Research Topics
| F MarkowetzSummaryAffiliation: Max Planck Institute for Molecular Genetics Country: Germany Publications
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Detail Information
Publications
Molecular diagnosis. Classification, model selection and performance evaluationF Markowetz
Max Planck Institute for Molecular Genetics, Computational Diagnostics Group, Ihnestrasse 63 73, 14195 Berlin, Germany
Methods Inf Med 44:438-43. 2005..We discuss supervised classification techniques applied to medical diagnosis based on gene expression profiles. Our focus lies on strategies of adaptive model selection to avoid overfitting in high-dimensional spaces...
Non-transcriptional pathway features reconstructed from secondary effects of RNA interferenceFlorian Markowetz
Department of Computational Molecular Biology, Computational Diagnostics Group, Max Planck Institute for Molecular Genetics Ihnestrasse 63 73, 14195 Berlin, Germany
Bioinformatics 21:4026-32. 2005....
Inferring cellular networks--a reviewFlorian Markowetz
Max Planck Institute for Molecular Genetics, Ihnestrasse 63 73, 14195 Berlin, Germany
BMC Bioinformatics 8:S5. 2007..The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations...
Nested effects models for high-dimensional phenotyping screensFlorian Markowetz
Lewis Sigler Institute for Integrative Genomics and Department of Computer Science, Princeton University, Princeton, NJ, 08544, USA
Bioinformatics 23:i305-12. 2007....
Structure learning in Nested Effects ModelsAchim Tresch
Johannes Gutenberg University Mainz
Stat Appl Genet Mol Biol 7:Article9. 2008..Third, we show that the new formulation of the likelihood allows efficiency in traversing model space. Fourth, we incorporate prior knowledge and an automated variable selection criterion to decrease the influence of noise in the data...
Computational diagnostics with gene expression profilesClaudio Lottaz
Max Planck Institute for Molecular Genetics and Berlin Center for Genome Based Bioinformatics, Berlin, Germany
Methods Mol Biol 453:281-96. 2008..In this process, they encounter a series of obstacles and pitfalls. This chapter reviews fundamental issues from machine learning and recommends a procedure for the computational aspects of a clinical micro-array study...
Computational identification of cellular networks and pathwaysFlorian Markowetz
Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
Mol Biosyst 3:478-82. 2007....
