More Vingron publications

  • J Perner, J Lasserre, S Kinkley, M Vingron, HR Chung (2014) 
    Inference of interactions between chromatin modifiers and histone modifications: from ChIP-Seq data to chromatin-signaling.
    Nucleic Acids Res.42 (22): 13689-95
  • D Emmerich et al. (2015)
    Somatic neurofibromatosis type I (NF1) inactivation events in cutaneous neurofibromas of a single NF1 patient.
    Eur J Hum Genet., 23 (6): 870-3
  • X Yu et al. (2014) 
    Reconstruction of gene regulatory network related to photosynthesis in Arabidopsis thaliana.
    Front Plant Sci., 5: 273
  • C Rintisch et al. (2014) 
    Natural variation of histone modification and its impact on gene expression in the rat genome.
    Genome Res.,24 (6): 942-53
  • N Misra, E Szczurek, M Vingron (2014) 
    Inferring the paths of somatic evolution in cancer.
    Bioinformatics, 30 (17): 2456-63
  • G Meng, M Vingron (2014) 
    Condition-specific target prediction from motifs and expression.
    Bioinformatics, 30 (12): 1643-50
  • L Fernandez-Cuesta et al. (2014) 
    CD74-NRG1 fusions in lung adenocarcinoma.
    Cancer Discovery, 4 (4): 415-22
  • A Dress, M Linial, O Troyanskaya, M Vingron (2013) 
    ISCB/SPRINGER series in computational biology.
    Bioinformatics, 29 (24): 3246-7
  • M Thomas-Chollier et al. (2013) 
    A naturally occuring insertion of a single amino acid rewires transcriptional regulation by glucocorticoid receptor isoforms.
    Proc Natl Acad Sci., 110 (44): 17826-31
  • J Lasserre, HR Chung, M Vingron (2013) 
    Finding associations among histone modifications using sparse partial correlation networks.
    PLoS Comput Biol., 9 (9): e1003168
  • A Mammana, M Vingron, HR Chung (2013) 
    Inferring nucleosome positions with their histone mark annotation from ChIP data.
    Bioinformatics, 29 (20): 2547-2554
  • A Marsico et al. (2013)
    PROmiRNA: a new miRNA promoter recognition method uncovers the complex regulation of intronic miRNAs.
    Genome Biol., 14 (8): R84
  • J Göke, YS Chan, J Yan, M Vingron, HH Ng (2013)
    Genome-wide kinase-chromatin interactions reveal the regulatory network of ERK signaling in human embryonic stem cells.
    Mol Cell, 50 (6): 844-55
  • E Szczurek, N Misra, M Vingron (2013)
    Synthetic sickness or lethality points at candidate combination therapy targets in glioblastoma.
    Int J Cancer, 133 (9): 2123-32
  • R Feldmann et al. (2013)
    Genome-wide analysis of LXRα activation reveals new transcriptional networks in human atherosclerotic foam cells.
    Nucleic Acids Res., 41 (6): 3518-31
  • MT Weirauch et al. (2013)
    Evaluation of methods for modeling transcription factor sequence specificity. 
    Nat Biotechnol.31 (2): 126-34
  • F Odoardi et al. (2012)
    T cells become licensed in the lung to enter the central nervous system.
    Nature, 488 (7413): 675-9
  • S Ni, M Vingron (2012)
    R2KS: A novel measure for comparing gene expression based on ranked gene lists.
    J Comput Biol., 19 (6): 766-75
  • T Zemojtel, M Vingron (2012)
    P53 binding sites in transposons.
    Front Genet., 3: 40
  • A Myšičková, M Vingron (2012)
    Detection of interacting transcription factors in human tissues using predicted DNA binding affinity.
    BMC Genomics, 13 Suppl 1: S2
  • D Adams et al. (2012)
    BLUEPRINT to decode the epigenetic signature written in blood.
    Nat Biotechnol., 30 (3): 224-6
  • MH Schulz, DR Zerbino, M Vingron, E Birney (2012)
    Oases: Robust de novo RNA-seq assembly across the dynamic range of expression levels.
    Bioinformatics, 28 (8): 1086-92
  • R Sun, MI Love, T Zemojtel, AK Emde, HR Chung, M Vingron, S Haas (2012)
    Breakpointer: using local mapping artifacts to support sequence breakpoint discovery from single-end reads.
    Bioinformatics, 28 (7): 1024-5
  • J Göke, MH Schulz, J Lasserre, M Vingron (2012)
    Estimation of pairwise sequence similarity of mammalian enhancers with word neighbourhood counts.
    Bioinformatics, 28 (5): 656-63
  • AK Emde et al. (2012)
    Detecting genomic indel variants with exact breakpoints in single- and paired-end sequencing data using SplazerS.
    Bioinformatics, 28 (5): 619-27
  • J Göke et al. (2011)
    Combinatorial binding in human and mouse embryonic stem cells identifies conserved enhancers active in early
    embryonic development.
    PLoS Comput Biol., 7 (12): e1002304
  • S Roepcke, S Stahlberg, H Klein, MH Schulz, L Theobald, S Gohlke, M Vingron, DJ Walther
    A tandem sequence motif acts as a distance-dependent enhancer in a set of genes involved in translation by
    binding the proteins NonO and SFPQ.
    BMC Genomics, 12 (1): 624
  • M Thomas-Chollier, A Hufton, M Heinig, S O'Keeffe, NE Masri, HG Roider, T Manke, M Vingron (2011)
    Transcription factor binding predictions using TRAP for the analysis of ChIP-seq data and regulatory SNPs.
    Nat Protoc., 6 (12): 1860-9
  • T Zemojtel, SM Kielbasa, PF Arndt, S Behrens, G Bourque, M Vingron (2011)
    CpG deamination creates transcription factor binding sites with high efficiency.
    Genome Biol Evol., 3: 1304-11
  • Y Yuan et al. (2011)
    Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.
    BMC Bioinformatics, 12: 347
  • J Lasserre et al. (2011)
    Predicting the outcome of renal transplantation.
    J Am Med Inform Assoc., 19 (2): 255-62
  • Y Yuan et al. (2011)
    Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.
    BMC Bioinformatics, 12 (1): 347
  • A Serin, M Vingron (2011)
    DeBi: Discovering differentially expressed biclusters using a frequent itemset approach.
    Algorithms Mol Biol., 6 (1): 18
  • E Szczurek, F Markowetz, I Gat-Viks, P Biecek, J Tiuryn, M Vingron (2011)
    Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data.
    BMC Bioinformatics, 12 (1): 249
  • HJ Warnatz et al. (2011)
    The BTB and CNC homology 1 (BACH1) target genes are involved in the oxidative stress response and in the control of the cell cycle.
    J Biol Chem., 286 (26): 23521-32
  • L Hallen et al. (2011)
    The KRAB-containing zinc-finger transcriptional regulator ZBRK1 activates SCA2 gene transcription through direct interaction with its gene product, ataxin-2.
    Hum Mol Genet., 20(1):104-14
  • HR Chung, I Dunkel, F Heise, C Linke, S Krobitsch, AE Ehrenhofer-Murray, SR Sperling, M Vingron (2010)
    The effect of micrococcal nuclease digestion on nucleosome positioning data.
    PLoS One. 5(12):e15754
  • S Lin, S Haas, T Zemojtel, P Xiao, M Vingron, R Li
    Genome-wide comparison of cyanobacterial transposable elements, potential genetic diversity indicators
    Gene, 473 (2):139-49
  • M Kolanczyk et al. (2010)
    NOA1 is an essential GTPase required for mitochondrial protein synthesis.
    Mol Biol Cell, 22(1):1-11
  • M Heinig et al. (2010)
    A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
    Nature, 467(7314):460-4
  • S Behrens, M Vingron (2010)
    Studying the evolution of promoter sequences: a waiting time problem.
    J Comput Biol., 17(12):1591-606
  • E Szczurek, P Biecek, J Tiuryn, M Vingron (2010)
    Introducing knowledge into differential expression analysis.
    J Comput Biol., 17(8):953-67
  • SM Kielbasa, H Klein, HG Roider, M Vingron, N Blüthgen (2010)
    TransFind--predicting transcriptional regulators for gene sets.
    Nucleic Acids Res., 38 Suppl:W275-80
  • HJ Warnatz, R Querfurth et al. (2010)
    Functional analysis and identification of cis-regulatory elements of human chromosome 21 gene promoters.
    Nucleic Acids Res., 38(18):6112-23
  • G Meng, A Mosig, M Vingron (2010)
    A computational evaluation of over-representation of regulatory motifs in the promoter regions of differentially expressed genes.
    BMC Bioinformatics, 11:267
  • H Richard et al. (2010)
    Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments.
    Nucleic Acids Res. 38(10):e112
  • R Karlic, HR Chung, J Lasserre, K Vlahovicek, M Vingron (2010)
    Histone modification levels are predictive for gene expression
    Proc Natl Acad Sci USA 107(7):2926-31
  • T Manke, M Heinig, M Vingron (2010)
    Quantifying the effect of sequence variation on regulatory interactions
    Hum Mutat. 31(4):477-83
  • HG Roider, B Lenhard, A Kanhere, SA Haas, M Vingron (2009)
    CpG-depleted promoters harbor tissue-specific transcription factor binding signals - implications for motif overrepresentation analyses
    Nucleic Acids Res. 37(19):6305-15
  • E Szczurek, I Gat-Viks, J Tiuryn, M Vingron (2009)
    Elucidating regulatory mechanisms downstream of a signaling pathway using informative experiments
    Mol Syst Biol. 5:287
  • X Huang, M Vingron
    Maximum similarity: a new formulation of phylogenetic reconstruction
    J Comput Biol. 16(7):887-98
  • HR Chung, M Vingron (2009)
    Comparison of sequence-dependent tiling array normalization approaches
    BMC Bioinformatics 10:204
  • C Steinhoff, M Paulsen, S Kielbasa, J Walter, M Vingron (2009)
    Expression profile and transcription factor binding site exploration of imprinted genes in human and mouse
    BMC Genomics 10:144
  • UJ Pape, H Klein, M Vingron
    Statistical detection of cooperative transcription factors with similarity adjustment
    Bioinformatics 25(16):2103-9
  • Vingron M, Brazma A, Coulson R, van Helden J, Manke T, Palin K, Sand O, Ukkonen E. (2009)
    Integrating sequence, evolution and functional genomics in regulatory genomics.
    Genome Biol. 10(1):202
  • Gat-Viks I, Vingron M (2009)
    Evidence for gene-specific rather than transcription rate-dependent histone H3 exchange in yeast coding regions
    PLoS Comput Biol. 5(2):e1000282
  • Kanhere A, Vingron M. (2009)
    Horizontal Gene Transfers in prokaryotes show differential preferences for metabolic and translational genes
    BMC Evol Biol. 9:9
  • Zemojtel T, Kielbasa SM, Arndt PF, Chung HR, Vingron M. (2009)
    Methylation and deamination of CpGs generate p53-binding sites on a genomic scale
    Trends Genet. 25(2):63-6
  • Roider HG, Manke T, O'Keeffe S, Vingron M, Haas SA (2009)
    PASTAA: identifying transcription factors associated with sets of co-regulated genes.
    Bioinformatics. 25(4):435-42
  • Chung HR, Vingron M (2009)
    Sequence-dependent nucleosome positioning
    J Mol Biol. 386(5):1411-22
  • Zhang J, Vingron M, Roepcke S (2008)
    Characteristic differences between the promoters of intron-containing and intronless ribosomal protein genes in yeast.
    BMC Res Notes. 1:109
  • Kielbasa SM, Vingron M (2008)
    Transcriptional autoregulatory loops are highly conserved in vertebrate evolution.
    PLoS One 3(9):e3210
  • Pape UJ, Rahmann S, Sun F, Vingron M. (2008)
    Compound poisson approximation of the number of occurrences of a position frequency matrix (PFM) on both strands
    J Comput Biol. 15(6):547-64
  • Klein H, Vingron M. (2007)
    Using transcription factor binding site co-occurrence to predict regulatory regions.
    Genome Inform. 18:109-18
  • Bauer S, Grossmann S, Vingron M, Robinson PN. (2008)
    Ontologizer 2.0--a multifunctional tool for GO term enrichment analysis and data exploration.
    Bioinformatics 24(14):1650-1
  • Toenjes M, Schueler M, Hammer S, Pape UJ, Fischer JJ, Berger F, Vingron M, Sperling S (2008)
    Prediction of cardiac transcription networks based on molecular data and complex clinical phenotypes
    Mol Biosyst. 4(6):589-98
  • Manke T, Roider HG, Vingron M. (2008)
    Statistical modeling of transcription factor binding affinities predicts regulatory interactions
    PLoS Comput Biol. 4(3):e1000039
  • Chen W et al. (2008)
    Mapping translocation breakpoints by next-generation sequencing
    Genome Res. 18(7):1143-9
  • Lee HJ, Manke T, Bringas R, Vingron M. (2008)
    Prioritization of gene regulatory interactions from large-scale modules in yeast
    BMC Bioinformatics. 9:32
  • Pape UJ, Rahmann S, Vingron M. (2008)
    Natural similarity measures between position frequency matrices with an application to clustering.
    Bioinformatics 24(3):350-7
  • Zemojtel T, Penzkofer T, Schultz J, Dandekar T, Badge R, Vingron M (2007)
    Exonization of active mouse L1s: a driver of transcriptome evolution?
    BMC Genomics. 8:392
  • Bais AS, Grossmann S, Vingron M (2007)
    Incorporating evolution of transcription factor binding sites into annotated alignments
    J Biosci. 32(5):841-50
  • HG Roider, A Kanhere, T Manke, M Vingron (2007)
    Predicting transcription factor affinities to DNA from a biophysical model.
    Bioinformatics, 23(2):134-141
  • Grossmann S, Bauer S, Robinson PN, Vingron M. (2007)
    Improved Detection of Overrepresentation of Gene-Ontology Annotations with Parent-Child Analysis.
    Bioinformatics 23(22):3024-31
  • Bais AS, Grossmann S, Vingron M. (2007)
    Simultaneous alignment and annotation of cis-regulatory regions.
    Bioinformatics, 15;23(2)
  • H Luz, M Vingron. (2006)
    Family specific rates of protein evolution.
    Bioinformatics, 15;22(10):1166-1171
  • Krause A, Stoye J, Vingron M. (2005)
    Large scale hierarchical clustering of protein sequences.
    BMC Bioinformatics, 22
  • Dieterich C, Rahmann S, Vingron M. (2004)
    Functional inference from non-random distributions of conserved predicted transcription factor binding sites.
    Bioinformatics, 20 Suppl 1:i109-15.
  • Huber, W., Heydebreck, A. von, Sueltmann, H., Poustka, A. and Vingron, M. (2003).
    Parameter estimation for the calibration and variance stabilization of microarray data.
    Statistical Applications in Genetics and Molecular Biology 2(1), Article 3 (http://www.bepress.com/sagmb/vol2/iss1/art3).
  • Manke T, Bringas R, Vingron M. (2003).
    Correlating Protein-DNA and Protein-Protein Interaction Networks.
    J. Mol. Biol. 333, 75-85.
  • W Huber, A von Heydebreck, H Sültmann, A Poustka, M Vingron (2002)
    Variance stabilization applied to microarray data calibration and to the quantification of differential expression.
    Bioinformatics, 18 Suppl 1: S96-104
  • Fellenberg, K., Hauser, N., Brors, B., Neutzner, A., Hoheisel, J., Vingron, M. (2001).
    Correspondence Analysis Applied to Microarray Data.
    Proc. Natl. Acad. Sci. USA 98, 10781-10786.
  • Müller, T. and Vingron, M. (2000).
    Modeling amino acid replacement.
    J. Comp. Biol. 7(6), 761-776.
  • Vingron, M. (1996).
    Near-optimal sequence alignment.
    Current Opinion in Structural Biology 6, 346-352.
  • Vingron, M. and Pevzner, P.A. (1995).
    Multiple Sequence Comparison and Consistency on Multipartite Graphs. Advances in Applied Mathematics 16, 1-22.
  • Vingron, M., Argos, P. (1991).
    Motif recognition and alignment for many sequences by comparison of dotmatrices. J. Mol. Biol. 218, 33-43.
  • Waterman, M.S., Vingron, M. (1994).
    Sequence Comparison Significance and Poisson Approximation.
    Statistical Science 9, 367-381.
  • Vingron, M. and Waterman, M.S. (1994).
    Sequence Alignment and Penalty Choice: Review of Concepts, Case Studies and Implications.
    J. Mol. Biol. 235, 1-12.
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