@article{DavidMarashiLarhlimietal.2011, author = {David, Laszlo and Marashi, Sayed-Amir and Larhlimi, Abdelhalim and Mieth, Bettina and Bockmayr, Alexander}, title = {FFCA a feasibility-based method for flux coupling analysis of metabolic networks}, series = {BMC bioinformatics}, volume = {12}, journal = {BMC bioinformatics}, number = {12}, publisher = {BioMed Central}, address = {London}, issn = {1471-2105}, doi = {10.1186/1471-2105-12-236}, pages = {7}, year = {2011}, abstract = {Background: Flux coupling analysis (FCA) is a useful method for finding dependencies between fluxes of a metabolic network at steady-state. FCA classifies reactions into subsets (called coupled reaction sets) in which activity of one reaction implies activity of another reaction. Several approaches for FCA have been proposed in the literature. Results: We introduce a new FCA algorithm, FFCA (Feasibility-based Flux Coupling Analysis), which is based on checking the feasibility of a system of linear inequalities. We show on a set of benchmarks that for genome-scale networks FFCA is faster than other existing FCA methods. Conclusions: We present FFCA as a new method for flux coupling analysis and prove it to be faster than existing approaches. A corresponding software tool is freely available for non-commercial use at http://www.bioinformatics.org/ffca/.}, language = {en} } @article{SchudomaLarhlimiWalther2011, author = {Schudoma, Christian and Larhlimi, Abdelhalim and Walther, Dirk}, title = {The influence of the local sequence environment on RNA loop structures}, series = {RNA : a publication of the RNA Society}, volume = {17}, journal = {RNA : a publication of the RNA Society}, number = {7}, publisher = {Cold Spring Harbor Laboratory Press}, address = {Cold Spring Harbor, NY}, issn = {1355-8382}, doi = {10.1261/rna.2550211}, pages = {1247 -- 1257}, year = {2011}, abstract = {RNA folding is assumed to be a hierarchical process. The secondary structure of an RNA molecule, signified by base-pairing and stacking interactions between the paired bases, is formed first. Subsequently, the RNA molecule adopts an energetically favorable three-dimensional conformation in the structural space determined mainly by the rotational degrees of freedom associated with the backbone of regions of unpaired nucleotides (loops). To what extent the backbone conformation of RNA loops also results from interactions within the local sequence context or rather follows global optimization constraints alone has not been addressed yet. Because the majority of base stacking interactions are exerted locally, a critical influence of local sequence on local structure appears plausible. Thus, local loop structure ought to be predictable, at least in part, from the local sequence context alone. To test this hypothesis, we used Random Forests on a nonredundant data set of unpaired nucleotides extracted from 97 X-ray structures from the Protein Data Bank (PDB) to predict discrete backbone angle conformations given by the discretized eta/theta-pseudo-torsional space. Predictions on balanced sets with four to six conformational classes using local sequence information yielded average accuracies of up to 55\%, thus significantly better than expected by chance (17\%-25\%). Bases close to the central nucleotide appear to be most tightly linked to its conformation. Our results suggest that RNA loop structure does not only depend on long-range base-pairing interactions; instead, it appears that local sequence context exerts a significant influence on the formation of the local loop structure.}, language = {en} } @article{HoehenwarterLarhlimiHummeletal.2011, author = {H{\"o}henwarter, Wolfgang and Larhlimi, Abdelhalim and Hummel, Jan and Egelhofer, Volker and Selbig, Joachim and van Dongen, Joost T. and Wienkoop, Stefanie and Weckwerth, Wolfram}, title = {MAPA Distinguishes genotype-specific variability of highly similar regulatory protein isoforms in potato tuber}, series = {Journal of proteome research}, volume = {10}, journal = {Journal of proteome research}, number = {7}, publisher = {American Chemical Society}, address = {Washington}, issn = {1535-3893}, doi = {10.1021/pr101109a}, pages = {2979 -- 2991}, year = {2011}, abstract = {Mass Accuracy Precursor Alignment is a fast and flexible method for comparative proteome analysis that allows the comparison of unprecedented numbers of shotgun proteomics analyses on a personal computer in a matter of hours. We compared 183 LC-MS analyses and more than 2 million MS/MS spectra and could define and separate the proteomic phenotypes of field grown tubers of 12 tetraploid cultivars of the crop plant Solanum tuberosum. Protein isoforms of patatin as well as other major gene families such as lipoxygenase and cysteine protease inhibitor that regulate tuber development were found to be the primary source of variability between the cultivars. This suggests that differentially expressed protein isoforms modulate genotype specific tuber development and the plant phenotype. We properly assigned the measured abundance of tryptic peptides to different protein isoforms that share extensive stretches of primary structure and thus inferred their abundance. Peptides unique to different protein isoforms were used to classify the remaining peptides assigned to the entire subset of isoforms based on a common abundance profile using multivariate statistical procedures. We identified nearly 4000,proteins which we used for quantitative functional annotation making this the most extensive study of the tuber proteome to date.}, language = {en} } @misc{LarhlimiBlachonSelbigetal.2011, author = {Larhlimi, Abdelhalim and Blachon, Sylvain and Selbig, Joachim and Nikoloski, Zoran}, title = {Robustness of metabolic networks a review of existing definitions}, series = {Biosystems : journal of biological and information processing sciences}, volume = {106}, journal = {Biosystems : journal of biological and information processing sciences}, number = {1}, publisher = {Elsevier}, address = {Oxford}, issn = {0303-2647}, doi = {10.1016/j.biosystems.2011.06.002}, pages = {1 -- 8}, year = {2011}, abstract = {Describing the determinants of robustness of biological systems has become one of the central questions in systems biology. Despite the increasing research efforts, it has proven difficult to arrive at a unifying definition for this important concept. We argue that this is due to the multifaceted nature of the concept of robustness and the possibility to formally capture it at different levels of systemic formalisms (e.g, topology and dynamic behavior). Here we provide a comprehensive review of the existing definitions of robustness pertaining to metabolic networks. As kinetic approaches have been excellently reviewed elsewhere, we focus on definitions of robustness proposed within graph-theoretic and constraint-based formalisms.}, language = {en} }