfer cells -- a microdissection-based transcriptome study of young barley grains 2008 Plant Physiology
Vol. 148(3), pp. 1436-1452 
article DOI URL 
Villmann, T., Hammer, B. & Strickert, M. Supervised neural gas for learning vector quantization 2002 Proceedings od the Fifth German Workshop on Artificial Life, pp. 9-18  inproceedings  
Villmann, T., Schleif, F.-M., Merenyi, E., Strickert, M. & Hammer, B. Class imaging of hyperspectral satellite remote sensing data using FLSOM 2007 Proceedings of the 6th International Workshop on Self-Organizing Maps (WSOM)  inproceedings URL 

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