Bioinformatics
Physical Mapping of DNA
- Partial Digest is Hard to Solve for Erroneous Input Data. Mark Cieliebak, Stephan Eidenbenz, and Paolo Penna.Theoretical Computer Science, 2005.
- Complexity
and Approximability of Double Digest. Mark Cieliebak, Stephan
Eidenbenz, and Gerhard J. Woeginger. Journal of Bioinformatics
and Computational Biology, 2005.
- Measurement
Errors Make the Partial Digest Problem NP-hard. Mark Cieliebak
and Stephan Eidenbenz. LATIN 2004.
- Noisy Data Make
the Partial Digest Problem NP-hard. Mark Cieliebak, Stephan Eidenbenz,
and Paolo Penna. WABI 2003.
- Double Digest
Revisited: Complexity and Approximability in the Presence of Noisy Data.
Mark Cieliebak, Stephan Eidenbenz, and Gerhard J. Woeginger. COCOON 2003.
- Noisy Data Make the
Partial Digest Problem NP-hard. Mark Cieliebak, Stephan Eidenbenz,
and Paolo Penna. Technical Report 381, ETH Zurich, 2002.
- Double Digest Revisited:
Complexity and Approximability in the Presence of Noisy Data.
Mark Cieliebak, Stephan Eidenbenz, and Gerhard J. Woeginger. Technical Report
382, ETH Zurich, 2002.
Protein Identification
- Finding Submasses in Weighted Strings with Fast Fourier Transform. Nikhil Bansal, Mark Cieliebak, and Zsuzsanna Lipták. Discrete Applied Mathematics (DAM), Special Issue on Computational Biology, to appear.
- AUDENS: A Tool for Automated Peptide de Novo Sequencing. Jonas Grossmann, Franz F. Roos, Mark Cieliebak, Zsuzsanna Lipták, Lucas K. Mathis, Matthias Müller, Wilhelm Gruissem, and Sacha Baginsky. Journal of Proteome Research, 2005.
- Efficient
Algorithms for Finding Submasses in Weighted Strings.
Nikhil Bansal, Mark Cieliebak, and Zsuzsanna Lipták. CPM
2004.
- Algorithmic
Complexity of Protein Identification: Combinatorics of Weighted
Strings.
Mark Cieliebak, Thomas Erlebach, Zsuzsanna
Lipták, Jens Stoye, and
Emo Welzl. Discrete Applied Mathematics, 2004.
- Algorithmic
Complexity of Protein Identification: Searching in Weighted Strings.
Mark Cieliebak, Thomas Erlebach, Zsuzsanna Lipták, Jens Stoye,
and Emo Welzl. TCS 2002.
- AuDeNS:
A Tool for Automatic De Novo Peptide Sequencing. Sacha
Baginsky, Mark Cieliebak, Wilhelm Gruissem, Torsten Kleffmann, Zsuzsanna
Lipták, and Matthias Müller,
and Paolo Penna. Technical Report 383, ETH Zurich, 2002.
- Statistical
Foundations of De Novo Sequencing. Sacha Baginsky, Mark
Cieliebak, Jonas Grossmann, Wilhelm Gruissem, Torsten Kleffmann, and
Lukas K. Mathis. Poster Abstract, SPS 2002.
- Algorithmic
Complexity of Protein Identification: Combinatorics of Weighted Strings.
Mark Cieliebak, Thomas Erlebach, Zsuzsanna Lipták, Jens Stoye, and
Emo Welzl. Technical Report 361, ETH Zurich, 2001.
Gathering Autonomous Robots
Combinatorics
- Scheduling
with Release Times and Deadlines on a Minimum Number of Machines.
Mark Cieliebak, Thomas Erlebach, Fabian Hennecke, Birgitta Weber, and
Peter Widmayer. IFIP TCS 2004.
- Scheduling with
Release Times and Deadlines on a Minimum Number of Machines.
Mark Cieliebak, Thomas Erlebach, Fabian Hennecke, Birgitta Weber, and Peter
Widmayer. Technical Report 419, ETH Zurich, 2003.
- Composing
Equipotent Teams. Mark Cieliebak, Stephan Eidenbenz, and
Aris Pagourtzis. FCT 2003.
- Equal Sum
Subsets: Complexity of Variations. Mark Cieliebak, Stephan
Eidenbenz, Aris Pagourtzis, and Konrad Schlude. Technical Report 370, ETH
Zurich, 2002.
Attribut-Efficient Learning
Geometry
Other Publications
- Startschuss
für die 8. Schweizer Informatikolympiade. Mark Cieliebak
and Roland Ulber. Visionen, ETH Zurich, 2003.
- Javakurs: Ein Autointerview
mit den Veranstaltern. Alexander Below and Mark Cieliebak. Visionen,
ETH Zurich, 2002.