citations.bib

@article{ich2016,
  abstract = {Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening--based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%.},
  author = {D{\"u}rr, Oliver and Sick, Beate},
  date-modified = {2016-02-16 22:21:18 +0000},
  doi = {10.1177/1087057116631284},
  eprint = {http://jbx.sagepub.com/content/early/2016/02/11/1087057116631284.full.pdf+html},
  journal = {Journal of Biomolecular Screening},
  title = {Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks},
  url = {http://jbx.sagepub.com/content/early/2016/02/11/1087057116631284.abstract},
  year = {2016},
  bdsk-url-1 = {http://jbx.sagepub.com/content/early/2016/02/11/1087057116631284.abstract},
  bdsk-url-2 = {http://dx.doi.org/10.1177/1087057116631284}
}
@inproceedings{cieliebak2014meta,
  author = {Cieliebak, Mark and D{\"u}rr, Oliver and Uzdilli, Fatih},
  booktitle = {Language Resources and Evaluation Conference (LREC)},
  date-added = {2016-02-14 16:34:53 +0000},
  date-modified = {2016-02-14 16:34:53 +0000},
  pages = {3100--3104},
  title = {Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools.},
  year = {2014}
}
@article{durr2001melt,
  author = {Durr, O and Frisch, HL and Dieterich, W},
  date-added = {2016-02-12 13:30:18 +0000},
  date-modified = {2016-02-12 13:32:01 +0000},
  journal = {JOURNAL OF CHEMICAL PHYSICS},
  number = {19},
  pages = {9042-9045},
  title = {Melt viscosities of lattice polymers using a Kramers potential treatment},
  volume = {115},
  year = {2001}
}
@inproceedings{durr2001model,
  author = {Durr, O and Pendzig, P and Dieterich, W and Nitzan, A},
  booktitle = {Proceedings of the 1st International Discussion Meeting on Superionic Conductor Physics},
  date-added = {2016-02-12 13:29:57 +0000},
  date-modified = {2016-02-12 13:35:18 +0000},
  editor = {Kawamura, Junichi},
  journal = {arXiv preprint cond-mat/0106196},
  title = {Model studies of diffusion in glassy and polymer ion conductors},
  year = {2007}
}
@article{durr2007robust,
  author = {D{\"u}rr, Oliver and Duval, Fran{\c{c}}ois and Nichols, Anthony and Lang, Paul and Brodte, Annette and Heyse, Stephan and Besson, Dominique},
  journal = {Journal of biomolecular screening},
  number = {8},
  pages = {1042--1049},
  publisher = {SAGE Publications},
  title = {Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay},
  volume = {12},
  year = {2007}
}
@article{dieterich1999percolation,
  author = {Dieterich, W and D{\"u}rr, O and Pendzig, P and Bunde, A and Nitzan, A},
  journal = {Physica A: Statistical Mechanics and its Applications},
  number = {1},
  pages = {229--237},
  publisher = {Elsevier},
  title = {Percolation concepts in solid state ionics},
  volume = {266},
  year = {1999}
}
@article{durr2004coupled,
  author = {D{\"u}rr, O and Dieterich, W and Nitzan, A},
  journal = {The Journal of chemical physics},
  number = {24},
  pages = {12732--12739},
  publisher = {AIP Publishing},
  title = {Coupled ion and network dynamics in polymer electrolytes: Monte Carlo study of a lattice model},
  volume = {121},
  year = {2004}
}
@article{durr2002dynamic,
  author = {D{\"u}rr, O and Volz, T and Dieterich, W and Nitzan, A},
  journal = {The Journal of chemical physics},
  number = {1},
  pages = {441--447},
  publisher = {AIP Publishing},
  title = {Dynamic percolation theory for particle diffusion in a polymer network},
  volume = {117},
  year = {2002}
}
@article{durr2002effective,
  author = {D{\"u}rr, Oliver and Dieterich, Wolfgang and Maass, Philipp and Nitzan, Abraham},
  journal = {The Journal of Physical Chemistry B},
  number = {24},
  pages = {6149--6155},
  publisher = {ACS Publications},
  title = {Effective medium theory of conduction in stretched polymer electrolytes},
  volume = {106},
  year = {2002}
}
@article{durr2002diffusion,
  author = {D{\"u}rr, O and Dieterich, W and Nitzan, A},
  journal = {Solid state ionics},
  number = {1},
  pages = {125--130},
  publisher = {Elsevier},
  title = {Diffusion in polymer electrolytes and the dynamic percolation model},
  volume = {149},
  year = {2002}
}
@article{heyse2005quantifying,
  author = {Heyse, Stephan and Brodte, Annette and Bruttger, Oliver and Duerr, Oliver and Freeman, Tobe and Jung, Tom and Lindemann, Michael and Ottl, Johannes and Rinn, Bernd},
  journal = {Journal of the Association for Laboratory Automation},
  number = {4},
  pages = {207--212},
  publisher = {SAGE Publications},
  title = {Quantifying bioactivity on a large scale: quality assurance and analysis of multiparametric ultra-HTS data},
  volume = {10},
  year = {2005},
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}
@incollection{dieterich1999stochastic,
  author = {Dieterich, W and D{\"u}rr, O and Pendzig, P and Nitzan, A},
  booktitle = {Anomalous Diffusion From Basics to Applications},
  pages = {175--185},
  publisher = {Springer},
  title = {Stochastic modelling of ion diffusion in complex systems},
  year = {1999}
}
@mastersthesis{durr1998monte,
  author = {D{\"u}rr, Oliver},
  date-modified = {2016-02-14 16:40:04 +0000},
  school = {Universit{\"a}t Konstanze},
  title = {Monte-carlo-simulationen zu polymeren ionenleitern},
  year = {1998}
}
@inproceedings{durr2015deep,
  author = {D{\"u}rr, Oliver and Pauchard, Yves and Browarnik, Diego and Axthelm, Rebekka and Loeser, Martin},
  booktitle = {Eurographics (Posters)},
  pages = {11--12},
  title = {Deep Learning on a Raspberry Pi for Real Time Face Recognition.},
  year = {2015}
}
@article{durr2001charge,
  author = {D{\"u}rr, O and Nitzan, A and Dieterich, W},
  journal = {Comput. Syst. Sci.},
  number = {cond-mat/0106197},
  pages = {288--292},
  title = {Charge Transport in Polymer Ion Conductors},
  volume = {177},
  year = {2001}
}
@inproceedings{durr2007glassy,
  author = {D{\"u}rr, O and Dieterich, W},
  booktitle = {Superionic Conductor Physics},
  pages = {77--80},
  title = {Glassy and Polymeric Ionic Conductors:. Statistical Modeling and Monte Carlo Simulations},
  volume = {1},
  year = {2007}
}
@phdthesis{durr2003theoretical,
  author = {D{\"u}rr, Oliver},
  school = {Dissertation. de},
  title = {Theoretical Studies of Relaxation and Ionic Transport in Polymers},
  year = {2003}
}
@article{franzini2015gene,
  author = {Franzini, Anca and Baty, Florent and Macovei, Ina I and D{\"u}rr, Oliver and Droege, Cornelia and Betticher, Daniel and Grigoriu, Bogdan D and Klingbiel, Dirk and Zappa, Francesco and Brutsche, Martin H},
  journal = {Clinical Cancer Research},
  number = {23},
  pages = {5253--5263},
  publisher = {AACR},
  title = {Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced nonsquamous non--small cell lung cancer patients (SAKK 19/05 trial)},
  volume = {21},
  year = {2015}
}
@article{franzini2014tumor,
  author = {Franzini, Anca and D{\"u}rr, Oliver and Baty, Florent and Brutsche, Martin},
  journal = {European Respiratory Journal},
  number = {Suppl 58},
  pages = {P821},
  publisher = {Eur Respiratory Soc},
  title = {Tumor-associated stromal gene expression signatures predict therapeutic response to erlotinib/bevacizumab in non-small cell lung cancer (NSCLC)},
  volume = {44},
  year = {2014},
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}
@inproceedings{cieliebak2013potential,
  author = {Cieliebak, Mark and D{\"u}rr, Oliver and Uzdilli, Fatih},
  booktitle = {ESSEM@ AI* IA},
  organization = {Citeseer},
  pages = {47--58},
  title = {Potential and Limitations of Commercial Sentiment Detection Tools.},
  year = {2013}
}
@article{durr2014joint_forces,
  author = {D{\"u}rr, Oliver and Uzdilli, Fatih and Cieliebak, Mark},
  journal = {SemEval 2014-Proceedings of the 8th International Workshop on Semantic Evaluation},
  pages = {366--369},
  title = {JOINT\_FORCES: Unite Competing Sentiment Classifiers with Random Forest},
  year = {2014},
  bdsk-file-1 = {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}
}
@article{durr2012using,
  author = {D{\"u}rr, Oliver and Brandenburg, Arnd},
  journal = {arXiv preprint arXiv:1207.6282},
  title = {Using Community Structure for Complex Network Layout},
  year = {2012}
}

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