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Thomas Lengauer
Researcher at Max Planck Society
Publications - 477
Citations - 37847
Thomas Lengauer is an academic researcher from Max Planck Society. The author has contributed to research in topics: DNA methylation & Gene. The author has an hindex of 80, co-authored 477 publications receiving 34430 citations. Previous affiliations of Thomas Lengauer include Stanford University & Bell Labs.
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ROCR: visualizing classifier performance in R
TL;DR: UNLABELLED ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R that features over 25 performance measures that can be freely combined to create two-dimensional performance curves.
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A Fast Flexible Docking Method using an Incremental Construction Algorithm
TL;DR: This work presents an automatic method for docking organic ligands into protein binding sites that combines an appropriate model of the physico-chemical properties of the docked molecules with efficient methods for sampling the conformational space of the ligand.
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A genome-wide association scan of nonsynonymous SNPs identifies a susceptibility variant for Crohn disease in ATG16L1
Jochen Hampe,Andre Franke,Philip Rosenstiel,Philip Rosenstiel,Andreas Till,Markus Teuber,Klaus Huse,Mario Albrecht,Gabriele Mayr,Francisco M. De La Vega,Jason C Briggs,Simone Günther,Natalie J. Prescott,Clive M. Onnie,Robert Häsler,Bence Sipos,Ulrich R. Fölsch,Thomas Lengauer,Matthias Platzer,Christopher G. Mathew,Michael Krawczak,Stefan Schreiber +21 more
TL;DR: Data suggest that the underlying biological process may be specific to Crohn disease, and that marker rs2241880, a coding SNP (T300A), carries virtually all the disease risk exerted by the ATG16L1 locus.
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Improved scoring of functional groups from gene expression data by decorrelating GO graph structure
TL;DR: Two novel algorithms that improve GO group scoring using the underlying GO graph topology are presented and it is shown that both methods eliminate local dependencies between GO terms and point to relevant areas in the GO graph that remain undetected with state-of-the-art algorithms for scoring functional terms.
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Computing topological parameters of biological networks
TL;DR: The versatile Cytoscape plugin NetworkAnalyzer computes and displays a comprehensive set of topological parameters, which includes the number of nodes, edges, and connected components, the network diameter, radius, density, centralization, heterogeneity, and clustering coefficient, and the characteristic path length.