The UK MARIBS Breast Screening Study: Evaluation of radiological features for breast tumour classification in clinical screening with machine learning methods. - Tim W. Nattkemper; Bert Arnrich; Oliver Lichte; Wiebke Timm; Andreas Degenhard; Linda Pointon; Carmel Hayes; Martin O. Leach (Artif. Intell. Medicine, 2005)

Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. - Alexandra Scherbart; Wiebke Timm; Sebastian Böcker; Tim W. Nattkemper (ICANN (2), 2007)

Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. - Alexandra Scherbart; Wiebke Timm; Sebastian Böcker; Tim W. Nattkemper (ICONIP (1), 2008)

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. - Wiebke Timm; Alexandra Scherbart; Sebastian Böcker; Oliver Kohlbacher; Tim W. Nattkemper (BMC Bioinform., 2008)

Peak intensity prediction in mass spectra using machine learning methods (Peakintensitätsvorhersage in Massenspektren mit maschinellen Lernmethoden) - Wiebke Timm (2008)

Non-linear classification for on-the-fly fractional mass filtering and targeted precursor fragmentation in mass spectrometry experiments. - Marc Kirchner; Wiebke Timm; Peying Fong; Philine Wangemann; Hanno Steen (Bioinform., 2010)