Baum, Benjamin

[["dc.contributor.author","Knopp, Cornelius"],["dc.contributor.author","Bauer, Christian R. K. D."],["dc.contributor.author","Baum, Benjamin"],["dc.contributor.author","Löhnhardt, Benjamin"],["dc.contributor.author","Nietert, Manuel Manfred"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Sax, Ulrich"],["dc.date.accessioned","2020-03-27T11:22:14Z"],["dc.date.available","2020-03-27T11:22:14Z"],["dc.date.issued","2016"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63384"],["dc.notes.preprint","yes"],["dc.relation.conference","Conference: HEC 2016 - Health-Exploring Complexity: An Interdisciplinairy Systems Approach"],["dc.relation.eventlocation","München"],["dc.relation.eventstart","2016-08"],["dc.relation.iserratumof","yes"],["dc.title","A validatable data management solution for multi-center research consortia: research data management with openBIS"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["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.artnumber","S6"],["dc.bibliographiccitation.issue","Suppl 1"],["dc.bibliographiccitation.journal","Journal of Clinical Bioinformatics"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Bauer, Christian"],["dc.contributor.author","Ganslandt, Thomas"],["dc.contributor.author","Baum, Benjamin"],["dc.contributor.author","Christoph, Jan"],["dc.contributor.author","Engel, Igor"],["dc.contributor.author","Löbe, Matthias"],["dc.contributor.author","Mate, Sebastian"],["dc.contributor.author","Prokosch, Hans-Ulrich"],["dc.contributor.author","Sax, Ulrich"],["dc.contributor.author","Stäubert, Sebastian"],["dc.contributor.author","Winter, Alfred"],["dc.date.accessioned","2016-03-17T17:03:59Z"],["dc.date.accessioned","2021-10-27T13:20:27Z"],["dc.date.available","2016-03-17T17:03:59Z"],["dc.date.available","2021-10-27T13:20:27Z"],["dc.date.issued","2015"],["dc.date.updated","2016-03-17T17:03:59Z"],["dc.identifier.doi","10.1186/2043-9113-5-S1-S6"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/13128"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/91967"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","CC BY 4.0"],["dc.rights.holder","Bauer et al; licensee BioMed Central Ltd."],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","The Integrated Data Repository Toolkit (IDRT): accelerating translational research infrastructures"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Information Technology"],["dc.bibliographiccitation.volume","59"],["dc.contributor.author","Baum, Benjamin"],["dc.contributor.author","Bauer, Christian R."],["dc.contributor.author","Franke, Thomas"],["dc.contributor.author","Kusch, Harald"],["dc.contributor.author","Parciak, Marcel"],["dc.contributor.author","Rottmann, Thorsten"],["dc.contributor.author","Umbach, Nadine"],["dc.contributor.author","Sax, Ulrich"],["dc.date.accessioned","2018-04-24T15:08:22Z"],["dc.date.available","2018-04-24T15:08:22Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1515/itit-2016-0031"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/13765"],["dc.identifier.url","https://sfb1002.med.uni-goettingen.de/production/literature/publications/176"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.relation","SFB 1002: Modulatorische Einheiten bei Herzinsuffizienz"],["dc.relation","SFB 1002 | INF: Unterstützung der SFB 1002 Forschungsdatenintegration, -visualisierung und -nachnutzung"],["dc.relation.workinggroup","RG Nußbeck"],["dc.title","Opinion paper: Data provenance challenges in biomedical research"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","overview_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","125"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Methods of Information in Medicine"],["dc.bibliographiccitation.lastpage","135"],["dc.bibliographiccitation.volume","55"],["dc.contributor.author","Bauer, C. R. K. D."],["dc.contributor.author","Ganslandt, T."],["dc.contributor.author","Baum, B."],["dc.contributor.author","Christoph, J."],["dc.contributor.author","Engel, I."],["dc.contributor.author","Löbe, M."],["dc.contributor.author","Mate, S."],["dc.contributor.author","Stäubert, S."],["dc.contributor.author","Drepper, J."],["dc.contributor.author","Prokosch, H.-U."],["dc.contributor.author","Winter, Aurelia"],["dc.contributor.author","Sax, Ulrich"],["dc.date.accessioned","2020-12-10T18:47:27Z"],["dc.date.available","2020-12-10T18:47:27Z"],["dc.date.issued","2016"],["dc.description.abstract","Background: In recent years, research data warehouses moved increasingly into the focus of interest of medical research. Nevertheless, there are only a few center-independent infrastructure solutions available. They aim to provide a consolidated view on medical data from various sources such as clinical trials, electronic health records, epidemiological registries or longitudinal cohorts. The i2b2 framework is a well-established solution for such repositories, but it lacks support for importing and integrating clinical data and metadata. Objectives: The goal of this project was to develop a platform for easy integration and administration of data from heterogeneous sources, to provide capabilities for linking them to medical terminologies and to allow for transforming and mapping of data streams for user-specific views. Methods: A suite of three tools has been developed: the i2b2 Wizard for simplifying administration of i2b2, the IDRT Import and Mapping Tool for loading clinical data from various formats like CSV, SQL, CDISC ODM or biobanks and the IDRT i2b2 Web Client Plugin for advanced export options. The Import and Mapping Tool also includes an ontology editor for rearranging and mapping patient data and structures as well as annotating clinical data with medical terminologies, primarily those used in Germany (ICD-10-GM, OPS, ICD-O, etc.). Results: With the three tools functional, new i2b2-based research projects can be created, populated and customized to researcher's needs in a few hours. Amalgamating data and metadata from different databases can be managed easily. With regards to data privacy a pseudonymization service can be plugged in. Using common ontologies and reference terminologies rather than project specific ones leads to a consistent understanding of the data semantics. Conclusions: i2b2's promise is to enable clinical researchers to devise and test new hypothesis even without a deep knowledge in statistical programing. The approach presented here has been tested in a number of scenarios with millions of observations and tens of thousands of patients. Initially mostly observant, trained researchers were able to construct new analyses on their own. Early feedback indicates that timely and extensive access to their \"own\" data is appreciated most, but it is also lowering the barrier for other tasks, for instance checking data quality and completeness (missing data, wrong coding)."],["dc.identifier.doi","10.3414/ME15-01-0082"],["dc.identifier.eissn","2511-705X"],["dc.identifier.isi","000372945200003"],["dc.identifier.issn","0026-1270"],["dc.identifier.pmid","26534843"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78767"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","0026-1270"],["dc.title","Integrated Data Repository Toolkit (IDRT)"],["dc.title.subtitle","A Suite of Programs to Facilitate Health Analytics on Heterogeneous Medical Data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]