Department of Computer Science
 Rutgers University

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Ivan G Costa

Doctoral Student

Now assistant professor in CS, Universidade Federal de Pernambuco<br>

I obtained my M.Sc. and B.Sc. degrees in computer science at the Universidade Federal de Pernambuco, Brazil. I joined the Algorithmics group in 2004, and completed my 2008. My research interests are in the area of classification and clustering, as well as applications of these in transcriptomics and analysis of heterogeneous data.

Since January 2009 I am Professor Adjunto (Assistant professor) at the Center of Informatics, Federal University of Pernambuco in Brasil. My new homepage is

Upcoming/Recent presentations

July 21, 2008. Inferring Differentiation Pathways from Gene Expression.. Contributed Talk at International Conference of Intelligent Systems for Molecular Biology, Toronto, Canada.

Aug. 29, 2007. Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information. Contributed Talk at Brazilian Symposium on Bioinformatics

Sept. 18, 2006. On the Feasibility of Heterogeneous Analysis of Large Scale Biological Data. Contributed Talk at ECML Workshop on Data and Text Mining for Integrative Biology

Aug. 8, 2006. Gene Expression Trees in Blood Cell Development. Contributed Talk at Plos Track of the International Conference on Intelligent Systems for Molecular Biology

Jan. 13, 2006. Clustering of Gene Expression Time-courses: Methods and Validity of Solutions. Invited Talk at Bioinformatics Working Seminar of the Max Planck Institute of Molecular Plant Physiology

Recent publications

T. Marshall, I. Costa, S. Canzar, M. Bauer, G. Klau, A. Schliep and A. Schönhuth CLEVER: Clique-Enumerating Variant Finder. Bioinformatics 2012. Accepted for Publication..

T. Marshall, I. Costa, S. Canzar, M. Bauer, G. Klau, A. Schliep and A. Schönhuth CLEVER: Clique-Enumerating Variant Finder. 2012. Arxiv.

C. Hafemeister, I.G. Costa, A. Schönhuth and A. Schliep Classifying short gene expression time-courses with Bayesian estimation of piecewise constant functions. Bioinformatics 2011, 27:7, 946–52.

R.B. Schilling, I.G. Costa and A. Schliep pGQL: A Probabilistic Graphical Query Language for Gene Expression Time Courses. BioData Mining 2011, 4:9.

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.

Project lead

DrosophilaDevelopment: Gene regulation during early Drosophila development.

MASCAAT: Meta-Learning for Selection and Combination of Clustering Algorithms Applied to Gene Expression Analysis.

CellDiff: Understanding transcriptional regulation in cell differentiation.

Software lead

GQL: Graphical Query Language.