@article{FeherLisecRoemischMargletal.2014,
  author    = {Feher, Kristen and Lisec, Jan and Roemisch-Margl, Lilla and Selbig, Joachim and Gierl, Alfons and Piepho, Hans-Peter and Nikoloski, Zoran and Willmitzer, Lothar},
  title     = {Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach},
  series = {PLoS one},
  volume    = {9},
  journal   = {PLoS one},
  number    = {1},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0085435},
  pages     = {9},
  year      = {2014},
  language  = {en}
}
@article{KlieNikoloskiSelbig2014,
  author    = {Klie, Sebastian and Nikoloski, Zoran and Selbig, Joachim},
  title     = {Biological cluster evaluation for gene function prediction},
  series = {Journal of computational biology},
  volume    = {21},
  journal   = {Journal of computational biology},
  number    = {6},
  publisher = {Liebert},
  address   = {New Rochelle},
  issn      = {1066-5277},
  doi       = {10.1089/cmb.2009.0129},
  pages     = {428 -- 445},
  year      = {2014},
  abstract  = {Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set.},
  language  = {en}
}
@article{GuoFuJuerchottetal.2014,
  author    = {Guo, Ke-Tai and Fu, Peng and Juerchott, Kathrin and Motaln, Helena and Selbig, Joachim and Lah, Tamara T. and Tonn, J{\"o}rg-Christian and Schichor, Christian},
  title     = {The expression of Wnt-inhibitor DKK1 (Dickkopf 1) is determined by intercellular crosstalk and hypoxia in human malignant gliomas},
  series = {Journal of cancer research and clinical oncology : official organ of the Deutsche Krebsgesellschaft},
  volume    = {140},
  journal   = {Journal of cancer research and clinical oncology : official organ of the Deutsche Krebsgesellschaft},
  number    = {8},
  publisher = {Springer},
  address   = {New York},
  issn      = {0171-5216},
  doi       = {10.1007/s00432-014-1642-2},
  pages     = {1261 -- 1270},
  year      = {2014},
  abstract  = {Objective Wnt signalling pathways regulate proliferation, motility and survival in a variety of human cell types. Dickkopf 1 (DKK1) gene codes for a secreted Wnt inhibitory factor. It functions as tumour suppressor gene in breast cancer and as a pro-apoptotic factor in glioma cells. In this study, we aimed to demonstrate whether the different expression of DKK1 in human glioma-derived cells is dependent on microenvironmental factors like hypoxia and regulated by the intercellular crosstalk with bone-marrow-derived mesenchymal stem cells (bmMSCs). Methods Glioma cell line U87-MG, three cell lines from human glioblastoma grade IV (glioma-derived mesenchymal stem cells) and three bmMSCs were selected for the experiment. The expression of DKK1 in cell lines under normoxic/hypoxic environment or co-culture condition was measured using real-time PCR and enzyme-linked immunoadsorbent assay. The effect of DKK1 on cell migration and proliferation was evaluated by in vitro wound healing assays and sulphorhodamine assays, respectively. Results Glioma-derived cells U87-MG displayed lower DKK1 expression compared with bmMSCs. Hypoxia led to an overexpression of DKK1 in bmMSCs and U87-MG when compared to normoxic environment, whereas co-culture of U87-MG with bmMSCs induced the expression of DKK1 in both cell lines. Exogenous recombinant DKK1 inhibited cell migration on all cell lines, but did not have a significant effect on cell proliferation of bmMSCs and glioma cell lines. Conclusion In this study, we showed for the first time that the expression of DKK1 was hypoxia dependent in human malignant glioma cell lines. The induction of DKK1 by intracellular crosstalk or hypoxia stimuli sheds light on the intense adaption of glial tumour cells to environmental alterations.},
  language  = {en}
}
@article{RajasundaramRunavotGuoetal.2014,
  author    = {Rajasundaram, Dhivyaa and Runavot, Jean-Luc and Guo, Xiaoyuan and Willats, William G. T. and Meulewaeter, Frank and Selbig, Joachim},
  title     = {Understanding the relationship between cotton fiber properties and non-cellulosic cell wall polysaccharides},
  series = {PLoS one},
  volume    = {9},
  journal   = {PLoS one},
  number    = {11},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0112168},
  pages     = {11},
  year      = {2014},
  abstract  = {A detailed knowledge of cell wall heterogeneity and complexity is crucial for understanding plant growth and development. One key challenge is to establish links between polysaccharide-rich cell walls and their phenotypic characteristics. It is of particular interest for some plant material, like cotton fibers, which are of both biological and industrial importance. To this end, we attempted to study cotton fiber characteristics together with glycan arrays using regression based approaches. Taking advantage of the comprehensive microarray polymer profiling technique (CoMPP), 32 cotton lines from different cotton species were studied. The glycan array was generated by sequential extraction of cell wall polysaccharides from mature cotton fibers and screening samples against eleven extensively characterized cell wall probes. Also, phenotypic characteristics of cotton fibers such as length, strength, elongation and micronaire were measured. The relationship between the two datasets was established in an integrative manner using linear regression methods. In the conducted analysis, we demonstrated the usefulness of regression based approaches in establishing a relationship between glycan measurements and phenotypic traits. In addition, the analysis also identified specific polysaccharides which may play a major role during fiber development for the final fiber characteristics. Three different regression methods identified a negative correlation between micronaire and the xyloglucan and homogalacturonan probes. Moreover, homogalacturonan and callose were shown to be significant predictors for fiber length. The role of these polysaccharides was already pointed out in previous cell wall elongation studies. Additional relationships were predicted for fiber strength and elongation which will need further experimental validation.},
  language  = {en}
}