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2. CompLife 2006: Cambridge, UK
- Michael R. Berthold, Robert C. Glen, Ingrid Fischer:
Computational Life Sciences II, Second International Symposium, CompLife 2006, Cambridge, UK, September 27-29, 2006, Proceedings. Lecture Notes in Computer Science 4216, Springer 2006, ISBN 3-540-45767-4
Genomics
- Michael Hirsch, Allan Tucker, Stephen Swift, Nigel J. Martin, Christine A. Orengo, Paul Kellam, Xiaohui Liu:
Improved Robustness in Time Series Analysis of Gene Expression Data by Polynomial Model Based Clustering. 1-10 - Tae-Kyung Kim, Kyoung-Ran Kim, Sang-Keun Oh, Jong-Hak Lee, Wan-Sup Cho:
A Hybrid Grid and Its Application to Orthologous Groups Clustering. 11-20 - Philip J. Uren, R. Mike Cameron-Jones, Arthur H. J. Sale:
Promoter Prediction Using Physico-Chemical Properties of DNA. 21-31 - Liping Du, Shuanhu Wu, Alan Wee-Chung Liew, David Keith Smith, Hong Yan:
Parametric Spectral Analysis of Malaria Gene Expression Time Series Data. 32-41 - Tak-Man Ma, Yuh-Dauh Lyuu, Yen-Wu Ti:
An Efficient Algorithm for Finding Long Conserved Regions Between Genes. 42-51 - Matthias Bernt, Daniel Merkle, Martin Middendorf:
The Reversal Median Problem, Common Intervals, and Mitochondrial Gene Orders. 52-63
Data Mining
- Hamse Y. Mussa, David John Lary, Robert C. Glen:
Building Structure-Property Predictive Models Using Data Assimilation. 64-73 - Illia Horenko, Johannes Schmidt-Ehrenberg, Christof Schütte:
Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models. 74-85 - Igor Trajkovski, Filip Zelezný, Jakub Tolar, Nada Lavrac:
Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. 86-96 - Robert Brijder, Hendrik Jan Hoogeboom, Michael Muskulus:
Applicability of Loop Recombination in Ciliates Using the Breakpoint Graph. 97-106 - Peter T. Corbett, Peter Murray-Rust:
High-Throughput Identification of Chemistry in Life Science Texts. 107-118 - Tim O. F. Conrad, Alexander B. Leichtle, Andre Hagehülsmann, Elmar Diederichs, Sven Baumann, Joachim Thiery, Christof Schütte:
Beating the Noise: New Statistical Methods for Detecting Signals in MALDI-TOF Spectra Below Noise Level. 119-128
Molecular Simulation
- Dmitry Nerukh, George Karvounis, Robert C. Glen:
Dynamic Complexity of Chaotic Transitions in High-Dimensional Classical Dynamics: Leu-Enkephalin Folding. 129-140 - Maxim V. Fedorov, Stephan Schumm, Jonathan M. Goodman:
Solvent Effects and Conformational Stability of a Tripeptide. 141-149 - S. Kashif Sadiq, Stefan J. Zasada, Peter V. Coveney:
Grid Assisted Ensemble Molecular Dynamics Simulations of HIV-1 Proteases Reveal Novel Conformations of the Inhibitor Saquinavir. 150-161
Molecular Informatics
- Annalisa Marsico, K. Tanuj Sapra, Daniel J. Muller, Michael Schroeder, Dirk Labudde:
A Structure-Based Analysis of Single Molecule Force Spectroscopy (SMFS) Data for Bacteriorhodopsin and Four Mutants. 162-172 - Edward O. Cannon, John B. O. Mitchell:
Classifying the World Anti-Doping Agency's 2005 Prohibited List Using the Chemistry Development Kit Fingerprint. 173-182 - Daniel Baum, Hans-Christian Hege:
A Point-Matching Based Algorithm for 3D Surface Alignment of Drug-Sized Molecules. 183-193
Systems Biology
- Andrea Y. Weiße, Illia Horenko, Wilhelm Huisinga:
Adaptive Approach for Modelling Variability in Pharmacokinetics. 194-204 - Abdelhalim Larhlimi, Alexander Bockmayr:
A New Approach to Flux Coupling Analysis of Metabolic Networks. 205-215
Biological Networks / Metabolism
- Regina Telgmann, Max von Kleist, Wilhelm Huisinga:
Software Supported Modelling in Pharmacokinetics. 216-225 - David P. Enot, Manfred Beckmann, John Draper:
On the Interpretation of High Throughput MS Based Metabolomics Fingerprints with Random Forest. 226-235 - Wouter Meuleman, Monique C. M. Welten, Fons J. Verbeek:
Construction of Correlation Networks with Explicit Time-Slices Using Time-Lagged, Variable Interval Standard and Partial Correlation Coefficients. 236-246
Computational Neuroscience
- Péter András:
The Language of Cortical Dynamics. 247-256 - A. Aldo Faisal, Jeremy E. Niven:
A Simple Method to Simultaneously Track the Numbers of Expressed Channel Proteins in a Neuron. 257-267
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