publist_brandt.bib

@inproceedings{Bessani2015,
  title = {BiobankCloud: a Platform for the Secure Storage, Sharing, and Processing of Large Biomedical Data Sets},
  author = {Alysson Bessani and J\"orgen Brandt and Marc Bux and Vinicius Cogo and Lora Dimitrova and Jim Dowling and Ali Gholami and Kamal Hakimzadeh and Michael Hummel and Mahmoud Ismail and Erwin Laure and Ulf Leser and Jan-Eric Litton and Roxanna Martinez and Salman Niazi and Jane Reichel and Karin Zimmermann},
  booktitle = {The First International Workshop on Data Management and Analytics for Medicine and Healthcare (DMAH 2015)},
  year = {2015},
  month = {September},
  owner = {jorgen},
  timestamp = {2015.08.28},
  url = {http://homepages.lasige.di.fc.ul.pt/~vielmo/publications/2015_biobankcloud-platform.pdf}
}
@inproceedings{Brandt2013,
  title = {AgED: Extraction and Evaluation of Elliptic Fourier Descriptors from Image Data in Phenotype Assessment Applications},
  author = {Brandt, J\"orgen and Heyl, Alexander},
  booktitle = {International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2013)},
  year = {2013},
  abstract = {In biological experiments, phenotype evaluation is a common challenge. In a wide variety of applications, the phenotypic features of organisms have to be measured and statistically assessed. This is especially important as differences between wild-type and mutant or treated and untreated organisms are often very subtle. Here, we propose a set of digital image transformations that implement preprocessing, feature extraction and statistical analysis of image data that is typically generated in a biological experiment. Moreover we present AgED - Analysis given Experimental Data, a software toolkit that facilitates the process of phenotypic feature evaluation from digital image data in an automatized fashion. Suitable statistical analysis and visualization is performed and controlled via a Graphical User Interface. Furthermore, the use of open data structures allows for the convenient reuse of the acquired feature data with miscellaneous data-mining software and scientific workflow systems. The functionality of this software tool is demonstrated and validated by repeating a phytohormone response experiment carried out on the fresh water alga Coleochaete scutata. The results showed that the timely and automatic processing of digital image data aides the researcher and rationalizes the formerly lengthy and, at times, error prone data evaluation in spreadsheet documents. Furthermore, the software toolkit AgED establishes a comparable evaluation standard and provides ready-to-publish graphic export facilities.},
  doi = {10.5220/0004249903240327},
  owner = {jorgen},
  timestamp = {2015.06.15}
}
@inproceedings{Brandt2015,
  title = {Cuneiform: A Functional Language for Large Scale Scientific Data Analysis},
  author = {Brandt, J{\"o}rgen and Bux, Marc and Leser, Ulf},
  booktitle = {Proceedings of the Workshops of the EDBT/ICDT},
  year = {2015},
  address = {Brussels, Belgium},
  month = {March},
  pages = {17--26},
  volume = {1330},
  abstract = {The need to analyze massive scientific data sets on the one hand and the availability of distributed compute resources with an increasing number of CPU cores on the other hand have promoted the development of a variety of languages and systems for parallel, distributed data analysis. Among them are data-parallel query languages such as Pig Latin or Spark as well as scientific workflow languages such as Swift or Pegasus DAX. While data-parallel query languages focus on the exploitation of data parallelism, scientific workflow languages focus on the integration of external tools and libraries. However, a language that combines easy integration of arbitrary tools, treated as black boxes, with the ability to fully exploit data parallelism does not exist yet. Here, we present Cuneiform, a novel language for large-scale scientific data analysis. We highlight its functionality with respect to a set of desirable features for such languages, introduce its syntax and semantics by example, and show its flexibility and conciseness with use cases, including a complex real-life workflow from the area of genome research. Cuneiform scripts are executed dynamically on the workflow execution platform Hi-WAY which is based on Hadoop YARN. The language Cuneiform, including tool support for programming, workflow visualization, debugging, logging, and provenance-tracing, and the parallel execution engine Hi-WAY are fully implemented.},
  url = {http://ceur-ws.org/Vol-1330/paper-03.pdf}
}
@inproceedings{Bux2015,
  title = {SAASFEE: Scalable Scientific Workflow Execution Engine},
  author = {Bux, Marc and Brandt, J\"{o}rgen and Lipka, Carsten and Hakimzadeh, Kamal and Dowling, Jim and Leser, Ulf},
  booktitle = {VLDB Demonstrations Track, forthcoming},
  year = {2015},
  address = {Hawaii, USA},
  month = {September},
  url = {https://www2.informatik.hu-berlin.de/~buxmarcn/publications/bux_saasfee_vldb_2015.pdf}
}
@inproceedings{Filter2013,
  title = {A community resource for integrated predictive microbial modelling (PMM-Lab)},
  author = {Filter, Matthias and Th{\"o}ns, Christian and Brandt, J{\"o}rgen and Weiser, Armin A and Falenski, Alexander and Appel, Bernd and K{\"a}sbohrer, Annemarie},
  booktitle = {5th International Workshop Cold Chain Management, Bonn, Germany},
  year = {2013},
  url = {http://ccm.ytally.com/fileadmin/user_upload/downloads/publications_5th_workshop/Filter_paper.pdf}
}
@article{Vossenkuhl2014a,
  title = {Comparison of spa Types, SCCmec types and antimicrobial resistance profiles of MRSA isolated from turkeys at farm, Slaughter and from Retail Meat Indicates Transmission along the Production Chain},
  author = {Vossenkuhl, Birgit and Brandt, J{\"o}rgen and Fetsch, Alexandra and K{\"a}sbohrer, Annemarie and Kraushaar, Britta and Alt, Katja and Tenhagen, Bernd-Alois},
  journal = {PloS one},
  year = {2014},
  number = {5},
  volume = {9},
  publisher = {Public Library of Science},
  url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0096308}
}
@article{Vossenkuhl2014b,
  title = {Modeling the transmission of livestock associated methicillin-resistant Staphylococcus aureus along the pig slaughter line},
  author = {Vossenkuhl, Birgit and Sharp, Hannah and Brandt, J{\"o}rgen and Fetsch, Alexandra and K{\"a}sbohrer, Annemarie and Tenhagen, Bernd-Alois},
  journal = {Food Control},
  year = {2014},
  pages = {17--24},
  volume = {39},
  publisher = {Elsevier},
  url = {http://www.sciencedirect.com/science/article/pii/S0956713513005550}
}
@incollection{Weiser2012,
  title = {An open-source community resource for creating, collecting, sharing and applying predictive microbial models (PMM-lab)},
  author = {Weiser, Armin A and Filter, Matthias and Falenski, Alexander and Brandt, J{\"o}rgen and K{\"a}sbohrer, Annemarie and Appel, Bernd},
  booktitle = {Future Security},
  publisher = {Springer},
  year = {2012},
  pages = {462--465},
  url = {http://link.springer.com/chapter/10.1007/978-3-642-33161-9_65}
}

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