gobics.de [Peter Meinicke]

University of Göttingen - Faculty of Biology - Institute of Microbiology and Genetics - Department of Bioinformatics

Dr. Peter Meinicke
Universität Göttingen
Institut für Mikrobiologie und Genetik
Abteilung für Bioinformatik
Goldschmidtstr. 1 (Raum 211)
37077 Göttingen

My spam-protected E-mail is:

Phone: +49 551 39-21690
Secretary: +49 551 39-14966
FAX: +49 551 39-14929

Short CV

Research Interests



Aßhauer KP, Wemheuer B, Daniel R, Meinicke P: Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics 2015, :2882-2884. [ bib | DOI ]

Meinicke P: UProC: tools for ultra-fast protein domain classification. Bioinformatics 2015, 31:1382-1388. [ bib | DOI ]

Kaever A, Landesfeind M, Feussner K, Mosblech A, Heilmann I, Morgenstern B, Feussner I, Meinicke P: MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data. Metabolomics 2015, 11:764-777. [ bib | DOI ]

Hoppenau CE, Tran VT, Kusch H, Aßhauer KP, Landesfeind M, Meinicke P, Popova B, Braus-Stromeyer SA, Braus GH: Verticillium dahliae VdTHI4, involved in thiazole biosynthesis, stress response and DNA repair functions, is required for vascular disease induction in tomato. Environmental and Experimental Botany 2014, 108:14-22. [ bib | DOI | http ]

Landesfeind M, Meinicke P: Predicting the functional repertoire of an organism from unassembled RNA–seq data. BMC Genomics 2014, 15:1003. [ bib ]

Lingner, Thomas, Meinicke, Peter: Characterizing metagenomic novelty with unexplained protein domain hits. In German Conference on Bioinformatics 2014, GI-Edition : lecture notes in informatics, Proceedings 2014:69-78. [ bib | .pdf ]

Landesfeind M, Kaever A, Feussner K, Thurow C, Gatz C, Feussner I, Meinicke P: Integrative study of Arabidopsis thaliana metabolomic and transcriptomic data with the interactive MarVis-Graph software. PeerJ 2014, 2:e239. [ bib | DOI ]

Kaever A, Landesfeind M, Feussner K, Morgenstern B, Feussner I, Meinicke P: Meta-analysis of pathway enrichment: combining independent and dependent omics data sets. PloS One 2014, 9:e89297. [ bib | DOI ]

Klingenberg H, Martinjak R, Glöckner FO, Daniel R, Lingner T, Meinicke P: Dinucleotide distance histograms for fast detection of rRNA in metatranscriptomic sequences. In German Conference on Bioinformatics (GCB'13) 2013:80-89. [ bib | DOI | http ]

Aßhauer KP, Meinicke P: On the estimation of metabolic profiles in metagenomics. In German Conference on Bioinformatics (GCB'13) 2013:1-13. [ bib | DOI | http ]

Klingenberg H, Aßhauer KP, Lingner T, Meinicke P: Protein signature-based estimation of metagenomic abundances including all domains of life and viruses. Bioinformatics 2013, 29:973-980. [ bib | DOI | http ]

Kaever A, Landesfeind M, Possienke M, Feussner K, Feussner I, Meinicke P: MarVis-Filter: Ranking, Filtering, Adduct and Isotope Correction of Mass Spectrometry Data. Journal of Biomedicine and Biotechnology 2012, 2012:263910. [ bib | DOI | http ]

Grossekathoefer U, Sadeghipour A, Lingner T, Meinicke P, Hermann T, Kopp S: Low Latency Recognition and Reproduction of Natural Gesture Trajectories. In ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, Volume 2 2012:154-161. [ bib | http ]

Danielsen L, Thürmer A, Meinicke P, Buée M, Morin E, Martin F, Pilate G, Daniel R, Polle A, Reich M: Fungal soil communities in a young transgenic poplar plantation form a rich reservoir for fungal root communities. Ecology and Evolution 2012, 2:1935-1948. [ bib | DOI | http ]

Bulla I, Schultz AK, Meinicke P: Improving Hidden Markov Models for classification of human immunodeficiency virus-1 subtypes through linear classifier learning. Statistical applications in genetics and molecular biology 2012, 11:Article 1. [ bib | http ]

Meinicke P, Aßhauer KP, Lingner T: Mixture models for analysis of the taxonomic composition of metagenomes. Bioinformatics 2011, 27:1618-1624. [ bib | DOI | http ]

Lingner T, Kataya AR, Antonicelli GE, Benichou A, Nilssen K, Chen XY, Siemsen T, Morgenstern B, Meinicke P, Reumann S: Identification of novel plant peroxisomal targeting signals by a combination of machine learning methods and in vivo subcellular targeting analyses. The Plant Cell 2011, 23:1556-1572. [ bib | DOI | http ]

Lingner T, Aßhauer KP, Schreiber F, Meinicke P: CoMet-a web server for comparative functional profiling of metagenomes. Nucleic Acids Research 2011, 39:W518-523. [ bib | DOI | http ]

Djamei A, Schipper K, Rabe F, Ghosh A, Vincon V, Kahnt J, Osorio S, Tohge T, Fernie AR, Feussner I, Feussner K, Meinicke P, Stierhof YD, Schwarz H, Macek B, Mann M, Kahmann R: Metabolic priming by a secreted fungal effector. Nature 2011, 478:395-398. [ bib | DOI | http ]

Subramanian AR, Hiran S, Steinkamp R, Meinicke P, Corel E, Morgenstern B: DIALIGN-TX and multiple protein alignment using secondary structure information at GOBICS. Nucleic Acids Research 2010, 38:W19-22. [ bib | DOI | http ]

Schreiber F, Gumrich P, Daniel R, Meinicke P: Treephyler: fast taxonomic profiling of metagenomes. Bioinformatics 2010, 26:960-961. [ bib | DOI | http ]

Nahlik K, Dumkow M, Bayram O, Helmstaedt K, Busch S, Valerius O, Gerke J, Hoppert M, Schwier E, Opitz L, Westermann M, Grond S, Feussner K, Goebel C, Kaever A, Meinicke P, Feussner I, Braus GH: The COP9 signalosome mediates transcriptional and metabolic response to hormones, oxidative stress protection and cell wall rearrangement during fungal development. Molecular Microbiology 2010, 78:964-979. [ bib | DOI | http ]

Lingner T, Mühlhausen S, Gabald'on T, Notredame C, Meinicke P: Predicting phenotypic traits of prokaryotes from protein domain frequencies. BMC Bioinformatics 2010, 11:481. [ bib | DOI | http ]

Meinicke P: UFO: a web server for ultra-fast functional profiling of whole genome protein sequences. BMC Genomics 2009, 10:409. [ bib | DOI | http ]

Kaever A, Lingner T, Feussner K, Göbel C, Feussner I, Meinicke P: MarVis: a tool for clustering and visualization of metabolic biomarkers. BMC Bioinformatics 2009, 10:92. [ bib | DOI | http ]

Hoff KJ, Lingner T, Meinicke P, Tech M: Orphelia: predicting genes in metagenomic sequencing reads. Nucleic Acids Research 2009, 37:W101-105. [ bib | DOI | http ]

Meinicke P, Lingner T, Kaever A, Feussner K, Göbel C, Feussner I, Karlovsky P, Morgenstern B: Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps. Algorithms for Molecular Biology: AMB 2008, 3:9. [ bib | DOI | http ]

Lingner T, Meinicke P: Word correlation matrices for protein sequence analysis and remote homology detection. BMC Bioinformatics 2008, 9:259. [ bib | DOI | http ]

Lingner T, Meinicke P: Fast Target Set Reduction for Large-Scale Protein Function Prediction: A Multi-class Multi-label Machine Learning Approach. In Algorithms in Bioinformatics, Volume 5251. Edited by Crandall KA, Lagergren J, Springer Berlin Heidelberg 2008:198-209. [ bib | http ]

Hoff KJ, Tech M, Lingner T, Daniel R, Morgenstern B, Meinicke P: Gene prediction in metagenomic fragments: a large scale machine learning approach. BMC Bioinformatics 2008, 9:217. [ bib | DOI | http ]

Taher L, Meinicke P, Morgenstern B: On splice site prediction using weight array models: a comparison of smoothing techniques. Journal of Physics: Conference Series 2007, 90:012004. [ bib | DOI | http ]

Mersch B, Glasmachers T, Meinicke P, Igel C: Evolutionary optimization of sequence kernels for detection of bacterial gene starts. International Journal of Neural Systems 2007, 17:369-381. [ bib | http ]

Igel C, Glasmachers T, Mersch B, Pfeifer N, Meinicke P: Gradient-based optimization of kernel-target alignment for sequence kernels applied to bacterial gene start detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics / IEEE, ACM 2007, 4:216-226. [ bib | DOI | http ]

Waack S, Keller O, Asper R, Brodag T, Damm C, Fricke WF, Surovcik K, Meinicke P, Merkl R: Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models. BMC Bioinformatics 2006, 7:142. [ bib | DOI | http ]

Tech M, Meinicke P: An unsupervised classification scheme for improving predictions of prokaryotic TIS. BMC Bioinformatics 2006, 7:121. [ bib | DOI | http ]

Tech M, Morgenstern B, Meinicke P: TICO: a tool for postprocessing the predictions of prokaryotic translation initiation sites. Nucleic Acids Research 2006, 34:W588-590. [ bib | DOI | http ]

Mersch B, Glasmachers T, Meinicke P, Igel C: Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. In Proc. of the Int. Conf. on Artificial Neural Networks 2006, Springer, LNCS 4132 2006:827-836. [ bib ]

Meinicke P, Brodag T, Fricke WF, Waack S: P-value based visualization of codon usage data. Algorithms for Molecular Biology: AMB 2006, 1:10. [ bib | DOI | http ]

Lingner T, Meinicke P: Remote homology detection based on oligomer distances. Bioinformatics 2006, 22:2224-2231. [ bib | DOI | http ]

Tech M, Pfeifer N, Morgenstern B, Meinicke P: TICO: a tool for improving predictions of prokaryotic translation initiation sites. Bioinformatics 2005, 21:3568-3569. [ bib | DOI | http ]

Meinicke P, Klanke S, Memisevic R, Ritter H: Principal surfaces from unsupervised kernel regression. IEEE Transactions on Pattern Analysis and Machine Intelligence 2005, 27:1379-1391. [ bib | DOI | http ]

Meinicke P, Tech M, Morgenstern B, Merkl R: Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites. BMC Bioinformatics 2004, 5:169. [ bib | DOI | http ]

Meinicke P, Hermann T, Bekel H, Müller HM, Weiss S, Ritter H: Identification of discriminative features in the EEG. Intelligent Data Analysis 2004, 8:97-107. [ bib ]

Kaper M, Meinicke P, Grossekathoefer U, Lingner T, Ritter H: BCI Competition 2003 - Dataset IIb: Support Vector Machines for the P300 speller paradigm. IEEE Transactions on Biomedical Engineering 2004, 51:1073-1076. [ bib ]

Meinicke P, Twellmann T, Ritter H: Discriminative Densities from Maximum Contrast Estimation. In Advances in Neural Information Processing Systems 15. Edited by Becker S, Thrun S, Obermayer K, MIT Press 2003:985-992. [ bib ]

Meinicke P, Kaper M, Hoppe F, Heumann M, Ritter H: Improving Transfer Rates in Brain Computer Interfacing: A Case Study. In Advances in Neural Information Processing Systems 15. Edited by Becker S, Thrun S, Obermayer K, MIT Press 2003:1107-1114. [ bib ]

Meinicke P, Ritter H: Quantizing Density Estimators. In Advances in Neural Information Processing Systems 14. Edited by Dietterich TG, Becker S, Ghahramani Z, MIT Press 2002:825-832. [ bib ]

Hermann T, Meinicke P, Bekel H, Ritter H, Müller H, Weiss S: Sonification for EEG Data Analysis. In Proc. of the Int. Conf. on Auditory Display. Edited by Nakatsu R, Kawahara H, Int. Community for Auditory Display 2002:37-41. [ bib ]

Meinicke P, Ritter H: Resolution-Based Complexity Control for Gaussian Mixture Models. Neural Computation 2001, 13:453-475. [ bib ]

Meinicke P, Ritter H: Independent Component Analysis with Quantizing Density Estimators. In Third International Conference on Independent Component Analysis and Signal Separation 2001:224-229. [ bib ]

Meinicke P: Unsupervised Learning in a Generalized Regression Framework. PhD thesis, Universitaet Bielefeld 2000. [ bib | http ]

Hermann T, Meinicke P, Ritter H: Principal Curve Sonification. In Proc. of the Int. Conf. on Auditory Display. Edited by Cook PR, Int. Community for Auditory Display 2000:81-86. [ bib ]

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