Buhmann, Joachim M.

Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry

Giesen, C., Wang, H. A. O., Schapiro, D., Zivanovic, N., Jacobs, A., Hattendorf, B., Schüffler, P. J., Grolimund, D., Buhmann, J. M., Brandt, S., et al. (2014) · Nature Methods

Single-cell and spatial transcriptomicsMass Spectrometry Techniques and Applications

Cited by 1,951

The Balanced Accuracy and Its Posterior Distribution

Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010) · 2010 20th International Conference on Pattern Recognition

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 1,816

Protein Identification False Discovery Rates for Very Large Proteomics Data Sets Generated by Tandem Mass Spectrometry

Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., & Aebersold, R. (2009) · Molecular & Cellular Proteomics

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 312

Wheel Defect Detection With Machine Learning

Krummenacher, G., Ong, C. S., Koller, S., Kobayashi, S., & Buhmann, J. M. (2018) · IEEE Transactions on Intelligent Transportation Systems

Railway Engineering and DynamicsMachine Fault Diagnosis Techniques

Cited by 258

Decoding the perception of pain from fMRI using multivariate pattern analysis

Brodersen, K. H., Wiech, K., Lomakina, E. I., Lin, C.-S., Buhmann, J. M., Bingel, U., Ploner, M., Stephan, K. E., & Tracey, I. (2012) · NeuroImage

Pain Mechanisms and TreatmentsPain Management and Placebo Effect

Cited by 200

Dissecting psychiatric spectrum disorders by generative embedding

Brodersen, K. H., Deserno, L., Schlagenhauf, F., Lin, Z., Penny, W. D., Buhmann, J. M., & Stephan, K. E. (2014) · NeuroImage: Clinical

Functional Brain Connectivity StudiesMental Health Research Topics

Cited by 173

Generative embedding for model-based classification of fMRI data

Brodersen, K. H., Schofield, T. M., Leff, A. P., Ong, C. S., Lomakina, E. I., Buhmann, J. M., & Stephan, K. E. (2011) · PLoS Computational Biology

Functional Brain Connectivity StudiesEEG and Brain-Computer Interfaces

Cited by 165

Automatic Human Sleep Stage Scoring Using Deep Neural Networks

Malafeev, A., Laptev, D., Bauer, S., Omlin, X., Wierzbicka, A., Wichniak, A., Jernajczyk, W., Riener, R., Buhmann, J., & Achermann, P. (2018) · Frontiers in Neuroscience

EEG and Brain-Computer InterfacesSleep and related disorders

Cited by 151

Model-based feature construction for multivariate decoding

Brodersen, K. H., Haiss, F., Ong, C. S., Jung, F., Tittgemeyer, M., Buhmann, J. M., Weber, B., & Stephan, K. E. (2011) · NeuroImage

Functional Brain Connectivity StudiesNeural dynamics and brain function

Cited by 36

Model Selection for Gaussian Process Regression

Gorbach, N. S., Bian, A. A., Fischer, B., Bauer, S., & Buhmann, J. M. (2017) · Lecture Notes in Computer Science

Gaussian Processes and Bayesian InferenceNeural Networks and Applications

Cited by 21

Proteome Coverage Prediction for Integrated Proteomics Datasets

Claassen, M., Aebersold, R., & Buhmann, J. M. (2011) · Journal of Computational Biology

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 8