Kaever, Alexander

[["dc.bibliographiccitation.artnumber","263910"],["dc.bibliographiccitation.journal","JOURNAL OF BIOMEDICINE AND BIOTECHNOLOGY"],["dc.contributor.author","Kaever, Alexander"],["dc.contributor.author","Landesfeind, Manuel"],["dc.contributor.author","Possienke, Mareike"],["dc.contributor.author","Feussner, Kirstin"],["dc.contributor.author","Feussner, Ivo"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T09:15:23Z"],["dc.date.available","2018-11-07T09:15:23Z"],["dc.date.issued","2012"],["dc.description.abstract","Statistical ranking, filtering, adduct detection, isotope correction, and molecular formula calculation are essential tasks in processing mass spectrometry data in metabolomics studies. In order to obtain high-quality data sets, a framework which incorporates all these methods is required. We present the MarVis-Filter software, which provides well-established and specialized methods for processing mass spectrometry data. For the task of ranking and filtering multivariate intensity profiles, MarVis-Filter provides the ANOVA and Kruskal-Wallis tests with adjustment for multiple hypothesis testing. Adduct and isotope correction are based on a novel algorithm which takes the similarity of intensity profiles into account and allows user-defined ionization rules. The molecular formula calculation utilizes the results of the adduct and isotope correction. For a comprehensive analysis, MarVis-Filter provides an interactive interface to combine data sets deriving from positive and negative ionization mode. The software is exemplarily applied in a metabolic case study, where octadecanoids could be identified as markers for wounding in plants."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2012"],["dc.identifier.doi","10.1155/2012/263910"],["dc.identifier.isi","000303726300001"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7716"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/27674"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Hindawi Publishing Corporation"],["dc.relation.issn","1110-7243"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","MarVis-Filter: Ranking, Filtering, Adduct and Isotope Correction of Mass Spectrometry Data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e89297"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Kaever, Alexander"],["dc.contributor.author","Landesfeind, Manuel"],["dc.contributor.author","Feussner, Kirstin"],["dc.contributor.author","Morgenstern, Burkhard"],["dc.contributor.author","Feussner, Ivo"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T09:43:35Z"],["dc.date.available","2018-11-07T09:43:35Z"],["dc.date.issued","2014"],["dc.description.abstract","A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e. g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2014"],["dc.identifier.doi","10.1371/journal.pone.0089297"],["dc.identifier.isi","000332396200047"],["dc.identifier.pmid","24586671"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/9992"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/34212"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Meta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Frontiers in Microbiology"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Leonard, Miriam"],["dc.contributor.author","Kühn, Anika"],["dc.contributor.author","Harting, Rebekka"],["dc.contributor.author","Maurus, Isabel"],["dc.contributor.author","Nagel, Alexandra"],["dc.contributor.author","Starke, Jessica"],["dc.contributor.author","Kusch, Harald"],["dc.contributor.author","Valerius, Oliver"],["dc.contributor.author","Feussner, Kirstin"],["dc.contributor.author","Feussner, Ivo"],["dc.contributor.author","Kaever, Alexander"],["dc.contributor.author","Landesfeind, Manuel"],["dc.contributor.author","Morgenstern, Burkhard"],["dc.contributor.author","Becher, Dörte"],["dc.contributor.author","Hecker, Michael"],["dc.contributor.author","Braus-Stromeyer, Susanna A."],["dc.contributor.author","Kronstad, James W."],["dc.contributor.author","Braus, Gerhard H."],["dc.date.accessioned","2021-04-14T08:23:50Z"],["dc.date.available","2021-04-14T08:23:50Z"],["dc.date.issued","2020"],["dc.description.abstract","Verticillia cause a vascular wilt disease affecting a broad range of economically valuable crops. The fungus enters its host plants through the roots and colonizes the vascular system. It requires extracellular proteins for a successful plant colonization. The exoproteomes of the allodiploid Verticillium longisporum upon cultivation in different media or xylem sap extracted from its host plant Brassica napus were compared. Secreted fungal proteins were identified by label free liquid chromatography-tandem mass spectrometry screening. V. longisporum induced two main secretion patterns. One response pattern was elicited in various non-plant related environments. The second pattern includes the exoprotein responses to the plant-related media, pectin-rich simulated xylem medium and pure xylem sap, which exhibited similar but additional distinct features. These exoproteomes include a shared core set of 221 secreted and similarly enriched fungal proteins. The pectin-rich medium significantly induced the secretion of 143 proteins including a number of pectin degrading enzymes, whereas xylem sap triggered a smaller but unique fungal exoproteome pattern with 32 enriched proteins. The latter pattern included proteins with domains of known pathogenicity factors, metallopeptidases and carbohydrate-active enzymes. The most abundant proteins of these different groups are the necrosis and ethylene inducing-like proteins Nlp2 and Nlp3, the cerato-platanin proteins Cp1 and Cp2, the metallopeptidases Mep1 and Mep2 and the carbohydrate-active enzymes Gla1, Amy1 and Cbd1. Their pathogenicity contribution was analyzed in the haploid parental strain V. dahliae. Deletion of the majority of the corresponding genes caused no phenotypic changes during ex planta growth or invasion and colonization of tomato plants. However, we discovered that the MEP1, NLP2, and NLP3 deletion strains were compromised in plant infections. Overall, our exoproteome approach revealed that the fungus induces specific secretion responses in different environments. The fungus has a general response to non-plant related media whereas it is able to fine-tune its exoproteome in the presence of plant material. Importantly, the xylem sap-specific exoproteome pinpointed Nlp2 and Nlp3 as single effectors required for successful V. dahliae colonization."],["dc.identifier.doi","10.3389/fmicb.2020.01876"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17508"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81068"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.notes.intern","Merged from goescholar"],["dc.publisher","Frontiers Media S.A."],["dc.relation.eissn","1664-302X"],["dc.rights","http://creativecommons.org/licenses/by/4.0/"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Verticillium longisporum Elicits Media-Dependent Secretome Responses With Capacity to Distinguish Between Plant-Related Environments"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e239"],["dc.bibliographiccitation.journal","PeerJ"],["dc.bibliographiccitation.volume","2"],["dc.contributor.author","Landesfeind, Manuel"],["dc.contributor.author","Kaever, Alexander"],["dc.contributor.author","Feussner, Kirstin"],["dc.contributor.author","Thurow, Corinna"],["dc.contributor.author","Gatz, Christiane"],["dc.contributor.author","Feussner, Ivo"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T09:42:35Z"],["dc.date.available","2018-11-07T09:42:35Z"],["dc.date.issued","2014"],["dc.description.abstract","State of the art high-throughput technologies allow comprehensive experimental studies of organism metabolism and induce the need for a convenient presentation of large heterogeneous datasets. Especially, the combined analysis and visualization of data from different high-throughput technologies remains a key challenge in bioinformatics. We present here the MarVis-Graph software for integrative analysis of metabolic and transcriptomic data. All experimental data is investigated in terms of the full metabolic network obtained from a reference database. The reactions of the network are scored based on the associated data, and sub-networks, according to connected high-scoring reactions, are identified. Finally, MarVis-Graph scores the detected sub-networks, evaluates them by means of a random permutation test and presents them as a ranked list. Furthermore, MarVis-Graph features an interactive network visualization that provides researchers with a convenient view on the results. The key advantage of MarVis-Graph is the analysis of reactions detached from their pathways so that it is possible to identify new pathways or to connect known pathways by previously unrelated reactions. The MarVis-Graph software is freely available for academic use and can be downloaded at: http://marvis.gobics.de/marvis-graph."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2014"],["dc.identifier.doi","10.7717/peerj.239"],["dc.identifier.isi","000347564400001"],["dc.identifier.pmid","24688832"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10012"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/33990"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Peerj Inc"],["dc.relation.issn","2167-8359"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Integrative study of Arabidopsis thaliana metabolomic and transcriptomic data with the interactive MarVis-Graph software"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","764"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Metabolomics"],["dc.bibliographiccitation.lastpage","777"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Kaever, Alexander"],["dc.contributor.author","Landesfeind, Manuel"],["dc.contributor.author","Feussner, Kirstin"],["dc.contributor.author","Mosblech, Alina"],["dc.contributor.author","Heilmann, Ingo"],["dc.contributor.author","Morgenstern, Burkhard"],["dc.contributor.author","Feussner, Ivo"],["dc.contributor.author","Meinicke, Peter"],["dc.date.accessioned","2018-11-07T09:56:52Z"],["dc.date.available","2018-11-07T09:56:52Z"],["dc.date.issued","2015"],["dc.description.abstract","A central aim in the evaluation of non-targeted metabolomics data is the detection of intensity patterns that differ between experimental conditions as well as the identification of the underlying metabolites and their association with metabolic pathways. In this context, the identification of metabolites based on non-targeted mass spectrometry data is a major bottleneck. In many applications, this identification needs to be guided by expert knowledge and interactive tools for exploratory data analysis can significantly support this process. Additionally, the integration of data from other omics platforms, such as DNA microarray-based transcriptomics, can provide valuable hints and thereby facilitate the identification of metabolites via the reconstruction of related metabolic pathways. We here introduce the MarVis-Pathway tool, which allows the user to identify metabolites by annotation of pathways from cross-omics data. The analysis is supported by an extensive framework for pathway enrichment and meta-analysis. The tool allows the mapping of data set features by ID, name, and accurate mass, and can incorporate information from adduct and isotope correction of mass spectrometry data. MarVis-Pathway was integrated in the MarVis-Suite (http://marvis.gobics.de), which features the seamless highly interactive filtering, combination, clustering, and visualization of omics data sets. The functionality of the new software tool is illustrated using combined mass spectrometry and DNA microarray data. This application confirms jasmonate biosynthesis as important metabolic pathway that is upregulated during the wound response of Arabidopsis plants."],["dc.identifier.doi","10.1007/s11306-014-0734-y"],["dc.identifier.isi","000354137100020"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11152"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37052"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1573-3890"],["dc.relation.issn","1573-3882"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]