323,098 research outputs found
Breeding goats for organic production in Germany
No full textWith only 120,000 females (year 2000), goat keeping is a niche activity in animal husbandry in Germany. Most of the goats (about 90%) are kept on part-time farms. The main reasons they are kept are as a hobby, for milk production and for landscape management; in many cases it is a non-profit oriented activity. There are estimates (no official statistics exist) that 20,000 goats are milked and 10,000 are used in landscape management to avoid shrub succession on protected biotopes. In the year 2000 10% of the goats (12,000) were kept on organic farms but not all for economic reasons.
Because the dairy breeds in Germany (White and Brown German Alpine) are selected under intensive keeping conditions, breeding under the restrictions of organic farming is necessary to get adopted and high yielding flocks. This is even more true in the case of harsh environmental conditions in landscape management. The German breeds are not suitable for the needs while grazing on marginal biotopes. This paper will show some results of:
· a ten-year breeding programme for more milk ingredients, fat and protein, in a flock of 30 mother goats on an organic farm and
· the breeding programme of the “Witzenhäuser Landschaftspflegeziege WLZ” for the new purposes of landscape management
Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms
No full textBaumbach J, Rahmann S, Tauch A. Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms. BMC Systems Biology. 2009;3(1):8.Background: Transcriptional regulation of gene activity is essential for any living organism. Transcription factors therefore recognize specific binding sites within the DNA to regulate the expression of particular target genes. The genome-scale reconstruction of the emerging regulatory networks is important for biotechnology and human medicine but cost-intensive, time-consuming, and impossible to perform for any species separately. By using bioinformatics methods one can partially transfer networks from well-studied model organisms to closely related species. However, the prediction quality is limited by the low level of evolutionary conservation of the transcription factor binding sites, even within organisms of the same genus. Results: Here we present an integrated bioinformatics workflow that assures the reliability of transferred gene regulatory networks. Our approach combines three methods that can be applied on a large-scale: re-assessment of annotated binding sites, subsequent binding site prediction, and homology detection. A gene regulatory interaction is considered to be conserved if (1) the transcription factor, (2) the adjusted binding site, and (3) the target gene are conserved. The power of the approach is demonstrated by transferring gene regulations from the model organism Corynebacterium glutamicum to the human pathogens C. diphtheriae, C. jeikeium, and the biotechnologically relevant C. efficiens. For these three organisms we identified reliable transcriptional regulations for similar to 40% of the common transcription factors, compared to similar to 5% for which knowledge was available before. Conclusion: Our results suggest that trustworthy genome-scale transfer of gene regulatory networks between organisms is feasible in general but still limited by the level of evolutionary conservation
T-Reg Comparator: an analysis tool for the comparison of position weight matrices
No full textRöpcke S, Grossmann S, Rahmann S, Vingron M. T-Reg Comparator: an analysis tool for the comparison of position weight matrices. Nucleic Acids Research. 2005;33(Web Server):W438-W441.T-Reg Comparator is a novel software tool designed to support research into transcriptional regulation. Sequence motifs representing transcription factor binding sites are usually encoded as position weight matrices. The user inputs a set of such weight matrices or binding site sequences and our program matches them against the T-Reg database, which is presently built on data from the Transfac [E. Wingender (2004) In Silico Biol., 4, 55-61] and Jaspar [A. Sandelin, W. Alkema, P. Engstrom, W. W. Wasserman and B. Lenhard (2004) Nucleic Acids Res., 32, D91-D94]. Our tool delivers a detailed report on similarities between user-supplied motifs and motifs in the database. Apart from simple one-to-one relationships, T-Reg Comparator is also able to detect similarities between submatrices. In addition, we provide a user interface to a program for sequence scanning with weight matrices. Typical areas of application for T-Reg Comparator are motif and regulatory module finding and annotation of regulatory genomic regions. T-Reg Comparator is available at http://treg.molgen.mpg.de
Searching for the Shortest Common Supersequence
No full textCarvalho Jr. de S, Rahmann S. Searching for the Shortest Common Supersequence. Technische Fakultät der Universität Bielefeld, Abteilung Informationstechnik; 2005
Large scale clustering of protein sequences with FORCE - a layout based heuristic for weighted cluster editing
No full textWittkop T, Baumbach J, Lobo FP, Rahmann S. Large scale clustering of protein sequences with FORCE - a layout based heuristic for weighted cluster editing. BMC Bioinformatics. 2007;8(1): 396.Background: Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clustering approaches, following different strategies, have been published to attack this problem. Today, new sequencing technologies provide huge amounts of sequence data that has to be efficiently clustered with constant or increased accuracy, at increased speed. Results: We advocate that the model of weighted cluster editing, also known as transitive graph projection is well-suited to protein clustering. We present the FORCE heuristic that is based on transitive graph projection and clusters arbitrary sets of objects, given pairwise similarity measures. In particular, we apply FORCE to the problem of protein clustering and show that it outperforms the most popular existing clustering tools ( Spectral clustering, TribeMCL, GeneRAGE, Hierarchical clustering, and Affinity Propagation). Furthermore, we show that FORCE is able to handle huge datasets by calculating clusters for all 192 187 prokaryotic protein sequences ( 66 organisms) obtained from the COG database. Finally, FORCE is integrated into the corynebacterial reference database CoryneRegNet. Conclusion: FORCE is an applicable alternative to existing clustering algorithms. Its theoretical foundation, weighted cluster editing, can outperform other clustering paradigms on protein homology clustering. FORCE is open source and implemented in Java. The software, including the source code, the clustering results for COG and CoryneRegNet, and all evaluation datasets are available at http://gi.cebitec.uni-bielefeld.de/comet/force/
Improving the design of GeneChip arrays by combining placement and embedding
No full textCarvalho Jr. de SA, Rahmann S. Improving the design of GeneChip arrays by combining placement and embedding. In: Computational Systems Bioformatics Conference. Vol 6. 2007: 417-427
Algorithmen für das Design von DNA-Microarrays
No full textRahmann S. Algorithmen für das Design von DNA-Microarrays. In: Wagner D, ed. Ausgezeichnete Informatikdissertationen 2004. Lecture Notes in Informatics. Vol 5. Bonn: Ges. für Informatik ; 2005: 145-154
CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks
No full textBaumbach J, Brinkrolf K, Czaja LF, Rahmann S, Tauch A. CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. BMC Genomics. 2006;7(1): 24
Exact and Heuristic Algorithms for Weighted Cluster Editing
No full textRahmann S, Wittkop T, Baumbach J, Martin M, Truss A, Böcker S. Exact and Heuristic Algorithms for Weighted Cluster Editing. Comput Syst Bioinformatics Conf. 2007;6(1):391-401
Accurate and robust phylogeny estimation based on profile distances: a study of the Chlorophyceae (Chlorophyta)
No full textMüller T, Rahmann S, Dandekar T, Wolf M. Accurate and robust phylogeny estimation based on profile distances: a study of the Chlorophyceae (Chlorophyta). BMC Evolutionary Biology. 2004;4(1): 20.Background: In phylogenetic analysis we face the problem that several subclade topologies are known or easily inferred and well supported by bootstrap analysis, but basal branching patterns cannot be unambiguously estimated by the usual methods (maximum parsimony (MP), neighbor-joining (NJ), or maximum likelihood (ML)), nor are they well supported. We represent each subclade by a sequence profile and estimate evolutionary distances between profiles to obtain a matrix of distances between subclades. Results: Our estimator of profile distances generalizes the maximum likelihood estimator of sequence distances. The basal branching pattern can be estimated by any distance-based method, such as neighbor-joining. Our method (profile neighbor-joining, PNJ) then inherits the accuracy and robustness of profiles and the time efficiency of neighbor-joining. Conclusions: Phylogenetic analysis of Chlorophyceae with traditional methods (MP, NJ, ML and MrBayes) reveals seven well supported subclades, but the methods disagree on the basal branching pattern. The tree reconstructed by our method is better supported and can be confirmed by known morphological characters. Moreover the accuracy is significantly improved as shown by parametric bootstrap
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