Potapov, Anatolij P.

[["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","97"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Nucleic Acids Research"],["dc.bibliographiccitation.lastpage","100"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Krull, Mathias"],["dc.contributor.author","Voss, Nico"],["dc.contributor.author","Choi, Claudia"],["dc.contributor.author","Pistor, Susanne"],["dc.contributor.author","Potapov, Anatolij"],["dc.contributor.author","Wingender, Edgar"],["dc.date.accessioned","2019-07-10T08:12:52Z"],["dc.date.available","2019-07-10T08:12:52Z"],["dc.date.issued","2003"],["dc.description.abstract","TRANSPATH® is a database system about gene regulatory networks that combines encyclopedic information on signal transduction with tools for visualization and analysis. The integration with TRANSFAC®, a database about transcription factors and their DNA binding sites, provides the possibility to obtain complete signaling pathways from ligand to target genes and their products, which may themselves be involved in regulatory action. As of July 2002, the TRANSPATH Professional release 3.2 contains about 9800 molecules, >1800 genes and >11 400 reactions collected from ~5000 references. With the ArrayAnalyzerTM, an integrated tool has been developed for evaluation of microarray data. It uses the TRANSPATH data set to identify key regulators in pathways connected with up- or down-regulated genes of the respective array. The key molecules and their surrounding networks can be viewed with the PathwayBuilderTM, a tool that offers four different modes of visualization. More information on TRANSPATH is available at http://www.biobase.de/pages/products/databases.html."],["dc.identifier.fs","12173"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?goescholar/4112"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/61065"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1362-4962"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.ddc","610"],["dc.title","TRANSPATH (R): an integrated database on signal transduction and a tool for array analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","European Journal of Cell Biology"],["dc.bibliographiccitation.volume","83"],["dc.contributor.author","Pistor, S."],["dc.contributor.author","Choi, C."],["dc.contributor.author","Krull, M."],["dc.contributor.author","Voss, Nico"],["dc.contributor.author","Potapov, Anatolij P."],["dc.contributor.author","Wingender, Edgar"],["dc.date.accessioned","2018-11-07T10:50:35Z"],["dc.date.available","2018-11-07T10:50:35Z"],["dc.date.issued","2004"],["dc.format.extent","33"],["dc.identifier.isi","000220823900046"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/48689"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Urban & Fischer Verlag"],["dc.publisher.place","Jena"],["dc.relation.conference","Annual Meeting of the Deutschen-Gesellschaft-fur-Zellbiologie"],["dc.relation.eventlocation","Berlin, Germany"],["dc.relation.issn","0171-9335"],["dc.title","Analysis of the regulatory network of APP, amyloid beta protein precursor, with the signal transcluction database TRANSPATH (R) Professional"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["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.firstpage","1"],["dc.bibliographiccitation.issue","227"],["dc.bibliographiccitation.journal","BMC bioinformatics"],["dc.bibliographiccitation.lastpage","15"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Potapov, Anatolij P."],["dc.contributor.author","Goemann, Björn"],["dc.contributor.author","Wingender, Edgar"],["dc.date.accessioned","2019-07-10T08:12:56Z"],["dc.date.available","2019-07-10T08:12:56Z"],["dc.date.issued","2008"],["dc.description.abstract","Background: Currently, there is a gap between purely theoretical studies of the topology of large bioregulatory networks and the practical traditions and interests of experimentalists. While the theoretical approaches emphasize the global characterization of regulatory systems, the practical approaches focus on the role of distinct molecules and genes in regulation. To bridge the gap between these opposite approaches, one needs to combine 'general' with 'particular' properties and translate abstract topological features of large systems into testable functional characteristics of individual components. Here, we propose a new topological parameter the pairwise disconnectivity index of a network's element that is capable of such bridging. Results: The pairwise disconnectivity index quantifies how crucial an individual element is for sustaining the communication ability between connected pairs of vertices in a network that is displayed as a directed graph. Such an element might be a vertex (i.e., molecules, genes), an edge (i.e., reactions, interactions), as well as a group of vertices and/or edges. The index can be viewed as a measure of topological redundancy of regulatory paths which connect different parts of a given network and as a measure of sensitivity (robustness) of this network to the presence (absence) of each individual element. Accordingly, we introduce the notion of a path-degree of a vertex in terms of its corresponding incoming, outgoing and mediated paths, respectively. The pairwise disconnectivity index has been applied to the analysis of several regulatory networks from various organisms. The importance of an individual vertex or edge for the coherence of the network is determined by the particular position of the given element in the whole network.Conclusion: Our approach enables to evaluate the effect of removing each element (i.e., vertex, edge, or their combinations) from a network. The greatest potential value of this approach is its ability to systematically analyze the role of every element, as well as groups of elements, in a regulatory network."],["dc.identifier.fs","208708"],["dc.identifier.ppn","575637900"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/4333"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/61079"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.ddc","610"],["dc.title","The pairwise disconnectivity index as a new metric for the topological analysis of regulatory networks"],["dc.title.alternative","Methodology article"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","53"],["dc.bibliographiccitation.journal","BMC Systems Biology"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Goemann, Bjoern"],["dc.contributor.author","Wingender, Edgar"],["dc.contributor.author","Potapov, Anatolij P."],["dc.date.accessioned","2018-11-07T08:29:52Z"],["dc.date.available","2018-11-07T08:29:52Z"],["dc.date.issued","2009"],["dc.description.abstract","Background: The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. Results: The pairwise disconnectivity index of a pattern instance quantifies the dependency of the pairwise connections between vertices in a network on the presence of this pattern instance. Thereby, it particularly considers how the coherence between the unique constituents of a pattern instance relates to the rest of a network. We have applied the method exemplarily to the analysis of 3-vertex topological pattern instances in the transcription networks of a bacteria (E. coli), a unicellular eukaryote (S. cerevisiae) and higher eukaryotes (human, mouse, rat). We found that in these networks only very few pattern instances break lots of the pairwise connections between vertices upon the removal of an instance. Among them network motifs do not prevail. Rather, those patterns that are shared by the three networks exhibit a conspicuously enhanced pairwise disconnectivity index. Additionally, these are often located in close vicinity to each other or are even overlapping, since only a small number of genes are repeatedly present in most of them. Moreover, evidence has gathered that the importance of these pattern instances is due to synergistic rather than merely additive effects between their constituents. Conclusion: A new method has been proposed that enables to evaluate the topological significance of various connected patterns in a regulatory network. Applying this method onto transcriptional networks of three largely distinct organisms we could prove that it is highly suitable to identify most important pattern instances, but that neither motifs nor any pattern in general appear to play a particularly important role per se. From the results obtained so far, we conclude that the pairwise disconnectivity index will most likely prove useful as well in identifying other (higher-order) pattern instances in transcriptional and other networks."],["dc.identifier.doi","10.1186/1752-0509-3-53"],["dc.identifier.isi","000266992100001"],["dc.identifier.pmid","19454001"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/5762"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/16757"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1752-0509"],["dc.rights","CC BY 2.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.0"],["dc.title","An approach to evaluate the topological significance of motifs and other patterns in regulatory networks"],["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","169"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of biosciences"],["dc.bibliographiccitation.lastpage","180"],["dc.bibliographiccitation.volume","32"],["dc.contributor.author","Wingender, Edgar"],["dc.contributor.author","Crass, Torsten"],["dc.contributor.author","Hogan, Jennifer D."],["dc.contributor.author","Kel, Alexander E."],["dc.contributor.author","Kel-Margoulis, Olga V."],["dc.contributor.author","Potapov, Anatolij P."],["dc.date.accessioned","2019-07-10T08:11:49Z"],["dc.date.available","2019-07-10T08:11:49Z"],["dc.date.issued","2007"],["dc.description.abstract","Bioinformatics has delivered great contributions to genome and genomics research, without which the world-wide success of this and other global ('omics') approaches would not have been possible. More recently, it has developed further towards the analysis of different kinds of networks thus laying the foundation for comprehensive description, analysis and manipulation of whole living systems in modern \"systems biology\". The next step which is necessary for developing a systems biology that deals with systemic phenomena is to expand the existing and develop new methodologies that are appropriate to characterize intercellular processes and interactions without omitting the causal underlying molecular mechanisms. Modelling the processes on the different levels of complexity involved requires a comprehensive integration of information on gene regulatory events, signal transduction pathways, protein interaction and metabolic networks as well as cellular functions in the respective tissues / organs."],["dc.identifier.pmid","17426389"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11190"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60805"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","0250-5991"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.subject.mesh","Animals"],["dc.subject.mesh","Cell Communication"],["dc.subject.mesh","Cell Physiological Phenomena"],["dc.subject.mesh","Computational Biology"],["dc.subject.mesh","Databases, Genetic"],["dc.subject.mesh","Gene Regulatory Networks"],["dc.subject.mesh","Genomics"],["dc.subject.mesh","Hormones"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Metabolic Networks and Pathways"],["dc.subject.mesh","Signal Transduction"],["dc.subject.mesh","Systems Biology"],["dc.title","Integrative content-driven concepts for bioinformatics \"beyond the cell\"."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","163"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","COMPARATIVE AND FUNCTIONAL GENOMICS"],["dc.bibliographiccitation.lastpage","168"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Choi, C."],["dc.contributor.author","Krull, M."],["dc.contributor.author","Kel, Alexander E."],["dc.contributor.author","Kel-Margoulis, Olga V."],["dc.contributor.author","Pistor, S."],["dc.contributor.author","Potapov, Anatolij P."],["dc.contributor.author","Voss, Nico"],["dc.contributor.author","Wingender, Edgar"],["dc.date.accessioned","2018-11-07T10:50:32Z"],["dc.date.available","2018-11-07T10:50:32Z"],["dc.date.issued","2004"],["dc.description.abstract","TRANSPATH(R) can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyser. Therefore, three modules have been created: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder(TM), which provides several different types of network visualization and hence faciliates understanding; the third is ArrayAnalyzer(TM), which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH(R) to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH(R) is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC(R), a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes. More information is available at www.biobase.de/pages/products/databases.html. Copyright (C) 2004 John Wiley Sons, Ltd."],["dc.identifier.doi","10.1002/cfg.386"],["dc.identifier.isi","000221783700006"],["dc.identifier.pmid","18629064"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/4431"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/48676"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","John Wiley & Sons Ltd"],["dc.relation.issn","1531-6912"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","TRANSPATH (R) - a high quality database focused on signal transduction"],["dc.type","review"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","012031"],["dc.contributor.author","Rizqulloh, M. N."],["dc.contributor.author","Drescher, Jochen"],["dc.contributor.author","Hartke, T. R."],["dc.contributor.author","Potapov, Anatolij P."],["dc.contributor.author","Scheu, Stefan"],["dc.contributor.author","Hidayat, P."],["dc.contributor.author","Widyastuti, R."],["dc.date.accessioned","2021-08-12T12:41:50Z"],["dc.date.available","2021-08-12T12:41:50Z"],["dc.date.issued","2021"],["dc.description.abstract","Ants (Formicidae) are fundamental components of almost every terrestrial ecosystem, especially in the tropics. While epigaeic ants are extensively studied, hypogaeic, soil living ants are still neglected to a large extent. To remedy this, in this paper we explore the effects of rainforest transformation cash crop monocultures on abundance, richness and community composition of soil living ants (Formicidae). Ants in this study were procured as a by-product of extensive sampling of soil meso- and macrofauna along a land-use gradient from lowland rainforest via jungle rubber to monocultures of rubber and oil palm in Jami Province, Sumatra, Indonesia. Sampled in 32 plots of 50 * 50 m each, with three 16 cm * 16 cm * 5 cm soil cores each, we collected 2.079 worker ant individuals, belonging to 90 morphospecies from 37 genera and six subfamilies. Land use had a significant effect on abundance and richness, while distance-based community composition was not affected. Cumulatively, lowland rainforest had the highest number of ant species exclusively living in it, and the highest average ant abundance, although multiple comparison tests did not detect significant differences. We also found highest species richness in the lowland rainforest in one of the two investigated landscapes, while not significantly different from the agricultural systems in the other. High abundance variances among the sample sites suggest inadequacy of the sampling method, however. Despite that, our study provides a first glimpse into hypogaeic ant community responses to rainforest conversion to cash crop monocultures in Sumatra, Indonesia."],["dc.identifier.doi","10.1088/1755-1315/771/1/012031"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/88695"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.relation","SFB 990: Ökologische und sozioökonomische Funktionen tropischer Tieflandregenwald-Transformationssysteme (Sumatra, Indonesien)"],["dc.relation","SFB 990 | B | B08: Struktur und Funktion des Zersetzersystems in Transformationssystemen von Tiefland-Regenwäldern"],["dc.relation","SFB 990 | Z | Z02: Central Scientific Support Unit"],["dc.relation.conference","2nd International Symposium on Transdisciplinarity Approach for Knowledge Co-Creation in Sustainability - Understanding Complexity and Transdisciplinarity for Environmental Sustainability"],["dc.relation.eventend","2020-11-04"],["dc.relation.eventlocation","Bogor, Indonesia"],["dc.relation.eventstart","2020-11-03"],["dc.relation.iserratumof","yes"],["dc.rights","CC BY 3.0"],["dc.subject.gro","Journal Article"],["dc.subject.gro","ABS"],["dc.subject.gro","sfb990_journalarticles"],["dc.subject.gro","sfb990_abs"],["dc.title","Effects of rainforest transformation to monoculture cash crops on soil living ants (Formicidae) in Jambi Province, Sumatra, Indonesia"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Strahlentherapie und Onkologie"],["dc.bibliographiccitation.volume","188"],["dc.contributor.author","Roedel, Claus"],["dc.contributor.author","Larsch, T."],["dc.contributor.author","Becker, H."],["dc.contributor.author","Fietkau, Rainer"],["dc.contributor.author","Hohenberger, Werner"],["dc.contributor.author","Hothorn, T."],["dc.contributor.author","Graeven, Ullrich"],["dc.contributor.author","Arnold, Dirk"],["dc.contributor.author","Lang-Welzenbach, M."],["dc.contributor.author","Raab, H.-R"],["dc.contributor.author","Suelberg, Heiko"],["dc.contributor.author","Wittekind, Christian"],["dc.contributor.author","Potapov, S."],["dc.contributor.author","Staib, Ludger"],["dc.contributor.author","Hess, C. F."],["dc.contributor.author","Weigang-Koehler, K."],["dc.contributor.author","Grabenbauer, G. G."],["dc.contributor.author","Hoffmans, H."],["dc.contributor.author","Lindemann, F."],["dc.contributor.author","Schlenska-Lange, A."],["dc.contributor.author","Folprecht, Gunnar"],["dc.contributor.author","Sauer, R."],["dc.date.accessioned","2018-11-07T09:09:23Z"],["dc.date.available","2018-11-07T09:09:23Z"],["dc.date.issued","2012"],["dc.format.extent","38"],["dc.identifier.isi","000309231200073"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/26245"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Urban & Vogel"],["dc.publisher.place","Munich"],["dc.relation.conference","18th Annual Congress of the German-Society-for-Radiation-Oncology"],["dc.relation.eventlocation","Wiesbaden, GERMANY"],["dc.relation.issn","0179-7158"],["dc.title","Preoperative chemoradiotherapy and postoperative chemotherapy with 5-fluorouracil and oxaliplatin vs. 5-fluorouracil alone in locally advanced rectal cancer: First results of the German CAO/ARO/AIO-04 randomized phase III trial"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]