Ivan Gesteira Costa Filho

Publications:

Redestig, H., Costa, I. G. Detection and interpretation of metabolite-transcript co-responses using combined profiling data. Bioinformatics, 2011. [paper]. [Supp]
Hafemeister, C., Costa, I. G., Schonhuth, A., Schliep, A. Classifying short gene expression time-courses with Bayesian estimation of piecewise constant functions. Bioinformatics, 2011. [paper]. [Supp]
Lorena, A. C., Costa , I. G., SPOLOIR, N., de Souto, M. C. P. Analysis of Complexity Indices for Classification Problems: Cancer Gene Expression Data. Neurocomputing, 2011.
Costa, I.G., Roider, H, do Rego, T. G., de Carvalho, F. A. T Predicting Gene Expression in T cell Differentiation from Histone Modifications and Transcription Factor Binding Affinities by Linear Mixture Models BMC Bioinformatics. , v.12, p.S29, 2011. [paper]. [Supp]

B. Georgi, I. G. Costa and A. Schliep PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data BMC Bioinformatics v.11, p.9, 2010, 11:9 [paper]. [Supp]
de Souto, M. C. P., Lorena, A. C., Spoloir, N., Costa , I. G. Complexity measures of supervised classifications tasks: A case study for cancer gene expression data , In: International Joint Conference on Neural Networks (IJCNN), 2010, Barcelona. Proceedings of the International Joint Conference on Neural Networks (IJCNN). Los Alamitos: IEEE, 2010. p.1-7.
Lorena, A. C., Spoloir, N., Costa , I. G., de Souto, M. C. P. On the Complexity of Gene Marker Selection ,. In: Brazilian Symposium on Neural Networks, 2010, Sao Paulo, Proc. of the Brazilian Symposium on Neural Networks. Los Alamitos, EUA: IEEE, 2010.
RIBEIRO, C., Costa , I. G., de Carvalho, F. A. T Semi-supervised Approach for Finding Cancer Sub-Classes on Gene Expression Data, In: Brazilian Symposium on Bioinformatics, 2010, Buzios. Advances in Computational Biology, Lecture Notes in Bioinformatics. Berlin: Springer Verlag, 2010. v.6268. p.24 - 34

I. G. Costa, A. Schoenhut, C. Hafemeister, and A. Schliep, Constrained Mixture Estimation for Analysis and Robust Classification of Clinical Time Series. Bioinformatics, v. 25, p. i6-i14, 2009. [paper]. [Supp]
I. G. Costa, A. C. Lorena, L. R. M. P. y Peres, M. C. P de Souto , Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data sets. In: Brazilian Symposin on Bionformatics, 2009, Porto Alegre. Lecture Notes on Bionformatics. Berlin : Springer Verlag, 2009 (Best Paper Award).
A.C.A. Nascimento, R.B.C. Prudencio, M.C.P. de Souto, I. G. Costa, Mining rules for selection of clustering methods for cancer gene expression. In: International Conference on Artificial Neural Networks, 2009, Limassol, Cyprus. Proc. of the International Conference on Artificial Neural Networks. Berlin : Springer-Verlag, 2009.

M. C. P. de Souto, I. G. Costa , D. A. S Araujo, T. B. Ludermir, and A. Schliep Clustering cancer gene expression data: a comparative study. BMC Bioinformatics, 9:497, 2008 [paper].
I. G. Costa, S. Roepcke, C. Hafemeister, and A. Schliep, Inferring Differentiation Pathways from Gene Expression. Bioinformatics, v 24, p. i156-i164, 2008, [pdf], [supplement].
de Souto, M. C. P. ; Costa , I. G. ; Lorena, A. C. On the complexity of gene expression classification data sets. In: Eighth International Conference on Hybrid Intelligent Systems, 2008, Barcelona. Eighth International Conference on Hybrid Intelligent Systems. Los Alamitos : IEEE, 2008.
M. C. P. de Souto, D. A. S. Araujo, I. G. Costa , R. G. F. Soares, T. B. Ludermir, and A. Schliep Comparative Study on Normalization Procedures for Cluster Analysis of Gene Expression Datasets. Proceedings of the International Joint Conference on Neural Networks, IEEE Computer Society, pages, 3728-3734, 2008 [pre-print].
M. C. P. de Souto, R. B. C. Prudencio, R. G. F. Soares, D. A. S. Araujo, I. G. Costa , T. B. Ludermir, and A. Schliep Ranking and Selecting Clustering Algorithms Using a Meta-learning Approach. Proceedings of the International Joint Conference on Neural Networks, IEEE Computer Society, 2008 [pre-print].

Costa , I. G. ; Roepcke, S ; Schliep, A. . Gene Expression Trees in Lymphoid Development . BMC Immunology, v. 8, p. 25, 2007, [pdf], [supplement].
I. G. Costa, R. Krause, L. Optiz, and A. Schliep Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data. BMC Bioinformatics 2007, Vol. 8, Pages S3. [pdf], [supplement].
I. G. Costa, M. C. P. de Souto, and A. Schliep Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information. Advances in Bioinformatics and Computational Biology, Proceedings of the Brazilian Symposium on Bioinformatics, Pages 81-92, Springer Verlag, 2007 [pre-print].

I. G. Costa and A. Schliep On the Feasibility of Heterogeneous Analysis of Large Scale Biological Data Proceedings of ECML/PKDD 2006 Workshop on Data and Text Mining for Integrative Biology, ac55-60. [preprint]
A. A. Schönhuth., I. G. Costa and A. Schliep Semi-supervised Clustering of Yeast Gene Expression Data Japanese-German Workshop on data analysis. and classification 2006, Springer, accepted, [pre-print].

A. Schliep, I. G. Costa, C. Steinhoff, A. A. Schönhuth. Analyzing Gene Expression Time-Courses IEEE/ACM Transactions on Computational Biology and Bioinformatics ( Special Issue on Machine Learning for Bioinformatics), 2005, 2(3):179-193. [pdf] [preprint] [supplement]
I. G. Costa and A. Schliep On external indices for mixtures: validating mixtures of genes In From Data and Information Analysis to Knowledge Engineering, M. Spiliopoulou R. Kruse, C. Borgelt, A. Nurnberger, W. Gaul (Eds.), Springer 2005, 662-669 (Proceedings of the GfKl 2005 conference).
I. G. Costa, A. Schönhuth, A. Schliep. The Graphical Query Language: a tool for analysis of gene expression time-courses , Bioinformatics, 2005, 21(10):2544-2545. [pdf]

I. G. Costa, F. A. T. de Carvalho, M. C. P. de Souto, Comparative Analysis of Clustering Methods for Gene Expression Time Course Data, Genetics and Molecular Biology, 2004, 27, 4:623-631. [pdf]

I. G. Costa, F. A. T. De Carvalho, M. C. P. de Souto Comparative Study on Proximity Indices for Cluster Analysis of Gene Expression Time Series. Journal of Intelligent and Fuzzy Systems, 13(2-4), 133-142, 2003.

Costa, I. G., M. C. P. de Souto, F. A. T. De Carvalho,. A Symbolic Approach to Gene Expression Time Series Analysis In: VII Brazilian Symposium on Neural Networks, 2002, Recife. VII Brazilian Symposium on Neural Networks. Los Alamitos: IEEE Computer Society Press, 2002, 1,24-30.
I. G. Costa, F. A. T. de Carvalho, M.C.P. de Souto Stability Evaluation of Clustering Algorithms for Time Series Gene Expression Data In: I Brazilian Workshop on Bioinformatics, 2002, 88-90.