Department of Computer Science
 Rutgers University

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Benjamin Georgi

Doctoral Student

Postdoctoral fellow with Maja Bucan at the University of Pennsylvania.

Benjamin Georgi reveived his M. Sc. in Bioinformatics in 2005 at the Freie Universit├Ąt of Berlin. From 2005-July 2009 he was a doctoral student in the algorithmics group of the MPI for Molecular Genetics. His dissertation work was concerned with cluster analysis of heterogeneous biological data using context-specific independence mixture models.

Since October 2009 he has moved on to the Genetics department of the University of Pennsylvania.

Upcoming/Recent presentations

Sept. 22, 2008. Prediction of functional residues and clustering for protein families using mixtures. Poster at European Conference in Computational Biology (ECCB) 2008

Sept. 18, 2007. Context-specific Independence mixture Modelling for Protein Families. Contributed Talk at <A HREF="">European Conference on Machine Learning (ECML)</A>,Warsaw, Poland

Sept. 17, 2007. Partially-supervised context-specific independence mixture modeling. Contributed Talk at workshop on <A HREF="">Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions</A> on the ECML 2007, Warsaw, Poland

March 9, 2007. Mixture model based group inference in fused genotype and phenotype data. Contributed Talk at <A HREF="">31st Annual Conference of the German Classification Society on Data Mining, Machine Learning and Data Analysis</A>, Freiburg, Germany

Aug. 8, 2006. Context-specific independence mixture modeling for positional weight matrices. Contributed Talk at <A HREF="">Intelligent Systems in Molecular Biology (ISMB)</A> , Fortaleza, Brazil

Recent publications

B. Georgi, I. Gesteira Costa and I. Schliep PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data. BMC Bioinformatics 2010, 11:9.

B. Georgi Context-specific Independence Mixture Models for Cluster Analysis of Biological Data. Ph.D. Thesis, Freie Universit├Ąt Berlin, Jun 2009.

B. Georgi, J. Schultz and A. Schliep Partially-supervised protein subclass discovery with simultaneous annotation of functional residues. BMC Struct Biol. 2009, 9:68.

B. Georgi and A. Schliep Partially-supervised context-specific independence mixture modeling. In workshop on Data Mining in Functional Genomics and Proteomics, ECML 2007, 2007.

S. Haesler, C. Rochefort, P. Licznerski, B. Georgi, P. Osten and C. Scharff Incomplete and inaccurate vocal imitation after knockdown of FoxP2 in songbird basal ganglia nucleus Area X. PloS Biology 2007, 5:12, e321.

Project lead

ComplexDiseases: Analysis of complex disease data.

CSIMixtures: Context-specific independence mixture modeling for sequence motifs.

Software lead

PyMix: The Python mixture package.