Mathäus Dejori

According to our database, Mathäus Dejori authored at least 14 papers between 2003 and 2011.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2011

A Meta-Data Approach to Querying Multiple Biomedical Ontologies.

Ravi Palla, Dan Tecuci, Vinay D. Shet, Mathäus Dejori

Proceedings of the 2nd International Conference on Biomedical Ontology, 2011

2010

Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction.

Lance E. Palmer, Mathäus Dejori, Randall A. Bolanos, Daniel P. Fasulo

BMC Bioinform., 2010

2009

Using a Local Discovery Ant Algorithm for Bayesian Network Structure Learning.

Pedro C. Pinto, Andreas Nägele, Mathäus Dejori, Thomas A. Runkler, João Miguel da Costa Sousa

IEEE Trans. Evol. Comput., 2009

Hierarchical Bayesian Models for Collaborative Tagging Systems.

Markus Bundschus, Shipeng Yu, Volker Tresp, Achim Rettinger, Mathäus Dejori, Hans-Peter Kriegel

Proceedings of the ICDM 2009, 2009

2008

Extraction of semantic biomedical relations from text using conditional random fields.

Markus Bundschus, Mathäus Dejori, Martin Stetter, Volker Tresp, Hans-Peter Kriegel

BMC Bioinform., 2008

Anticipating annotations and emerging trends in biomedical literature.

Fabian Mörchen, Mathäus Dejori, Dmitriy Fradkin, Julien Etienne, Bernd Wachmann, Markus Bundschus

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Learning of Bayesian networks by a local discovery ant colony algorithm.

Pedro C. Pinto, Andreas Nägele, Mathäus Dejori, Thomas A. Runkler, João Miguel da Costa Sousa

Proceedings of the IEEE Congress on Evolutionary Computation, 2008

Emerging Trend Prediction in Biomedical Literature.

Fabian Mörchen, Dmitriy Fradkin, Mathäus Dejori, Bernd Wachmann

Proceedings of the AMIA 2008, 2008

2007

Structure Learning with Nonparametric Decomposable Models.

Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter

Proceedings of the Artificial Neural Networks, 2007

Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures.

Andreas Nägele, Mathäus Dejori, Martin Stetter

Proceedings of the Machine Learning: ECML 2007, 2007

2004

Systems Level Modeling of Gene Regulatory Networks.

Martin Stetter, Bernd Schürmann, Mathäus Dejori

Proceedings of the Artificial Intelligence Methods And Tools For Systems Biology, 2004

Identifying Interventional and Pathogenic Mechanisms by Generative Inverse Modeling of Gene Expression Profiles.

Mathäus Dejori, Martin Stetter

J. Comput. Biol., 2004

2003

Large-Scale Computational Modeling of Genetic Regulatory Networks.

Martin Stetter, Gustavo Deco, Mathäus Dejori

Artif. Intell. Rev., 2003

Bayesian Inference of Genetic Networks from Gene-Expression-Data: Convergence and Reliability.

Mathäus Dejori, Martin Stetter

Proceedings of the International Conference on Artificial Intelligence, 2003