Meinicke, Peter

[["dc.bibliographiccitation.firstpage","14"],["dc.bibliographiccitation.journal","Environmental and Experimental Botany"],["dc.bibliographiccitation.lastpage","22"],["dc.bibliographiccitation.volume","108"],["dc.contributor.author","Hoppenau, Clara E."],["dc.contributor.author","Tran, Van-Tuan"],["dc.contributor.author","Kusch, Harald"],["dc.contributor.author","Aßhauer, Kathrin P."],["dc.contributor.author","Landesfeind, Manuel"],["dc.contributor.author","Meinicke, Peter"],["dc.contributor.author","Popova, Blagovesta"],["dc.contributor.author","Braus-Stromeyer, Susanna A."],["dc.contributor.author","Braus, Gerhard H."],["dc.date.accessioned","2018-04-24T15:04:17Z"],["dc.date.available","2018-04-24T15:04:17Z"],["dc.date.issued","2014"],["dc.description.abstract","The vascular plant pathogen Verticillium dahliae colonizes the xylem fluid where only low nutrient concentrations are provided. Biosynthesis of the vitamin thiamine is connected to oxidative stress. The highly conserved VdThi4 protein is localized in fungal mitochondria and is required under vitamin B1 limiting conditions. Deletion of the corresponding VdTHI4 gene by Agrobacterium-mediated transformation resulted in strains which were impaired in growth on thiamine-free medium and could be rescued by additional vitamin supply or by complementation with the original gene after protoplastation. Furthermore, we show that VdThi4 increases fungal stress tolerance such as UV-damage or oxidative stress. The orthologous sti35 gene of Fusarium oxysporum, another vascular wilt fungus, was shown to be involved in stress response, however to be dispensable for pathogenicity on tomato. In contrast, VdTHI4 is required for fungal-induced tomato disease demonstrated by infection assays with a V. dahliae ΔVdTHI4 deletion strain which is still able to invade plants through the roots but is asymptomatic. Our results suggest remarkable differences between two vascular tomato pathogens where VdThi4 is required for pathogenicity of V. dahliae, whereas F. oxysporum still causes disease when the corresponding Sti35 protein is absent."],["dc.description.sponsorship","Federal Ministry of Education and Research (BMBF)"],["dc.description.sponsorship","Cluster of Excellence and DFG Research Center Nanoscale Microscopy and Molecular Physiology of the Brain"],["dc.identifier.doi","10.1016/j.envexpbot.2013.12.015"],["dc.identifier.other","http://www.sciencedirect.com/science/article/pii/S0098847213002268"],["dc.identifier.pii","S0098847213002268"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/13764"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-575"],["dc.notes.status","zu prüfen"],["dc.relation.issn","0098-8472"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","Verticillium dahliae VdTHI4, involved in thiazole biosynthesis, stress response and DNA repair functions, is required for vascular disease induction in tomato"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1073"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","IEEE Transactions on Biomedical Engineering"],["dc.bibliographiccitation.lastpage","1076"],["dc.bibliographiccitation.volume","51"],["dc.contributor.author","Kaper, M."],["dc.contributor.author","Meinicke, Peter"],["dc.contributor.author","Grossekathoefer, U."],["dc.contributor.author","Lingner, Thomas"],["dc.contributor.author","Ritter, H."],["dc.date.accessioned","2018-11-07T10:48:28Z"],["dc.date.available","2018-11-07T10:48:28Z"],["dc.date.issued","2004"],["dc.description.abstract","We propose an approach to analyze data from the P300 speller paradigm using the machine-learning technique support vector machines. In a conservative classification scheme, we found the correct solution after five repetitions. While the classification within the competition is designed for offline analysis, our approach is also well-suited for a real-world online solution: It is fast, requires only 10 electrode positions and demands only a small amount of preprocessing."],["dc.identifier.doi","10.1109/TBME.2004.826698"],["dc.identifier.isi","000221578000029"],["dc.identifier.pmid","15188881"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/48199"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Ieee-inst Electrical Electronics Engineers Inc"],["dc.relation.issn","0018-9294"],["dc.title","BCI competition 2003 - Data set IIb: Support vector machines for the P300 speller paradigm"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3568"],["dc.bibliographiccitation.issue","17"],["dc.bibliographiccitation.journal","Bioinformatics"],["dc.bibliographiccitation.lastpage","3569"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Tech, Maike"],["dc.contributor.author","Pfeifer, N."],["dc.contributor.author","Morgenstern, Burkhard"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T10:55:56Z"],["dc.date.available","2018-11-07T10:55:56Z"],["dc.date.issued","2005"],["dc.description.abstract","We provide the tool 'TICO' (Translation Initiation site COrrection) for improving the results of conventional gene finders for prokaryotic genomes with regard to exact localization of the translation initiation site (TIS). At the current state TICO provides an interface for direct post processing of the predictions obtained from the widely used program GLIMMER. Our program is based on a clustering algorithm for completely unsupervised scoring of potential TIS locations."],["dc.identifier.doi","10.1093/bioinformatics/bti563"],["dc.identifier.isi","000231472500017"],["dc.identifier.pmid","15994191"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/49897"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1367-4803"],["dc.title","TICO: a tool for improving predictions of prokaryotic translation initiation sites"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","919"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Microbial Ecology"],["dc.bibliographiccitation.lastpage","930"],["dc.bibliographiccitation.volume","67"],["dc.contributor.author","Nacke, Heiko"],["dc.contributor.author","Fischer, Christiane"],["dc.contributor.author","Thuermer, Andrea"],["dc.contributor.author","Meinicke, Peter"],["dc.contributor.author","Daniel, Rolf"],["dc.date.accessioned","2018-11-07T09:41:00Z"],["dc.date.available","2018-11-07T09:41:00Z"],["dc.date.issued","2014"],["dc.description.abstract","Soil microorganisms play an essential role in sustaining biogeochemical processes and cycling of nutrients across different land use types. To gain insights into microbial gene transcription in forest and grassland soil, we isolated mRNA from 32 sampling sites. After sequencing of generated complementary DNA (cDNA), a total of 5,824,229 sequences could be further analyzed. We were able to assign nonribosomal cDNA sequences to all three domains of life. A dominance of bacterial sequences, which were affiliated to 25 different phyla, was found. Bacterial groups capable of aromatic compound degradation such as Phenylobacterium and Burkholderia were detected in significantly higher relative abundance in forest soil than in grassland soil. Accordingly, KEGG pathway categories related to degradation of aromatic ring-containing molecules (e.g., benzoate degradation) were identified in high abundance within forest soil-derived metatranscriptomic datasets. The impact of land use type forest on community composition and activity is evidently to a high degree caused by the presence of wood breakdown products. Correspondingly, bacterial groups known to be involved in lignin degradation and containing ligninolytic genes such as Burkholderia, Bradyrhizobium, and Azospirillum exhibited increased transcriptional activity in forest soil. Higher solar radiation in grassland presumably induced increased transcription of photosynthesis-related genes within this land use type. This is in accordance with high abundance of photosynthetic organisms and plant-infecting viruses in grassland."],["dc.identifier.doi","10.1007/s00248-014-0377-6"],["dc.identifier.isi","000334495000019"],["dc.identifier.pmid","24553913"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/33623"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1432-184X"],["dc.relation.issn","0095-3628"],["dc.title","Land Use Type Significantly Affects Microbial Gene Transcription in Soil"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","960"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Bioinformatics"],["dc.bibliographiccitation.lastpage","961"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Schreiber, Fabian"],["dc.contributor.author","Gumrich, Peter"],["dc.contributor.author","Daniel, Rolf"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T08:44:21Z"],["dc.date.available","2018-11-07T08:44:21Z"],["dc.date.issued","2010"],["dc.description.abstract","Assessment of phylogenetic diversity is a key element to the analysis of microbial communities. Tools are needed to handle next-generation sequencing data and to cope with the computational complexity of large-scale studies. Here, we present Treephyler, a tool for fast taxonomic profiling of metagenomes. Treephyler was evaluated on real metagenome to assess its performance in comparison to previous approaches for taxonomic profiling. Results indicate that Treephyler is in terms of speed and accuracy prepared for next-generation sequencing techniques and large-scale analysis."],["dc.description.sponsorship","DFG (German Research Foundation) [Wo896/6-1,2]"],["dc.identifier.doi","10.1093/bioinformatics/btq070"],["dc.identifier.isi","000276045800016"],["dc.identifier.pmid","20172941"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/20178"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1367-4803"],["dc.title","Treephyler: fast taxonomic profiling of metagenomes"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1556"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","The Plant Cell"],["dc.bibliographiccitation.lastpage","1572"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Lingner, Thomas"],["dc.contributor.author","Kataya, Amr R."],["dc.contributor.author","Antonicelli, Gerardo E."],["dc.contributor.author","Benichou, Aline"],["dc.contributor.author","Nilssen, Kjersti"],["dc.contributor.author","Chen, Xiong-Yan"],["dc.contributor.author","Siemsen, Tanja"],["dc.contributor.author","Morgenstern, Burkhard"],["dc.contributor.author","Meinicke, Peter"],["dc.contributor.author","Reumann, Sigrun"],["dc.date.accessioned","2018-11-07T08:57:10Z"],["dc.date.available","2018-11-07T08:57:10Z"],["dc.date.issued","2011"],["dc.description.abstract","In the postgenomic era, accurate prediction tools are essential for identification of the proteomes of cell organelles. Prediction methods have been developed for peroxisome-targeted proteins in animals and fungi but are missing specifically for plants. For development of a predictor for plant proteins carrying peroxisome targeting signals type 1 (PTS1), we assembled more than 2500 homologous plant sequences, mainly from EST databases. We applied a discriminative machine learning approach to derive two different prediction methods, both of which showed high prediction accuracy and recognized specific targeting-enhancing patterns in the regions upstream of the PTS1 tripeptides. Upon application of these methods to the Arabidopsis thaliana genome, 392 gene models were predicted to be peroxisome targeted. These predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal. The prediction methods were able to correctly infer novel PTS1 tripeptides, which even included novel residues. Twenty-three newly predicted PTS1 tripeptides were experimentally confirmed, and a high variability of the plant PTS1 motif was discovered. These prediction methods will be instrumental in identifying low-abundance and stress-inducible peroxisomal proteins and defining the entire peroxisomal proteome of Arabidopsis and agronomically important crop plants."],["dc.identifier.doi","10.1105/tpc.111.084095"],["dc.identifier.isi","000291000500030"],["dc.identifier.pmid","21487095"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/23328"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Soc Plant Biologists"],["dc.relation.issn","1040-4651"],["dc.title","Identification of Novel Plant Peroxisomal Targeting Signals by a Combination of Machine Learning Methods and in Vivo Subcellular Targeting Analyses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","973"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Bioinformatics"],["dc.bibliographiccitation.lastpage","980"],["dc.bibliographiccitation.volume","29"],["dc.contributor.author","Klingenberg, Heiner"],["dc.contributor.author","Assauer, Kathrin Petra"],["dc.contributor.author","Lingner, Thomas"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T09:25:59Z"],["dc.date.available","2018-11-07T09:25:59Z"],["dc.date.issued","2013"],["dc.description.abstract","Motivation: Metagenome analysis requires tools that can estimate the taxonomic abundances in anonymous sequence data over the whole range of biological entities. Because there is usually no prior knowledge about the data composition, not only all domains of life but also viruses have to be included in taxonomic profiling. Such a full-range approach, however, is difficult to realize owing to the limited coverage of available reference data. In particular, archaea and viruses are generally not well represented by current genome databases. Results: We introduce a novel approach to taxonomic profiling of metagenomes that is based on mixture model analysis of protein signatures. Our results on simulated and real data reveal the difficulties of the existing methods when measuring achaeal or viral abundances and show the overall good profiling performance of the protein-based mixture model. As an application example, we provide a large-scale analysis of data from the Human Microbiome Project. This demonstrates the utility of our method as a first instance profiling tool for a fast estimate of the community structure."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [ME 3138, LI 2050]"],["dc.identifier.doi","10.1093/bioinformatics/btt077"],["dc.identifier.isi","000318109300002"],["dc.identifier.pmid","23418187"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/30193"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1367-4803"],["dc.title","Protein signature-based estimation of metagenomic abundances including all domains of life and viruses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","369"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","International Journal of Neural Systems"],["dc.bibliographiccitation.lastpage","381"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Mersch, Britta"],["dc.contributor.author","Glasmachers, Tobias"],["dc.contributor.author","Meinicke, Peter"],["dc.contributor.author","Igel, Christian"],["dc.date.accessioned","2018-11-07T10:58:07Z"],["dc.date.available","2018-11-07T10:58:07Z"],["dc.date.issued","2007"],["dc.description.abstract","Oligo kernels for biological sequence classification have a high discriminative power. A new parameterization for the K-mer oligo kernel is presented, where all oligomers of length K are weighted individually. The task specific choice of these parameters increases the classification performance and reveals information about discriminative features. For adapting the multiple kernel parameters based on cross-validation the covariance matrix adaptation evolution strategy is proposed. It is applied to optimize the trimer oligo kernels for the detection of bacterial gene starts. The resulting kernels lead to higher classification rates, and the adapted parameters reveal the importance of particular triplets for classification, for example of those occurring in the Shine-Dalgarno Sequence."],["dc.identifier.doi","10.1142/S0129065707001214"],["dc.identifier.isi","000252398100003"],["dc.identifier.pmid","18098369"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/50408"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","World Scientific Publ Co Pte Ltd"],["dc.relation.issn","0129-0657"],["dc.title","Evolutionary optimization of sequence kernels for detection of bacterial gene starts"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","395"],["dc.bibliographiccitation.issue","7369"],["dc.bibliographiccitation.journal","Nature"],["dc.bibliographiccitation.volume","478"],["dc.contributor.author","Djamei, Armin"],["dc.contributor.author","Schipper, Kerstin"],["dc.contributor.author","Rabe, Franziska"],["dc.contributor.author","Ghosh, Anupama"],["dc.contributor.author","Vincon, Volker"],["dc.contributor.author","Kahnt, Joerg"],["dc.contributor.author","Osorio, Sonia"],["dc.contributor.author","Tohge, Takayuki"],["dc.contributor.author","Fernie, Alisdair R."],["dc.contributor.author","Feussner, Ivo"],["dc.contributor.author","Feussner, Kirstin"],["dc.contributor.author","Meinicke, Peter"],["dc.contributor.author","Stierhof, York-Dieter"],["dc.contributor.author","Schwarz, Heinz"],["dc.contributor.author","Macek, Boris"],["dc.contributor.author","Mann, Matthias"],["dc.contributor.author","Kahmann, Regine"],["dc.date.accessioned","2018-11-07T08:50:40Z"],["dc.date.available","2018-11-07T08:50:40Z"],["dc.date.issued","2011"],["dc.description.abstract","Maize smut caused by the fungus Ustilago maydis is a widespread disease characterized by the development of large plant tumours. U. maydis is a biotrophic pathogen that requires living plant tissue for its development and establishes an intimate interaction zone between fungal hyphae and the plant plasma membrane. U. maydis actively suppresses plant defence responses by secreted protein effectors(1,2). Its effector repertoire comprises at least 386 genes mostly encoding proteins of unknown function(1,3,4) and expressed exclusively during the biotrophic stage(3). The U. maydis secretome also contains about 150 proteins with probable roles in fungal nutrition, fungal cell wall modification and host penetration as well as proteins unlikely to act in the fungal-host interface(4) like a chorismate mutase. Chorismate mutases are key enzymes of the shikimate pathway and catalyse the conversion of chorismate to prephenate, the precursor for tyrosine and phenylalanine synthesis. Root-knot nematodes inject a secreted chorismate mutase into plant cells likely to affect development(5,6). Here we show that the chorismate mutase Cmu1 secreted by U. maydis is a virulence factor. The enzyme is taken up by plant cells, can spread to neighbouring cells and changes the metabolic status of these cells through metabolic priming. Secreted chorismate mutases are found in many plant-associated microbes and might serve as general tools for host manipulation."],["dc.identifier.doi","10.1038/nature10454"],["dc.identifier.isi","000296021100048"],["dc.identifier.pmid","21976020"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/21746"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Nature Publishing Group"],["dc.relation.issn","0028-0836"],["dc.title","Metabolic priming by a secreted fungal effector"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Statistical Applications in Genetics and Molecular Biology"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Bulla, Ingo"],["dc.contributor.author","Schultz, Anne-Kathrin"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T09:15:17Z"],["dc.date.available","2018-11-07T09:15:17Z"],["dc.date.issued","2012"],["dc.description.abstract","Profile Hidden Markov Models (pHMMs) are widely used to model nucleotide or protein sequence families. In many applications, a sequence family classified into several subfamilies is given and each subfamily is modeled separately by one pHMM. A major drawback of this approach is the difficulty of coping with subfamilies composed of very few sequences. Correct subtyping of human immunodeficiency virus-1 (HIV-1) sequences is one of the most crucial bioinformatic tasks affected by this problem of small subfamilies, i.e., HIV-1 subtypes with a small number of known sequences. To deal with small samples for particular subfamilies of HIV-1, we employ a machine learning approach. More precisely, we make use of an existing HMM architecture and its associated inference engine, while replacing the unsupervised estimation of emission probabilities by a supervised method. For that purpose, we use regularized linear discriminant learning together with a balancing scheme to account for the widely varying sample size. After training the multiclass linear discriminants, the corresponding weights are transformed to valid probabilities using a softmax function. We apply this modified algorithm to classify HIV-1 sequence data (in the form of partial-length HIV-1 sequences and semi-artificial recombinants) and show that the performance of pHMMs can be significantly improved by the proposed technique."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [STA 1009/5-1]"],["dc.identifier.doi","10.2202/1544-6115.1680"],["dc.identifier.isi","000305091700001"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/27643"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Walter De Gruyter & Co"],["dc.relation.issn","1544-6115"],["dc.title","Improving Hidden Markov Models for Classification of Human Immunodeficiency Virus-1 Subtypes through Linear Classifier Learning"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]