Alexander Schliep

Summary

Affiliation: Max Planck Institute for Molecular Genetics
Country: Germany

Publications

  1. ncbi request reprint Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree
    Alexander Schliep
    Dept Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 63 73, D 14195 Berlin, Germany
    Bioinformatics 22:e424-30. 2006
  2. ncbi request reprint Group testing with DNA chips: generating designs and decoding experiments
    Alexander Schliep
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Inestrasse 63 73, D 14195 Berlin, Germany
    Proc IEEE Comput Soc Bioinform Conf 2:84-91. 2003
  3. ncbi request reprint Analyzing gene expression time-courses
    Alexander Schliep
    Max Planck Institute for Molecular Genetics, Berlin, Germany
    IEEE/ACM Trans Comput Biol Bioinform 2:179-93. 2005
  4. pmc Clustering cancer gene expression data: a comparative study
    Marcilio C P De Souto
    Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    BMC Bioinformatics 9:497. 2008
  5. ncbi request reprint Robust inference of groups in gene expression time-courses using mixtures of HMMs
    Alexander Schliep
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    Bioinformatics 20:i283-9. 2004
  6. ncbi request reprint Using hidden Markov models to analyze gene expression time course data
    Alexander Schliep
    Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany
    Bioinformatics 19:i255-63. 2003
  7. ncbi request reprint The Graphical Query Language: a tool for analysis of gene expression time-courses
    Ivan G Costa
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany
    Bioinformatics 21:2544-5. 2005
  8. doi request reprint Efficient algorithms for the computational design of optimal tiling arrays
    Alexander Schliep
    Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 69 73, 14195 Berlin, Germany
    IEEE/ACM Trans Comput Biol Bioinform 5:557-67. 2008
  9. ncbi request reprint Context-specific independence mixture modeling for positional weight matrices
    Benjamin Georgi
    Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany
    Bioinformatics 22:e166-73. 2006
  10. pmc Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
    Ivan G Costa
    Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    BMC Bioinformatics 8:S3. 2007

Detail Information

Publications19

  1. ncbi request reprint Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree
    Alexander Schliep
    Dept Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 63 73, D 14195 Berlin, Germany
    Bioinformatics 22:e424-30. 2006
    ..Of great relevance, however, is the problem of identifying the presence of previously unknown targets or of targets that evolve rapidly...
  2. ncbi request reprint Group testing with DNA chips: generating designs and decoding experiments
    Alexander Schliep
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Inestrasse 63 73, D 14195 Berlin, Germany
    Proc IEEE Comput Soc Bioinform Conf 2:84-91. 2003
    ..On a data set of 28S rDNA sequences we were able to identify 660 sequences, a substantial improvement over a prior approach using unique probes which only identified 408 sequences...
  3. ncbi request reprint Analyzing gene expression time-courses
    Alexander Schliep
    Max Planck Institute for Molecular Genetics, Berlin, Germany
    IEEE/ACM Trans Comput Biol Bioinform 2:179-93. 2005
    ..A software implementing the method is freely available under the GPL from http://ghmm.org/gql...
  4. pmc Clustering cancer gene expression data: a comparative study
    Marcilio C P De Souto
    Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    BMC Bioinformatics 9:497. 2008
    ..There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context...
  5. ncbi request reprint Robust inference of groups in gene expression time-courses using mixtures of HMMs
    Alexander Schliep
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    Bioinformatics 20:i283-9. 2004
    ..A simple approach, partially supervised learning, allows to benefit from prior biological knowledge during the training. Our method allows simultaneous analysis of cyclic and non-cyclic genes and copes well with noise and missing values...
  6. ncbi request reprint Using hidden Markov models to analyze gene expression time course data
    Alexander Schliep
    Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany
    Bioinformatics 19:i255-63. 2003
    ..The inherent time dependencies in the data suggest that clustering techniques which reflect those dependencies yield improved performance...
  7. ncbi request reprint The Graphical Query Language: a tool for analysis of gene expression time-courses
    Ivan G Costa
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany
    Bioinformatics 21:2544-5. 2005
    ..AVAILABILITY: The GQL package is freely available under the GNU general public license (GPL) at http://www.ghmm.org/gql..
  8. doi request reprint Efficient algorithms for the computational design of optimal tiling arrays
    Alexander Schliep
    Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 69 73, 14195 Berlin, Germany
    IEEE/ACM Trans Comput Biol Bioinform 5:557-67. 2008
    ..A web application is available at http://tileomatic.org...
  9. ncbi request reprint Context-specific independence mixture modeling for positional weight matrices
    Benjamin Georgi
    Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany
    Bioinformatics 22:e166-73. 2006
    ..However, estimating a conventional mixture distribution for each position will in many cases cause overfitting...
  10. pmc Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
    Ivan G Costa
    Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    BMC Bioinformatics 8:S3. 2007
    ..Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns...
  11. pmc Partially-supervised protein subclass discovery with simultaneous annotation of functional residues
    Benjamin Georgi
    Max Planck Institute for Molecular Genetics, Dept, of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany
    BMC Struct Biol 9:68. 2009
    ..The locations of putative functional residues in known protein structures provide insights into how different substrate specificities are reflected on the protein structure level...
  12. doi request reprint Classifying short gene expression time-courses with Bayesian estimation of piecewise constant functions
    Christoph Hafemeister
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    Bioinformatics 27:946-52. 2011
    ..The current state-of-the-art method (SCOW) uses a variant of dynamic time warping and models time series as higher order polynomials (splines)...
  13. pmc Identifying protein complexes directly from high-throughput TAP data with Markov random fields
    Wasinee Rungsarityotin
    Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestr, 73, D 14195 Berlin, Germany
    BMC Bioinformatics 8:482. 2007
    ..First, they construct an interaction graph from the data, predominantly using heuristics, and subsequently cluster its vertices to identify protein complexes...
  14. pmc Inferring differentiation pathways from gene expression
    Ivan G Costa
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    Bioinformatics 24:i156-64. 2008
    ..In general, the similarities in the gene expression programs of cell populations reflect the similarities in the differentiation path...
  15. pmc Gene expression trees in lymphoid development
    Ivan G Costa
    Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
    BMC Immunol 8:25. 2007
    ....
  16. pmc pGQL: A probabilistic graphical query language for gene expression time courses
    Ruben Schilling
    Max Planck Institute for Molecular Genetics, Department of Computational Biology, Ihnestr, 63 73, 14195 Berlin, Germany
    BioData Min 4:9. 2011
    ..abstract:..
  17. ncbi request reprint New, improved, and practical k-stem sequence similarity measures for probe design
    Anthony J Macula
    Biomathematics Group, SUNY Geneseo, Geneseo, New York 14454, USA
    J Comput Biol 15:525-34. 2008
    ....
  18. ncbi request reprint Optimal robust non-unique probe selection using Integer Linear Programming
    Gunnar W Klau
    Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria
    Bioinformatics 20:i186-93. 2004
    ..If we allow to test for more than one target in the sample, the design of the probe set becomes difficult in the case of non-unique probes...
  19. ncbi request reprint Selecting signature oligonucleotides to identify organisms using DNA arrays
    Lars Kaderali
    Center for Applied Computer Sciences Cologne ZAIK, University of Cologne, Weyertal 80, 50931 Koln, Germany
    Bioinformatics 18:1340-9. 2002
    ..Furthermore, all probes on the array must hybridize to their intended targets under the same reaction conditions, most importantly at the temperature T at which the experiment is conducted...