@article{BeerenwinkelSingLengaueretal.2005,
  author    = {Beerenwinkel, Niko and Sing, Tobias and Lengauer, Thomas and Rahnenfuhrer, Joerg and Roomp, Kirsten and Savenkov, Igor and Fischer, Roman and Hoffmann, Daniel and Selbig, Joachim and Korn, Klaus and Walter, Hauke and Berg, Thomas and Braun, Patrick and Faetkenheuer, Gerd and Oette, Mark and Rockstroh, Juergen and Kupfer, Bernd and Kaiser, Rolf and Daeumer, Martin},
  title     = {Computational methods for the design of effective therapies against drug resistant HIV strains},
  year      = {2005},
  abstract  = {The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data},
  language  = {en}
}
@article{HummelKeshvariWeckwerthetal.2005,
  author    = {Hummel, Jan and Keshvari, N. and Weckwerth, Wolfram and Selbig, Joachim},
  title     = {Species-specific analysis of protein sequence motifs using mutual information},
  issn      = {1471-2105},
  year      = {2005},
  abstract  = {Background: Protein sequence motifs are by definition short fragments of conserved amino acids, often associated with a specific function. Accordingly protein sequence profiles derived from multiple sequence alignments provide an alternative description of functional motifs characterizing families of related sequences. Such profiles conveniently reflect functional necessities by pointing out proximity at conserved sequence positions as well as depicting distances at variable positions. Discovering significant conservation characteristics within the variable positions of profiles mirrors group-specific and, in particular, evolutionary features of the underlying sequences. Results: We describe the tool PROfile analysis based on Mutual Information (PROMI) that enables comparative analysis of user-classified protein sequences. PROMI is implemented as a web service using Perl and R as well as other publicly available packages and tools on the server-side. On the client-side platform-independence is achieved by generally applied internet delivery standards. As one possible application analysis of the zinc finger C2H2-type protein domain is introduced to illustrate the functionality of the tool. Conclusion: The web service PROMI should assist researchers to detect evolutionary correlations in protein profiles of defined biological sequences. It is available at http:// promi.mpimpgolm. mpg.de where additional documentation can be found},
  language  = {en}
}
@article{ScholzKaplanGuyetal.2005,
  author    = {Scholz, Matthias and Kaplan, F. and Guy, C. L. and Kopka, Joachim and Selbig, Joachim},
  title     = {Non-linear PCA : a missing data approach},
  issn      = {1367-4803},
  year      = {2005},
  abstract  = {Motivation: Visualizing and analysing the potential non-linear structure of a dataset is becoming an important task in molecular biology. This is even more challenging when the data have missing values. Results: Here, we propose an inverse model that performs non-linear principal component analysis (NLPCA) from incomplete datasets. Missing values are ignored while optimizing the model, but can be estimated afterwards. Results are shown for both artificial and experimental datasets. In contrast to linear methods, non-linear methods were able to give better missing value estimations for non-linear structured data. Application: We applied this technique to a time course of metabolite data from a cold stress experiment on the model plant Arabidopsis thaliana, and could approximate the mapping function from any time point to the metabolite responses. Thus, the inverse NLPCA provides greatly improved information for better understanding the complex response to cold stress},
  language  = {en}
}