K
Knut Baumann
Researcher at Braunschweig University of Technology
Publications - 101
Citations - 3353
Knut Baumann is an academic researcher from Braunschweig University of Technology. The author has contributed to research in topics: Cross-validation & Feature selection. The author has an hindex of 33, co-authored 99 publications receiving 2944 citations. Previous affiliations of Knut Baumann include University of Jena & University of Bern.
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Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.
TL;DR: Refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data that provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods.
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Cross-validation as the objective function for variable-selection techniques
TL;DR: It is shown that the commonly applied leave-one-out cross-validation has a strong tendency to overfitting, underestimates the true prediction error, and should not be used without further constraints or further validation.
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Towards a detailed understanding of bacterial metabolism--spectroscopic characterization of Staphylococcus epidermidis.
Ute Neugebauer,Ulrike Schmid,Knut Baumann,Wilma Ziebuhr,Svetlana Kozitskaya,Volker Deckert,Michael Schmitt,Jürgen Popp +7 more
TL;DR: In this paper, various vibrational spectroscopic techniques are applied to comprehensively characterize, on a molecular level, bacteria of the strain Staphylococcus epidermidis, an opportunistic pathogen which has evolved to become a major cause of nosocomial infections.
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Reliable estimation of prediction errors for QSAR models under model uncertainty using double cross-validation
Désirée Baumann,Knut Baumann +1 more
TL;DR: The cross-validation design in the inner loop and the influence of the test set size in the outer loop is systematically studied for regression models in combination with variable selection.
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Evaluation of arene ruthenium(II) N-heterocyclic carbene complexes as organometallics interacting with thiol and selenol containing biomolecules
Luciano Oehninger,Maria Stefanopoulou,Hamed Alborzinia,Julia Schur,Stephanie Ludewig,Kazuhiko Namikawa,Alvaro Muñoz-Castro,Reinhard W. Köster,Knut Baumann,Stefan Wölfl,William S. Sheldrick,Ingo Ott +11 more
TL;DR: Ruthenium complexes of the type (p-cymene)(NHC)RuCl(2) interacted with biologically relevant thiols and selenols, which resulted in the inhibition of enzymes such as thioredoxin reductase or cathepsin B andounced antiproliferative effects could be obtained provided that an appropriate cellular uptake was achieved.