Dönitz, Jürgen

[["dc.bibliographiccitation.journal","Nucleic acids research"],["dc.contributor.author","Dönitz, Jürgen"],["dc.contributor.author","Gerischer, Lizzy"],["dc.contributor.author","Hahnke, Stefan"],["dc.contributor.author","Pfeiffer, Stefan"],["dc.contributor.author","Bucher, Gregor"],["dc.date.accessioned","2019-07-09T11:44:35Z"],["dc.date.available","2019-07-09T11:44:35Z"],["dc.date.issued","2017-10-24"],["dc.description.abstract","The iBeetle-Base provides access to sequence and phenotype information for genes of the beetle Tribolium castaneum. It has been updated including more and updated data and new functions. RNAi phenotypes are now available for >50% of the genes, which represents an expansion of 60% compared to the previous version. Gene sequence information has been updated based on the new official gene set OGS3 and covers all genes. Interoperability with FlyBase has been enhanced: First, gene information pages of homologous genes are interlinked between both databases. Second, some steps of a new query pipeline allow transforming gene lists from either species into lists with related gene IDs, names or GO terms. This facilitates the comparative analysis of gene functions between fly and beetle. The backend of the pipeline is implemented as endpoints of a RESTful interface, such that it can be reused by other projects or tools. A novel online interface allows the community to propose GO terms for their gene of interest expanding the range of animals where GO terms are defined. iBeetle-Base is available at http://ibeetle-base.uni-goettingen.de/."],["dc.identifier.doi","10.1093/nar/gkx984"],["dc.identifier.pmid","29069517"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14825"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59041"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1362-4962"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Expanded and updated data and a query pipeline for iBeetle-Base."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","D720"],["dc.bibliographiccitation.issue","D1"],["dc.bibliographiccitation.journal","Nucleic Acids Research"],["dc.bibliographiccitation.lastpage","D725"],["dc.bibliographiccitation.volume","43"],["dc.contributor.author","Doenitz, Juergen"],["dc.contributor.author","Schmitt-Engel, Christian"],["dc.contributor.author","Grossmann, Daniela"],["dc.contributor.author","Gerischer, Lizzy"],["dc.contributor.author","Tech, Maike"],["dc.contributor.author","Schoppmeier, Michael"],["dc.contributor.author","Klingler, Martin"],["dc.contributor.author","Bucher, Gregor"],["dc.date.accessioned","2018-11-07T10:01:53Z"],["dc.date.available","2018-11-07T10:01:53Z"],["dc.date.issued","2015"],["dc.description.abstract","The iBeetle-Base (http://ibeetle-base.uni-goettingen.de) makes available annotations of RNAi phenotypes, which were gathered in a large scale RNAi screen in the red flour beetle Tribolium castaneum (iBeetle screen). In addition, it provides access to sequence information and links for all Tribolium cas-taneum genes. The iBeetle-Base contains the annotations of phenotypes of several thousands of genes knocked down during embryonic and metamorphic epidermis and muscle development in addition to phenotypes linked to oogenesis and stink gland biology. The phenotypes are described according to the EQM (entity, quality, modifier) system using controlled vocabularies and the Tribolium morphological ontology (TrOn). Furthermore, images linked to the respective annotations are provided. The data are searchable either for specific phenotypes using a complex 'search for morphological defects' or a 'quick search' for gene names and IDs. The red flour beetle Tribolium castaneum has become an important model system for insect functional genetics and is a representative of the most species rich taxon, the Coleoptera, which comprise several devastating pests. It is used for studying insect typical development, the evolution of development and for research on metabolism and pest control. Besides Drosophila, Tribolium is the first insect model organism where large scale unbiased screens have been performed."],["dc.description.sponsorship","Open-Access-Publikationsfunds 2014"],["dc.identifier.doi","10.1093/nar/gku1054"],["dc.identifier.isi","000350210400105"],["dc.identifier.pmid","25378303"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11085"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/38124"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1362-4962"],["dc.relation.issn","0305-1048"],["dc.rights","CC BY-NC 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by-nc/4.0"],["dc.title","iBeetle-Base: a database for RNAi phenotypes in the red flour beetle Tribolium castaneum"],["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","D540"],["dc.bibliographiccitation.journal","Nucleic Acids Research"],["dc.bibliographiccitation.lastpage","D545"],["dc.bibliographiccitation.volume","34"],["dc.contributor.author","Potapov, Anatolij P."],["dc.contributor.author","Liebich, Ines"],["dc.contributor.author","Doenitz, Juergen"],["dc.contributor.author","Schwarzer, Knut"],["dc.contributor.author","Sasse, Nicole"],["dc.contributor.author","Schoeps, Torsten"],["dc.contributor.author","Crass, Torsten"],["dc.contributor.author","Wingender, Edgar"],["dc.date.accessioned","2018-11-07T10:39:42Z"],["dc.date.available","2018-11-07T10:39:42Z"],["dc.date.issued","2006"],["dc.description.abstract","EndoNet is a new database that provides information about the components of endocrine networks and their relations. It focuses on the endocrine cell-to-cell communication and enables the analysis of intercellular regulatory pathways in humans. In the EndoNet data model, two classes of components span a bipartite directed graph. One class represents the hormones ( in the broadest sense) secreted by defined donor cells. The other class consists of the acceptor or target cells expressing the corresponding hormone receptors. The identity and anatomical environment of cell types, tissues and organs is defined through references to the CYTOMER (R) ontology. With the EndoNet user interface, it is possible to query the database for hormones, receptors or tissues and to combine several items from different search rounds in one complex result set, from which a network can be reconstructed and visualized. For each entity, a detailed characteristics page is available. Some well-established endocrine pathways are offered as showcases in the form of predefined result sets. These sets can be used as a starting point for a more complex query or for obtaining a quick overview. The EndoNet database is accessible at http://endonet.bioinf.med.uni-goettingen.de/."],["dc.identifier.doi","10.1093/nar/gkj121"],["dc.identifier.isi","000239307700117"],["dc.identifier.pmid","16381928"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/46112"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1362-4962"],["dc.relation.issn","0305-1048"],["dc.title","EndoNet: an information resource about endocrine networks"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1905"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Developmental Dynamics"],["dc.bibliographiccitation.lastpage","1916"],["dc.bibliographiccitation.volume","240"],["dc.contributor.author","Halacheva, Viktoriya"],["dc.contributor.author","Fuchs, Mathias"],["dc.contributor.author","Doenitz, Juergen"],["dc.contributor.author","Reupke, Tobias"],["dc.contributor.author","Pueschel, Bernd"],["dc.contributor.author","Viebahn, Christoph"],["dc.date.accessioned","2018-11-07T08:54:01Z"],["dc.date.available","2018-11-07T08:54:01Z"],["dc.date.issued","2011"],["dc.description.abstract","Formation of the mammalian primitive streak appears to rely on cell proliferation to a minor extent only, but compensating cell movements have not yet been directly observed. This study analyses individual cell migration and proliferation simultaneously, using multiphoton and differential interference contrast time-lapse microscopy of late pregastrulation rabbit blastocysts. Epiblast cells in the posterior gastrula extension area accumulated medially and displayed complex planar movements including U-turns and a novel type of processional cell movement. In the same area metaphase plates tended to be aligned parallel to the anterior-posterior axis, and statistical analysis showed that rotations of metaphase plates causing preferred orientation were near-complete 8 min before anaphase onset; in some cases, rotations were strikingly rapid, achieving up to 45 degrees per min. The mammalian primitive streak appears to be formed initially with its typically minimal anteroposterior elongation by a combination of oriented cell divisions with dedicated planar cell movements. Developmental Dynamics 240:1905-1916, 2011. (C) 2011 Wiley-Liss, Inc."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [Vi 151/8-1]"],["dc.identifier.doi","10.1002/dvdy.22687"],["dc.identifier.isi","000292772400004"],["dc.identifier.pmid","21761476"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/22567"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1058-8388"],["dc.title","Planar Cell Movements and Oriented Cell Division During Early Primitive Streak Formation in the Mammalian Embryo"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","W619"],["dc.bibliographiccitation.journal","Nucleic Acids Research"],["dc.bibliographiccitation.lastpage","W624"],["dc.bibliographiccitation.volume","35"],["dc.contributor.author","Degenhardt, Jost"],["dc.contributor.author","Haubrock, Martin"],["dc.contributor.author","Doenitz, Juergen"],["dc.contributor.author","Wingender, Edgar"],["dc.contributor.author","Crass, Torsten"],["dc.date.accessioned","2018-11-07T11:01:14Z"],["dc.date.available","2018-11-07T11:01:14Z"],["dc.date.issued","2007"],["dc.description.abstract","High-throughput methods for measuring transcript abundance, like SAGE or microarrays, are widely used for determining differences in gene expression between different tissue types, dignities (normal/malignant) or time points. Further analysis of such data frequently aims at the identification of gene interaction networks that form the causal basis for the observed properties of the systems under examination. To this end, it is usually not sufficient to rely on the measured gene expression levels alone; rather, additional biological knowledge has to be taken into account in order to generate useful hypotheses about the molecular mechanism leading to the realization of a certain phenotype. We present a method that combines gene expression data with biological expert knowledge on molecular interaction networks, as described by the TRANSPATH(1) database on signal transduction, to predict additional - and not necessarily differentially expressed - genes or gene products which might participate in processes specific for either of the examined tissues or conditions. In a first step, significance values for over-expression in tissue/condition A or B are assigned to all genes in the expression data set. Genes with a significance value exceeding a certain threshold are used as starting points for the reconstruction of a graph with signaling components as nodes and signaling events as edges. In a subsequent graph traversal process, again starting from the previously identified differentially expressed genes, all encountered nodes 'inherit' all their starting nodes' significance values. In a final step, the graph is visualized, the nodes being colored according to a weighted average of their inherited significance values. Each node's, or sub-network's, predominant color, ranging from green (significant for tissue/condition A) over yellow (not significant for either tissue/condition) to red (significant for tissue/condition B), thus gives an immediate visual clue on which molecules - differentially expressed or not - may play pivotal roles in the tissues or conditions under examination. The described method has been implemented in Java as a client/server application and a web interface called DEEP (Differential Expression Effector Prediction). The client, which features an easy-to-use graphical interface, can freely be downloaded from the following URL: http://deep.bioinf.med.uni-goettingen.de."],["dc.identifier.doi","10.1093/nar/gkm469"],["dc.identifier.isi","000255311500115"],["dc.identifier.pmid","17584786"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?goescholar/4016"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/51101"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","0305-1048"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","DEEP - A tool for differential expression effector prediction"],["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.contributor.author","Kurz, Nadine S."],["dc.contributor.author","Perera-Bel, Júlia"],["dc.contributor.author","Höltermann, Charlotte"],["dc.contributor.author","Tucholski, Tim"],["dc.contributor.author","Yang, Jingyu"],["dc.contributor.author","Beissbarth, Tim"],["dc.contributor.author","Dönitz, Jürgen"],["dc.contributor.editor","Röhrig, Rainer"],["dc.contributor.editor","Grabe, Niels"],["dc.contributor.editor","Hoffmann, Verena S."],["dc.contributor.editor","Hübner, Ursula"],["dc.contributor.editor","König, Jochem"],["dc.contributor.editor","Sax, Ulrich"],["dc.contributor.editor","Schreiweis, Björn"],["dc.contributor.editor","Sedlmayr, Martin"],["dc.date.accessioned","2022-10-04T10:21:42Z"],["dc.date.available","2022-10-04T10:21:42Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.3233/SHTI220806"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114480"],["dc.notes.intern","DOI-Import GROB-600"],["dc.publisher","IOS Press"],["dc.relation.crisseries","Studies in Health Technology and Informatics"],["dc.relation.eisbn","9781643683034"],["dc.relation.isbn","9781643683027"],["dc.relation.ispartof","German Medical Data Sciences 2022 – Future Medicine: More Precise, More Integrative, More Sustainable! : Proceedings of the Joint Conference of the 67th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) and the 14th Annual Meeting of the TMF – Technology, Methods, and Infrastructure for Networked Medical Research e.V. 2022 online in Kiel, Germany"],["dc.title","Identifying Actionable Variants in Cancer – The Dual Web and Batch Processing Tool MTB-Report"],["dc.type","book_chapter"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","38"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMC Biology"],["dc.bibliographiccitation.volume","20"],["dc.contributor.author","Hakeemi, Muhammad S."],["dc.contributor.author","Ansari, Salim"],["dc.contributor.author","Teuscher, Matthias"],["dc.contributor.author","Weißkopf, Matthias"],["dc.contributor.author","Großmann, Daniela"],["dc.contributor.author","Kessel, Tobias"],["dc.contributor.author","Dönitz, Jürgen"],["dc.contributor.author","Siemanowski, Janna"],["dc.contributor.author","Wan, Xuebin"],["dc.contributor.author","Schultheis, Dorothea"],["dc.contributor.author","Frasch, Manfred"],["dc.contributor.author","Roth, Siegfried"],["dc.contributor.author","Schoppmeier, Michael"],["dc.contributor.author","Klingler, Martin"],["dc.contributor.author","Bucher, Gregor"],["dc.date.accessioned","2022-04-01T10:03:06Z"],["dc.date.accessioned","2022-08-18T12:34:50Z"],["dc.date.available","2022-04-01T10:03:06Z"],["dc.date.available","2022-08-18T12:34:50Z"],["dc.date.issued","2022-02-08"],["dc.date.updated","2022-07-29T12:07:11Z"],["dc.description.abstract","Abstract\r\n \r\n Background\r\n Most of the known genes required for developmental processes have been identified by genetic screens in a few well-studied model organisms, which have been considered representative of related species, and informative—to some degree—for human biology. The fruit fly Drosophila melanogaster is a prime model for insect genetics, and while conservation of many gene functions has been observed among bilaterian animals, a plethora of data show evolutionary divergence of gene function among more closely-related groups, such as within the insects. A quantification of conservation versus divergence of gene functions has been missing, without which it is unclear how representative data from model systems actually are.\r\n \r\n \r\n Results\r\n Here, we systematically compare the gene sets required for a number of homologous but divergent developmental processes between fly and beetle in order to quantify the difference of the gene sets. To that end, we expanded our RNAi screen in the red flour beetle Tribolium castaneum to cover more than half of the protein-coding genes. Then we compared the gene sets required for four different developmental processes between beetle and fly. We found that around 50% of the gene functions were identified in the screens of both species while for the rest, phenotypes were revealed only in fly (~ 10%) or beetle (~ 40%) reflecting both technical and biological differences. Accordingly, we were able to annotate novel developmental GO terms for 96 genes studied in this work. With this work, we publish the final dataset for the pupal injection screen of the iBeetle screen reaching a coverage of 87% (13,020 genes).\r\n \r\n \r\n Conclusions\r\n We conclude that the gene sets required for a homologous process diverge more than widely believed. Hence, the insights gained in flies may be less representative for insects or protostomes than previously thought, and work in complementary model systems is required to gain a comprehensive picture. The RNAi screening resources developed in this project, the expanding transgenic toolkit, and our large-scale functional data make T. castaneum an excellent model system in that endeavor."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.citation","BMC Biology. 2022 Feb 08;20(1):38"],["dc.identifier.doi","10.1186/s12915-022-01231-4"],["dc.identifier.pii","1231"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/106084"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112934"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-530"],["dc.publisher","BioMed Central"],["dc.relation.eissn","1741-7007"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject","Gene function"],["dc.subject","Comparative genomics"],["dc.subject","RNAi screen"],["dc.subject","iBeetle"],["dc.subject","Tribolium castaneum"],["dc.subject","Drosophila melanogaster"],["dc.subject","Divergence of gene function"],["dc.subject","iBeetle-Base"],["dc.subject","FlyBase"],["dc.title","Screens in fly and beetle reveal vastly divergent gene sets required for developmental processes"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","D689"],["dc.bibliographiccitation.journal","Nucleic Acids Research"],["dc.bibliographiccitation.lastpage","D694"],["dc.bibliographiccitation.volume","36"],["dc.contributor.author","Doenitz, Juergen"],["dc.contributor.author","Goemann, Bjoern"],["dc.contributor.author","Lize, Muriel"],["dc.contributor.author","Michael, Holger"],["dc.contributor.author","Sasse, Nicole"],["dc.contributor.author","Wingender, Edgar"],["dc.contributor.author","Potapov, Anatolij P."],["dc.date.accessioned","2018-11-07T11:20:30Z"],["dc.date.available","2018-11-07T11:20:30Z"],["dc.date.issued","2008"],["dc.description.abstract","EndoNet is an information resource about intercellular regulatory communication. It provides information about hormones, hormone receptors, the sources (i.e. cells, tissues and organs) where the hormones are synthesized and secreted, and where the respective receptors are expressed. The database focuses on the regulatory relations between them. An elementary communication is displayed as a causal link from a cell that secretes a particular hormone to those cells which express the corresponding hormone receptor and respond to the hormone. Whenever expression, synthesis and/or secretion of another hormone are part of this response, it renders the corresponding cell an internal node of the resulting network. This intercellular communication network coordinates the function of different organs. Therefore, the database covers the hierarchy of cellular organization of tissues and organs as it has been modeled in the Cytomer ontology, which has now been directly embedded into EndoNet. The user can query the database; the results can be used to visualize the intercellular information flow. A newly implemented hormone classification enables to browse the database and may be used as alternative entry point. EndoNet is accessible at: http://endonet.bioinf.med.uni-goettingen.de/."],["dc.identifier.doi","10.1093/nar/gkm940"],["dc.identifier.isi","000252545400124"],["dc.identifier.pmid","18045786"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?goescholar/4133"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/55550"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1362-4962"],["dc.relation.issn","0305-1048"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","EndoNet: an information resource about regulatory networks of cell-to-cell communication"],["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","197"],["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.journal","Frontiers in genetics"],["dc.bibliographiccitation.lastpage","11"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Dönitz, Jürgen"],["dc.contributor.author","Wingender, Edgar"],["dc.date.accessioned","2019-07-09T11:53:51Z"],["dc.date.available","2019-07-09T11:53:51Z"],["dc.date.issued","2012"],["dc.description.abstract","The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and \"partOf\" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba."],["dc.identifier.doi","10.3389/fgene.2012.00197"],["dc.identifier.fs","590598"],["dc.identifier.pmid","23060901"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8162"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60514"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.publisher","Frontiers Research Foundation"],["dc.relation.eissn","1664-8021"],["dc.relation.issn","1664-8021"],["dc.rights","http://www.frontiersin.org/licenseagreement"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","The ontology-based answers (OBA) service: a connector for embedded usage of ontologies in applications."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","7822"],["dc.bibliographiccitation.journal","Nature Communications"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Schmitt-Engel, Christian"],["dc.contributor.author","Schultheis, Dorothea"],["dc.contributor.author","Schwirz, Jonas"],["dc.contributor.author","Stroehlein, Nadi"],["dc.contributor.author","Troelenberg, Nicole"],["dc.contributor.author","Majumdar, Upalparna"],["dc.contributor.author","Dao, Van Anh"],["dc.contributor.author","Grossmann, Daniela"],["dc.contributor.author","Richter, Tobias"],["dc.contributor.author","Tech, Maike"],["dc.contributor.author","Doenitz, Juergen"],["dc.contributor.author","Gerischer, Lizzy"],["dc.contributor.author","Theis, Mirko"],["dc.contributor.author","Schild, Inga"],["dc.contributor.author","Trauner, Jochen"],["dc.contributor.author","Koniszewski, Nikolaus Dieter Bernhard"],["dc.contributor.author","Kuester, Elke"],["dc.contributor.author","Kittelmann, Sebastian"],["dc.contributor.author","Hu, Yonggang"],["dc.contributor.author","Lehmann, Sabrina"],["dc.contributor.author","Siemanowski, Janna L."],["dc.contributor.author","Ulrich, Julia"],["dc.contributor.author","Panfilio, Kristen A."],["dc.contributor.author","Schroeder, Reinhard"],["dc.contributor.author","Morgenstern, Burkhard"],["dc.contributor.author","Stanke, Mario"],["dc.contributor.author","Buchhholz, Frank"],["dc.contributor.author","Frasch, Manfred"],["dc.contributor.author","Roth, Siegfried"],["dc.contributor.author","Wimmer, Ernst A."],["dc.contributor.author","Schoppmeier, Michael"],["dc.contributor.author","Klingler, Martin"],["dc.contributor.author","Bucher, Gregor"],["dc.date.accessioned","2018-11-07T09:55:00Z"],["dc.date.available","2018-11-07T09:55:00Z"],["dc.date.issued","2015"],["dc.description.abstract","Genetic screens are powerful tools to identify the genes required for a given biological process. However, for technical reasons, comprehensive screens have been restricted to very few model organisms. Therefore, although deep sequencing is revealing the genes of ever more insect species, the functional studies predominantly focus on candidate genes previously identified in Drosophila, which is biasing research towards conserved gene functions. RNAi screens in other organisms promise to reduce this bias. Here we present the results of the iBeetle screen, a large-scale, unbiased RNAi screen in the red flour beetle, Tribolium castaneum, which identifies gene functions in embryonic and postembryonic development, physiology and cell biology. The utility of Tribolium as a screening platform is demonstrated by the identification of genes involved in insect epithelial adhesion. This work transcends the restrictions of the candidate gene approach and opens fields of research not accessible in Drosophila."],["dc.description.sponsorship","Open-Access Publikationsfonds 2015"],["dc.identifier.doi","10.1038/ncomms8822"],["dc.identifier.isi","000358860900002"],["dc.identifier.pmid","26215380"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12460"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36659"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","2041-1723"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","The iBeetle large-scale RNAi screen reveals gene functions for insect development and physiology"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]