Krawczak, Michael

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[["dc.bibliographiccitation.firstpage","479"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Briefings in Bioinformatics"],["dc.bibliographiccitation.lastpage","487"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Bauer, Christian R."],["dc.contributor.author","Knecht, Carolin"],["dc.contributor.author","Fretter, Christoph"],["dc.contributor.author","Baum, Benjamin"],["dc.contributor.author","Jendrossek, Sandra"],["dc.contributor.author","Ruehlemann, Malte"],["dc.contributor.author","Heinsen, Femke-Anouska"],["dc.contributor.author","Umbach, Nadine"],["dc.contributor.author","Grimbacher, Bodo"],["dc.contributor.author","Franke, Andre"],["dc.contributor.author","Lieb, Wolfgang"],["dc.contributor.author","Krawczak, Michael"],["dc.contributor.author","Huett, Marc-Thorsten"],["dc.contributor.author","Sax, Ulrich"],["dc.date.accessioned","2018-11-07T10:24:26Z"],["dc.date.available","2018-11-07T10:24:26Z"],["dc.date.issued","2017"],["dc.description.abstract","Electronic access to multiple data types, from generic information on biological systems at different functional and cellular levels to high-throughputmolecular data from human patients, is a prerequisite of successful systems medicine research. However, scientists often encounter technical and conceptual difficulties that forestall the efficient and effective use of these resources. We summarize and discuss some of these obstacles, and suggest ways to avoid or evade them. The methodological gap between data capturing and data analysis is huge in human medical research. Primary data producers often do not fully apprehend the scientific value of their data, whereas data analysts maybe ignorant of the circumstances under which the data were collected. Therefore, the provision of easy-to-use data access tools not only helps to improve data quality on the part of the data producers but also is likely to foster an informed dialogue with the data analysts. We propose a means to integrate phenotypic data, questionnaire data and microbiome data with a user-friendly Systems Medicine toolbox embedded into i2b2/tranSMART. Our approach is exemplified by the integration of a basic outlier detection tool and a more advanced microbiome analysis (alpha diversity) script. Continuous discussion with clinicians, data managers, biostatisticians and systems medicine experts should serve to enrich even further the functionality of toolboxes like ours, being geared to be used by 'informed non-experts' but at the same time attuned to existing, more sophisticated analysis tools."],["dc.identifier.doi","10.1093/bib/bbw024"],["dc.identifier.isi","000400968000012"],["dc.identifier.pmid","27016392"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/42664"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1477-4054"],["dc.relation.issn","1467-5463"],["dc.title","Interdisciplinary approach towards a systems medicine toolbox using the example of inflammatory diseases"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1245"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Movement Disorders"],["dc.bibliographiccitation.lastpage","1248"],["dc.bibliographiccitation.volume","35"],["dc.contributor.author","Hopfner, Franziska"],["dc.contributor.author","Mueller, Stefanie H."],["dc.contributor.author","Szymczak, Silke"],["dc.contributor.author","Junge, Olaf"],["dc.contributor.author","Tittmann, Lukas"],["dc.contributor.author","May, Sandra"],["dc.contributor.author","Lohmann, Katja"],["dc.contributor.author","Grallert, Harald"],["dc.contributor.author","Lieb, Wolfgang"],["dc.contributor.author","Strauch, Konstantin"],["dc.contributor.author","Müller‐Nurasyid, Martina"],["dc.contributor.author","Berger, Klaus"],["dc.contributor.author","Schormair, Barbara"],["dc.contributor.author","Winkelmann, Juliane"],["dc.contributor.author","Mollenhauer, Brit"],["dc.contributor.author","Trenkwalder, Claudia"],["dc.contributor.author","Maetzler, Walter"],["dc.contributor.author","Berg, Daniela"],["dc.contributor.author","Kasten, Meike"],["dc.contributor.author","Klein, Christine"],["dc.contributor.author","Höglinger, Günter U."],["dc.contributor.author","Gasser, Thomas"],["dc.contributor.author","Deuschl, Günther"],["dc.contributor.author","Franke, André"],["dc.contributor.author","Krawczak, Michael"],["dc.contributor.author","Dempfle, Astrid"],["dc.contributor.author","Kuhlenbäumer, Gregor"],["dc.date.accessioned","2021-04-14T08:26:16Z"],["dc.date.available","2021-04-14T08:26:16Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1002/mds.28037"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81882"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1531-8257"],["dc.relation.issn","0885-3185"],["dc.title","Rare Variants in Specific Lysosomal Genes Are Associated With Parkinson's Disease"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1859"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","Genes"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Koch, Sebastian"],["dc.contributor.author","Laabs, Björn-Hergen"],["dc.contributor.author","Kasten, Meike"],["dc.contributor.author","Vollstedt, Eva-Juliane"],["dc.contributor.author","Becktepe, Jos"],["dc.contributor.author","Brüggemann, Norbert"],["dc.contributor.author","Franke, Andre"],["dc.contributor.author","Krämer, Ulrike M."],["dc.contributor.author","Kuhlenbäumer, Gregor"],["dc.contributor.author","Lieb, Wolfgang"],["dc.contributor.author","Caliebe, Amke"],["dc.contributor.author","Mollenhauer, Brit"],["dc.contributor.author","Neis, Miriam"],["dc.contributor.author","Trenkwalder, Claudia"],["dc.contributor.author","Schäffer, Eva"],["dc.contributor.author","Usnich, Tatiana"],["dc.contributor.author","Wittig, Michael"],["dc.contributor.author","Klein, Christine"],["dc.contributor.author","König, Inke R."],["dc.contributor.author","Lohmann, Katja"],["dc.contributor.author","Krawczak, Michael"],["dc.contributor.editor","Ebert, Allison D."],["dc.date.accessioned","2022-01-11T14:08:06Z"],["dc.date.available","2022-01-11T14:08:06Z"],["dc.date.issued","2021"],["dc.description.abstract","Idiopathic Parkinson’s disease (PD) is a complex multifactorial disorder caused by the interplay of both genetic and non-genetic risk factors. Polygenic risk scores (PRSs) are one way to aggregate the effects of a large number of genetic variants upon the risk for a disease like PD in a single quantity. However, reassessment of the performance of a given PRS in independent data sets is a precondition for establishing the PRS as a valid tool to this end. We studied a previously proposed PRS for PD in a separate genetic data set, comprising 1914 PD cases and 4464 controls, and were able to replicate its ability to differentiate between cases and controls. We also assessed theoretically the prognostic value of the PD-PRS, i.e., its ability to predict the development of PD in later life for healthy individuals. As it turned out, the PD-PRS alone can be expected to perform poorly in this regard. Therefore, we conclude that the PD-PRS could serve as an important research tool, but that meaningful PRS-based prognosis of PD at an individual level is not feasible."],["dc.description.abstract","Idiopathic Parkinson’s disease (PD) is a complex multifactorial disorder caused by the interplay of both genetic and non-genetic risk factors. Polygenic risk scores (PRSs) are one way to aggregate the effects of a large number of genetic variants upon the risk for a disease like PD in a single quantity. However, reassessment of the performance of a given PRS in independent data sets is a precondition for establishing the PRS as a valid tool to this end. We studied a previously proposed PRS for PD in a separate genetic data set, comprising 1914 PD cases and 4464 controls, and were able to replicate its ability to differentiate between cases and controls. We also assessed theoretically the prognostic value of the PD-PRS, i.e., its ability to predict the development of PD in later life for healthy individuals. As it turned out, the PD-PRS alone can be expected to perform poorly in this regard. Therefore, we conclude that the PD-PRS could serve as an important research tool, but that meaningful PRS-based prognosis of PD at an individual level is not feasible."],["dc.identifier.doi","10.3390/genes12121859"],["dc.identifier.pii","genes12121859"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97934"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-507"],["dc.publisher","MDPI"],["dc.relation.eissn","2073-4425"],["dc.rights","Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)."],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Validity and Prognostic Value of a Polygenic Risk Score for Parkinson’s Disease"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]