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- Andersson, Siv G E, et al.
(författare)
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Comparative genomics of microbial pathogens and symbionts.
- 2002
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Ingår i: Bioinformatics. - 1367-4803 .- 1367-4811. ; 18 Suppl 2, s. S17-
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Tidskriftsartikel (refereegranskat)abstract
- We are interested in quantifying the contribution of gene acquisition, loss, expansion and rearrangements to the evolution of microbial genomes. Here, we discuss factors influencing microbial genome divergence based on pair-wise genome comparisons of closely related strains and species with different lifestyles. A particular focus is on intracellular pathogens and symbionts of the genera Rickettsia, Bartonella and BUCHNERA: Extensive gene loss and restricted access to phage and plasmid pools may provide an explanation for why single host pathogens are normally less successful than multihost pathogens. We note that species-specific genes tend to be shorter than orthologous genes, suggesting that a fraction of these may represent fossil-orfs, as also supported by multiple sequence alignments among species. The results of our genome comparisons are placed in the context of phylogenomic analyses of alpha and gamma proteobacteria. We highlight artefacts caused by different rates and patterns of mutations, suggesting that atypical phylogenetic placements can not a priori be taken as evidence for horizontal gene transfer events. The flexibility in genome structure among free-living microbes contrasts with the extreme stability observed for the small genomes of aphid endosymbionts, in which no rearrangements or inflow of genetic material have occurred during the past 50 millions years (1). Taken together, the results suggest that genomic stability correlate with the content of repeated sequences and mobile genetic elements, and thereby indirectly with bacterial lifestyles.
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| 2. |
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| 3. |
- Arvestad, Lars, et al.
(författare)
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Bayesian gene/species tree reconciliation and orthology analysis using MCMC
- 2003
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Ingår i: Bioinformatics. - : Oxford Journals. - 1367-4803 .- 1367-4811. ; 19, s. i7-i15
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. Results: We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves ‘inside’ a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch’s original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for reconciliations. That is, we can find the most probable reconciliations and estimate the probability of any reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.
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| 4. |
- Edvardsson, Sverker, et al.
(författare)
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A search for H/ACA snoRNAs in yeast using MFE secondary structure prediction
- 2003
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 19:7, s. 865-873
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Tidskriftsartikel (refereegranskat)abstract
- We develop an algorithm to screen the yeast genome for novel H/ACA snoRNAs. To achieve this, we introduce some new methods for facilitating the search for noncoding RNAs in genomic sequences which are based on properties of predicted minimum free-energy (MFE) secondary structures. The algorithm has been implemented and can be generalized to enable screening of other eukaryote genomes. We find that use of primary sequence alone is insufficient for identifying novel H/ACA snoRNAs. Only the use of secondary structure filters reduces the number of candidates to a manageable size. From genomic context, we identify three strong H/ACA snoRNA candidates. These together with a further 47 candidates obtained by our analysis are being experimentally screened.
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| 5. |
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| 6. |
- Forslund, Kristoffer, et al.
(författare)
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VisRD--visual recombination detection.
- 2004
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Ingår i: Bioinformatics. - 1367-4803 .- 1367-4811. ; 20:18, s. 3654-5
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Tidskriftsartikel (refereegranskat)
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| 7. |
- Holme, Petter, et al.
(författare)
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Subnetwork hierarchies of biochemical pathways
- 2003
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 19:4, s. 532-538
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: The vastness and complexity of the biochemical networks that have been mapped out by modern genomics calls for decomposition into subnetworks. Such networks can have inherent non-local features that require the global structure to be taken into account in the decomposition procedure. Furthermore, basic questions such as to what extent the network (graph theoretically) can be said to be built by distinct subnetworks are little studied. Results: We present a method to decompose biochemical networks into subnetworks based on the global geometry of the network. This method enables us to analyze the full hierarchical organization of biochemical networks and is applied to 43 organisms from the WIT database. Two types of biochemical networks are considered: metabolic networks and whole-cellular networks (also including for example information processes). Conceptual and quantitative ways of describing the hierarchical ordering are discussed. The general picture of the metabolic networks arising from our study is that of a few core-clusters centred around the most highly connected substances enclosed by other substances in outer shells, and a few other well-defined subnetworks.
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| 8. |
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| 9. |
- Johansson, Daniel, et al.
(författare)
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A multivariate approach applied to microarray data for identification of genes with cell cycle-coupled transcription
- 2003
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4811 .- 1367-4803. ; 19:4, s. 467-73
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Tidskriftsartikel (refereegranskat)abstract
- We have analyzed microarray data using a modeling approach based on the multivariate statistical method partial least squares (PLS) regression to identify genes with periodic fluctuations in expression levels coupled to the cell cycle in the budding yeast, Saccharomyces cerevisiae. PLS has major advantages for analyzing microarray data since it can model data sets with large numbers of variables and with few observations.A response model was derived describing the expression profile over time expected for periodically transcribed genes, and was used to identify budding yeast transcripts with similar profiles. PLS was then used to interpret the importance of the variables (genes) for the model, yielding a ranking list of how well the genes fitted the generated model. Application of an appropriate cutoff value, calculated from randomized data, allows the identification of genes whose expression appears to be synchronized with cell cycling. Our approach also provides information about the stage in the cell cycle where their transcription peaks.Three synchronized yeast cell microarray data sets were analyzed, both separately and combined. Cell cycle-coupled periodicity was suggested for 455 of the 6,178 transcripts monitored in the combined data set, at a significance level of 0.5%. Among the candidates, 85% of the known periodic transcripts were included. Analysis of the three data sets separately yielded similar ranking lists, showing that the method is robust.
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| 10. |
- Klau, Gunnar W, et al.
(författare)
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Optimal robust non-unique probe selection using Integer Linear Programming.
- 2004
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Ingår i: Bioinformatics (Oxford, England). - : Oxford University Press (OUP). - 1367-4811 .- 1367-4803 .- 1460-2059. ; 20 Suppl 1
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Tidskriftsartikel (refereegranskat)abstract
- Besides their prevalent use for analyzing gene expression, microarrays are an efficient tool for biological, medical and industrial applications due to their ability to assess the presence or absence of biological agents, the targets, in a sample. Given a collection of genetic sequences of targets one faces the challenge of finding short oligonucleotides, the probes, which allow detection of targets in a sample. Each hybridization experiment determines whether the probe binds to its corresponding sequence in the target. Depending on the problem, the experiments are conducted using either unique or non-unique probes and usually assume that only one target is present in the sample. The problem at hand is to compute a design, i.e. a minimal set of probes that allows to infer the targets in the sample from the result of the hybridization experiment. If we allow to test for more than one target in the sample, the design of the probe set becomes difficult in the case of non-unique probes.Building upon previous work on group testing for microarrays, we describe the first approach to select a minimal probe set for the case of non-unique probes in the presence of a small number of multiple targets in the sample. The approach is based on an ILP formulation and a branch-and-cut algorithm. Our preliminary implementation greatly reduces the number of probes needed while preserving the decoding capabilities.http://www.inf.fu-berlin.de/inst/ag-bio
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