Jörg Wicker, Dipl.-Bioinf.

Wissenschaftlicher Mitarbeiter

Raum: 03-619

Johannes Gutenberg - Universität Mainz
Institut für Informatik
Staudingerweg 9
55128 Mainz, Germany

E-Mail: wicker@uni-mainz.de

Tel.: +49-6131-39-21058
Fax: +49-6131-39-23534

Sprechstunde

Dienstag: 15.00-16.00

Forschungsinteressen

Bioabbau, Bioinformatik, Chemoinformatik, Data Mining, Induktive Datenbanken, Maschinelles Lernen, Multi-Label Klassifikation, Toxikologie

Aktivitäten

Konferenzen und Workshops

Mitglied der Programm Commitee der European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2013)
Mitglied des Organisationsteams von Innovation in Predictive Toxicology: OpenTox InterAction Meeting 2011, in München.
Mitglied des Organisationsteams der MLSB11, the Fifth International Workshop on Machine Learning in Systems Biology, in Wien.

(Co-)Reviewing

10th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2008)
18th International Conference on Inutive Logic Programming (ILP 2008)

19th International Conference on Genome Informatics (GIW 2008)
From Local Patterns to Global Models - ECML/PKDD-08 Workshop (LeGo 2008)
19th International Conference on Inductive Logic Programming (ILP 2009)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2009)
IEEE International Conference on Data Mining (ICDM 2009)
ACM Symposium on Applied Computing (SAC-2010) Data Mining Track
27th International Conference on Machine Learning (ICML 2010)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010)
IEEE International Conference on Data Mining (ICDM 2010)
28th International Conference on Machine Learning (ICML 2011)
15th International Conference on Extending Database Technology (EDBT 2012)
27th Conference on Artificial Intelligence (AAAI 2013)

Veröffentlichungen

Wicker, J, Pfahringer, B, and Kramer, S (2012).
Multi-Label Classification using Boolean Matrix Decomposition
In: Proceedings of the 27th Symposium On Applied Computing, pp. 179-186 , ACM.

Wicker, J, Richter, L, and Kramer, S (2011).
SINDBAD and SiQL: Overview, Applications and Future Developments
In: Inductive Databases and Constraint-Based Data Mining (in press), ed. by Sašo Džeroski, Bart Goethals, Panče Panov. Springer, chap. 12, pp. 289-310.

Hardy, B, Douglas, N, Helma, C, Rautenberg, M, Jeliazkova, N, Jeliazkov, V, Nikolova, I, Benigni, R, Tcheremenskaia, O, Kramer, S, Girschick, T, Buchwald, F, Wicker, J, Karwath, A, Gütlein, M, Maunz, A, Sarimveis, H, Melagraki, G, Afantitis, A, Sopasakis, P, Gallagher, D, Poroikov, V, Filimonov, D, Zakharov, A, Langunin, A, Gloriozova, T, Novikov, S, Skvortsova, N, Druzhilovsky, D, Chawla, S, Gosh, I, Ray, S, Patel, H, and Escher, S (2010).
Collaborative Development of Predictive Toxicology Applications
Journal of Cheminformatics, 2(7).

Wicker, J and Kramer, S (2010).
An Extensive Multi Label Analysis of the ToxCast Data Set
In: 18th European Symposium on Quantitative Structure-Activity Relationships.

Wicker, J, Fenner, K, Ellis, L, Wackett, L, and Kramer, S (2010).
Predicting Biodegradation Products and Pathways: A Hybrid Knowledge-Based and Machine Learning Based Approach
Bioinformatics, 26(6):814-821.

Wicker, J, Fenner, K, Ellis, L, Wackett, L, and Kramer, S (2010).
Predicting Biodegradation Products and Pathways: A Hybrid Knowledge-Based and Machine Learning Based Approach
In: TransCon2010.

Richter, L, Wicker, J, Kessler, K, and Kramer, S (2008).
An Inductive Database and Query Language in the Relational Model
In: Proceedings of the 11th international conference on Extending database technology: Advances in database technology, pp. 740-744, ACM Press.

Wicker, J, Brosdau, C, Richter, L, and Kramer, S (2008).
SINDBAD SAILS: A Service Architecture for Inductive Learning Schemes
In: Proceedings of the 1st Workshop on Third Generation Data Mining: Towards Service-oriented Knowledge Discovery at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2008, ed. by Nada Lavrač, Joost Kok, Jeroen de Bruin, Vid Podpečan.

Wicker, J, Fenner, K, Ellis, L, Wackett, L, and Kramer, S (2008).
Machine Learning and Data Mining Approaches to Biodegradation Pathway Prediction
In: Proceedings of the Second International Workshop on the Induction of Process Models at ECML PKDD 2008, ed. by Will Bridewell, Toon Calders, Ana Karla de Medeiros, Stefan Kramer, Mykola Pechenizkiy,Ljupco Todorovski.

Wicker, J, Richter, L, Kessler, K, and Kramer, S (2008).
SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model
In: Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II, ed. by Walter Daelemans, Bart Goethals, Katharina Morik, pp. 690-694, Springer.

Kramer, S, Aufschild, V, Hapfelmeier, A, Jarasch, A, Kessler, K, Reckow, S, Wicker, J, and Richter, L (2006).
Inductive Databases in the Relational Model: The Data as the Bridge
In: Proceedings of the Fourth International Workshop on Knowledge Discovery in Databases, pp. 124-138.

Ausgewählte Vorträge und Tutorials

SINDBAD and SiQL: an Inductive Database and Query Language in the Relational Model, am Institut Jožef Stefan in Ljubljana, Dezember 2009

Kurzer wissenschaftlicher Lebenslauf

seit 07/2007		Doktorand in der Arbeitsgruppe Maschinelles Lernen und Data Mining in der Bioinformatik der Technischen Universität München
seit 11/2011		Wissenschaftlicher Mitarbeiter in der Arbeitsgruppe Informationssysteme der Johannes Gutenberg-Universität Mainz
11/2009-12/2009		Gast am Department of Knowledge Discoveries im Institut Jožef Stefan in Ljubljana
09/2007-08/2011		Algorithmus und REST Web Service Entwicker und Wissenschaftler im EU FP7 Projekt OpenTox (Projekt-Nr.: HEALTH-F5-2008-200787)
07/2007-09/2011		Wissenschaftlicher Mitarbeiter in der Arbeitsgruppe Maschinelles Lernen und Data Mining in der Bioinformatik der Technischen Universität München
2007		Bioinformatik Diplom an der Technischen Universität München und Ludwig-Maximilans Universität München
09/2000-05/2007		Studium Bioinformatics an der Technischen Universität München und Ludwig-Maximilans Universität München

Lehre

Lectures, seminars, courses

Hauptseminar Bioinformatik (2007, 2008, 2009, 2010, 2010)
Bioinformatik Programmierpraktikum (2008, 2009, 2010)
Data Mining Seminar (2012, 2013)
Data Mining Praktikum (2009, 2010, 2011, 2012, 2013)
Proseminar Bioinformatik (2009, 2011)
SEP: Sindbad (2008)
Assistent in Vorlesung Datenanken 1 (2012, 2013)
Assistent in Vorlesung Software Technik (2012)
Assistent im Praktikum Software Technik (2012)
Assistent in Vorlesung Data Mining (2012)
Tutor in Vorlesung Einführung in die Programmierung (2011)
Tutor in Vorlesung Maschinelles Lernen und Data Mining in der Bioinformatik (2009)
Assitent in Vorlesung Maschinelles Lernen und Statistische Datenanalyse (2012, 2013)

Diploma, Bachelor and Master Thesis

Diplomarbeit: Daniela Bieley - Integration von String Mining in eine Induktive Datenbank (2008)
Diplomarbeit: Christoph Brosdau - Serviceorientiertes Data Mining für Biologische Daten (2008)
Bachelor Arbeit: Julian Lemke - Data Imputation für Multi-Label Klassification (2011)
Bachelor Arbeit: Sebastian Lehnerer - Feature und Label-Selection für Multi-Label Klassification (2011)
Bachelor Arbeit: Florian Seifert - Data Mining in in medizinischen Datenbanken (2011)

Benutzerspezifische Werkzeuge

Sektionen