Wiebke Timm

Marc Kirchner, Wiebke Timm, Peying Fong, Philine Wangemann, Hanno Steen: Non-linear classification for on-the-fly fractional mass filtering and targeted precursor fragmentation in mass spectrometry experiments. Bioinformatics 26(6): 791-797 (2010)

Wiebke Timm, Alexandra Scherbart, Sebastian Böcker, Oliver Kohlbacher, Tim W. Nattkemper: Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics 9 (2008)

Alexandra Scherbart, Wiebke Timm, Sebastian Böcker, Tim W. Nattkemper: Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. ICONIP (1) 2008: 513-520

Alexandra Scherbart, Wiebke Timm, Sebastian Böcker, Tim W. Nattkemper: Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. ICANN (2) 2007: 90-99

Tim W. Nattkemper, Bert Arnrich, Oliver Lichte, Wiebke Timm, Andreas Degenhard, Linda Pointon, Carmel Hayes, Martin O. Leach: The UK MARIBS Breast Screening Study: Evaluation of radiological features for breast tumour classification in clinical screening with machine learning methods. Artificial Intelligence in Medicine 34(2): 129-139 (2005)