Graduiertenkolleg / PhD Program
Computer and Information Science

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Dr. Nicolas Cebron

Doctoral Student in the PhD program from 01.04.2005 to 01.05.2008. advisors 1. Prof. Dr. Michael Berthold 2. Prof. Dr. Ulrik Brandes organisational data Room :  Z 809 Tel. :  +49 (0)7531 / 88-4719 E-mail :  ncebron@gmail.com

project description

Data Mining in Bioinformatics

The development of high-throughput imaging instruments - e.g. flourescence microscope cameras - resulted in them becoming the major tool to study the effect of agents on different cell types. These devices are able to produce about 55,000 images per day; until recently, visual inspection by a domain expert was the only way to distinguish between 'active' and 'nonactive' cells.

The aim of this project is to design classifiers that are able to learn the differences between cell types. As we are dealing with a large amount of unlabeled data, the expert should label only a small subset to train the classifier. Choosing randomly drawn examples from the dataset would render the classifier biased towards the underlying distribution of the different kinds of cells.

Therefore, we try to apply the concept of 'active learning' to this task, where our learning algorithm has control over which parts of the input domain it receives information about. This concept is very similar to the human form of learning, whereby problem domains are examined in an active manner.

The objective of this thesis is to develop new concepts and algorithms based on the idea of active learning for miscellaneous data-mining algorithms in order to build stable classifiers in the field of bioinformatics.

publications

The following list of publications covers only those, which are or were published during participation at the Graduiertenkolleg / PhD program.

2008

Cebron, N., Berthold, M., Active learning for object classification: From exploration to exploitation, Journal of Data Mining and Knowledge Discovery, Vol. 18, No. 2, pp. 283-299, 2008. File on Springer's Website Cebron, N., Berthold, M., Adaptive prototype-based fuzzy classification, Fuzzy Sets and Systems, Vol. 159, No. 21, pp. 2806-2818, 2008.

2007		Berthold, M., Cebron, N., Dill, F., Gabriel, T., Kötter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B., Knime: The Konstanz Information Miner, Studies in Classification, Data Analysis, and Knowledge Organization (GfKL), Freiburg, Germany, 2007, Springer-Verlag. abstract Berthold, M., Cebron, N., Dill, F., Gabriel, T., Kötter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B., Open Source Data Pipelining für Interaktive Datenexploration, Aktuelle Trends in der Softwareforschung (do it.software-forschungstag 2007), Mathematical Intelligencer, Fellbach, Germany, 2007, MFG Stiftung Baden-Württemberg. abstract
2006		Berthold, M., Cebron, N., Dill, F., Di Fatta, G., Gabriel, T., Georg, F., Meinl, T., Ohl, P., Sieb, C., Wiswedel, B., Knime: the Konstanz Information Miner, International Workshop on Multi-Agent Systems and Simulation (MAS&S), 4th Annual Industrial Simulation Conference (ISC), pp. 58-61, Palermo, Italy, June 2006. abstract Cebron, N., Berthold, M., Adaptive fuzzy clustering, North American Fuzzy Information Processing Society (NAFIPS), pp. 188-193, Montreal, QC, Canada, 2006. abstract Cebron, N., Berthold, M., Adaptive active classification of cell assay images, European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Lecture Notes in Computer Science (LNCS), Vol. 4213, pp. 79-90, 2006, Springer-Verlag. abstract Cebron, N., Berthold, M., Adaptive Klassifikation von Zellbildern, 16. Workshop on Computational Intelligence, pp. 223 - 234, 2006.
2005		Cebron, N., Berthold, M., Mining of cell assay images using active semi-supervised clustering, Workshop on Computational Intelligence in Data Mining (ICDM), pp. 63-70, Houston, USA, 2005. abstract

2007

Cebron, N., Berthold, M., An adaptive multi objective selection strategy for active learning, University of Konstanz, TR # 235, Konstanzer Schriften in Mathematik und Informatik, August 2007. abstract

2008

Cebron, N., Aktives Lernen zur Klassifikation großer Datenmengen mittels Exploration und Spezialisierung, University of Konstanz, April 2008. abstract

curriculum vitae

2004 - 2005	Participation in special admissions procedure for the PhD Program in Computer Science.
1999 - 2004	Studies of Computer Science at the University of Applied Sciences in Braunschweig/Wolfenbuettel, Germany. Degree: Diplom-Informatiker (FH). Internship at British Telecom, Ipswich / UK: Development of an estimation procedure for task time prediction.

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Last modified March 25, 2011 by webmaster.