Alexander Schliep

Head

Mailing address:
Department of Computer Science and Engineering
Chalmers | Gothenburg University
41296 Gothenburg, Sweden

Visiting address:
Department of Computer Science and Engineering
Chalmers | Gothenburg University
D&IT 6480
Rännvägen 6 B
41258 Göteborg, Sweden

Phone: +46-31-772-1000
Fax:
E-mail: alexander@schlieplab.org

Alexander Schliep received a MS in Mathematics from the University of Delaware working with Felix Lazebnik in extremal graph theory and a PhD degree in computer science from the Center for Applied Computer Science (ZAIK/ZPR) at the Universität zu Köln, Germany (2001; advisor Rainer Schrader), in collaboration with David C. Torney in the Theoretical Biology and Biophysics Group (T-10) at Los Alamos National Laboratory. From 2002-2009 he was the group leader of the Bioinformatics Algorithms Group in the Department for Computational Molecular Biology at the Max Planck Institute for Molecular Genetics in Berlin.

From 2009-2016 he was an associate professor Rutgers University with a joint position in theDepartment of Computer Science and the BioMaPS Institute for Quantitative Biology. He is a permanent member of DIMACS, the Center for Discrete Mathematics and Theoretical Computer Science. In 2016 he joined the department for Computer Science and Engineering (CSE) which is jointly between Chalmers and Gothenburg University.

He serves as an associate editor for BMC Bioinformatics and http://peerj.com. Previously, he served as an associate editor for Discrete Mathematics, Algorithms and Applications.

Further information can be found at his Google Scholar profile and Orcid Profile 0000-0002-3555-3188.

Upcoming/Recent presentations

Jan. 24, 2017. Statistical Bioinformatics at Genome-Scale. Invited Talk at SciLifeLab, Stockholm University, Stockholm, Sweden

Nov. 11, 2016. Compressive Omics: Data science for biomedical applications. Invited Talk at 4th Swedish Workshop on Data Science (SweDS 2016), Skövde, Sweden

Oct. 17, 2016. Statistical Bioinformatics for Genome-Scale Data. Invited Talk at Lifescience Area of Advance Seminar Series, Chalmers, Gothenburg, Sweden.

July 11, 2016. Meaningful Data Compression and Reduction of High-Throughput Sequencing Data. Contributed Talk at Special session on Compressive Omics, ISMB 2016, Orlando, FL

June 17, 2016. Compressive Genomics: Statistical Bioinformatics for Genome-Scale Data. Invited Talk at Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine

Recent publications

P. Damaschke and A. Schliep An Optimization Problem Related to Bloom Filters With Bit Patterns. In SOFSEM 2018: Theory and Practice of Computer Science, Springer, Jan 2018. To appear.

G.A. Bravo, A. Antonelli, C.D. Bacon, K. Bartoszek, M.P.K. Blom, S. Huynh, G. Jones, L.L. Knowles, S. Lamichhaney, T. Marcussen, H. Morlon, L.K. Nakhleh, B. Oxelman, B. Pfeil, A. Schliep, N. Wahlberg, F.P. Werneck, J. Wiedenhoeft, S. Willows-Munro and S.V. Edwards Embracing heterogeneity: building the Tree of Life and the future of phylogenomics. PeerJ 2018. Preprint, under review.

J. Wiedenhoeft and A. Schliep Using HaMMLET for Bayesian segmentation of WGS read-depth data. In Copy Number Variants: Methods and Protocols, Springer, 2018. To be published..

C. Meijner, S. Persson, A. Schliep, B. Eliasson and O. Mogren Automatic blood glucose prediction with confidence using recurrent neural networks. In Sep 2017. Under review.

I.O.N. Lopes, A. Schliep and A.P.L.F. Carvalho Automatic learning of pre-miRNAs from different species. BMC Bioinformatics 2016, 17:224.