Principal Investigator

DFG Priority Programme SPP1392: "Integrative Analysis of Olfaction" (second funding period), subproject "Does topography matter? Predicting odor response maps and inhibitory interactions between glomeruli for the dorsal olfactory bulb".

DFG Priority Programme SPP1392: "Integrative Analysis of Olfaction" (first funding period), subproject "Testing olfactory bulb chemotopy and deorphanizing olfactory receptors by combining in vivo functional imaging and virtual screening" in collaboration with Hartwig Spors (MPI for Biophysics, Frankfurt/Main). (concluded).

Bernstein Center Berlin, 2nd funding period 2010 - 2014, subproject "Unmixing of sensory channels encoding noxious mechanical and heat stimuli",  in collaboration with Gary Lewin (MDC Berlin-Buch)

• Information processing in neuronal systems

• Neuromorphic computing

• Learning in neuronal systems

• Cheminformatics: Structure-activity relationships for olfactory receptor ligands

More details at my project page.

 

Peer-reviewed articles

Soelter J, Schumacher J, Spors H, Schmuker M (2014). Automatic Segmentation of Odour Maps in the Mouse Olfactory Bulb using regularized Non-negative Matrix Factorization. Neuroimage 98:279-288. [abstract] [PDF] (Open Access)

Schmuker M, Pfeil T, Nawrot MP (2014) A neuromorphic network for generic multivariate data classification. PNAS, 111(6):2081-2086. Open Access Full Text  | Open Access PDF + SI

Gabler S, Soelter J, Hussain T, Sachse S and Schmuker M (2013). Physicochemical vs. vibrational descriptors for prediction of odor receptor responses. Molecular Informatics 32(9-10):855-865. Abstract | PDF

Kasap B and Schmuker M (2013). Improving odor classification through self-organized lateral inhibition in a spiking olfaction-inspired network. Proceedings of the 6th International Conference on Neural Engineering (NER2013), Nov. 6-8 2013, San Diego, CA, USA. Abstract | PDF

Pfeil T, Grübl A, Jeltsch S, Müller E, Müller P, Petrovici MA, Schmuker M, Brüderle D, Schemmel J and Meier K (2013). Six networks on a universal neuromorphic computing substrate. Frontiers in Neuroscience 7:11. Abstract | Full Text | PDF | prepub on ArXiv

Schmuker M, Yamagata N, Nawrot M and Menzel R (2011). Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee. Frontiers in Neuroengineering 4:17. Abstract | PDF

Eschbach C, Vogt K, Schmuker M, Gerber B (2011): The Similarity between Odors and Their Binary Mixtures in Drosophila. Chemical Senses 36(7):613-621. abstract | Full Text | PDF

Häusler C, Nawrot M P and Schmuker M (2011): A spiking neuron classifier network with a deep architecture inspired by the olfactory system of the honeybee. Proceedings of the 5th International IEEE EMBS Conference on Neural Engineering, April 27 - May 01 2011, Cancun, Mexico. doi:10.1109/NER.2011.5910522 | Full text

Chen Y-C, Mishra D, Schmitt L, Schmuker M and Gerber B (2011): A Behavioral Odor Similarity "Space" in Larval Drosophila. Chem. Senses 36(7):223-235. Free full text

Yamagata N, Schmuker M, Szyszka P, Mizunami M and Menzel R (2009) Differential odor processing in two olfactory pathways in the honeybee. Front. Syst. Neurosci. 3:16. doi:10.3389/neuro.06.016.2009 abstract PDF

Schmuker M, Weidert M and Menzel R (2008): A network model for learing-induced changes in odor representation in the antennal lobe, in Proceedings of the Second french conference on Computational Neuroscience, Marseille, Laurent U. Perrinet and Emmanuel Daucé (ed.). Full text

Schmuker M, Schneider G (2007): Processing and classification of chemical data inspired by insect olfaction. PNAS 104:20285-20289. PubMed

Schmuker M, de Bruyne M, Hähnel M and Schneider, G (2007): Predicting olfactory receptor neuron responses from odorant structure, Chemistry Central Journal, 1:11. Free full text

Renner S, Hechenberger M, Noeske T, Böcker A, Jatzke C, Schmuker M, Parsons CG, Weil T and Schneider G (2007): Searching for drug scaffolds with 3D pharmacophores and neural network ensembles, Angewandte Chemie International Edition, 46(28):5336-5339. PubMed

Schmuker M, Schwarte F, Brück A, Proschak E, Tanrikulu Y, Givehchi A, Scheiffele K and Schneider G (2007): SOMMER: Self-Organising Maps for Education and Research, Journal of Molecular Modeling, 13(1):225-228 SpringerLink PubMed
SOMMER is available online.

Meissner M, Schmuker M and Schneider G (2006): Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training. BMC Bioinformatics, 7:125. Free Full Text

Schmuker M, Givehchi A, Schneider G (2004): Impact of different software implementations on the performance of the Maxmin method for diverse subset selection. Molecular Diversity 8(4):421-425 PubMed

Zuegge J, Ralph S, Schmuker M, McFadden GI, Schneider G (2001): Deciphering apicoplast targeting signals - feature extraction from nuclear-encoded precursors of Plasmodium falciparum apicoplast proteins. Gene 280(1-2):19-26 PubMed

Book chapter

Schmuker M, Schneider G (2011): Brain-like Processing and Classification of Chemical Data: An Approach Inspired by the Sense of Smell, 289-303. In Lodhi H and Yamanishi, Y (Ed.): Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, (p. 289-303). Hershey, PA: IGI Global.

PhD thesis

Schmuker M (2007): Analysis of Coding Principles in the Olfactory System and their Application in Cheminformatics. PhD Thesis, Johann Wolfgang Goethe-Universität Frankfurt am Main, Germany. PDF (2.2 MB)

For citations refer to the following:
URN: urn:nbn:de:hebis:30-53163
URL: http://publikationen.ub.uni-frankfurt.de/volltexte/2008/5316/

Diploma thesis

Schmuker M (2003): Modeling homogeneity detection with spiking neurons in primate visual cortex. Diploma Thesis, Albert-Ludwigs-Universität Freiburg im Breisgau, Germany. pdf (1.4 MB)

Software

• Contributed an implementation of the NIPALS algorithm for principal component analysis and a Neural Gas implementation to the MDP toolkit, a data processing framework written in python.
• SOMMER, The Self-Organizing Map Maker for Education and Research. A full-blown application written in Java for training and visualization of Self-Organizing Maps with various topologies (see also Schmuker et al., J. Mol. Model., 2007). SOMMER's source code is open source and available from the sourceforge project page.
• MaxMinSelection light: Diverse subset selection (see also Schmuker et al., Mol. Divers., 2004).
• I'm an enthusiastic user of PyNN, a Python package for simulator-independent specification of neuronal network models.