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Sökning: L773:0219 7200 OR L773:1757 6334

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1.
  • Addario-Berry, L, et al. (författare)
  • Ancestral maximum likelihood of evolutionary trees is hard
  • 2004
  • Ingår i: Journal of Bioinformatics and Computational Biology. - 0219-7200 .- 1757-6334. ; 2:2, s. 257-271
  • Tidskriftsartikel (refereegranskat)abstract
    • Maximum likelihood (ML) (Felsenstein, 1981) is an increasingly popular optimality criterion for selecting evolutionary trees. Finding optimal ML trees appears to be a very hard computational task - in particular, algorithms and heuristics for ML take longer to run than algorithms and heuristics for maximum parsimony (MP). However, while MP has been known to be NP-complete for over 20 years, no such hardness result has been obtained so far for ML. In this work we make a first step in this direction by proving that ancestral maximum likelihood (AML) is NP-complete. The input to this problem is a set of aligned sequences of equal length and the goal is to find a tree and an assignment of ancestral sequences for all of that tree's internal vertices such that the likelihood of generating both the ancestral and contemporary sequences is maximized. Our NP-hardness proof follows that for MP given in (Day, Johnson and Sankoff, 1986) in that we use the same reduction from VERTEX COVER; however, the proof of correctness for this reduction relative to AML is different and substantially more involved.
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2.
  • Akhtar, Malik N., et al. (författare)
  • Identification of best indicators of peptide-spectrum match using a permutation resampling approach
  • 2014
  • Ingår i: Journal of Bioinformatics and Computational Biology. - 0219-7200 .- 1757-6334. ; 12:5, s. 1440001-
  • Tidskriftsartikel (refereegranskat)abstract
    • Various indicators of observed-theoretical spectrum matches were compared and the resulting statistical significance was characterized using permutation resampling. Novel decoy databases built by resampling the terminal positions of peptide sequences were evaluated to identify the conditions for accurate computation of peptide match significance levels. The methodology was tested on real and manually curated tandem mass spectra from peptides across a wide range of sizes. Spectra match indicators from complementary database search programs were pro filed and optimal indicators were identified. The combination of the optimal indicator and permuted decoy databases improved the calculation of the peptide match significance compared to the approaches currently implemented in the database search programs that rely on distributional assumptions. Permutation tests using p-values obtained from software-dependent matching scores and E-values outperformed permutation tests using all other indicators. The higher overlap in matches between the database search programs when using end permutation compared to existing approaches con firmed the superiority of the end permutation method to identify peptides. The combination of effective match indicators and the end permutation method is recommended for accurate detection of peptides.
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3.
  • Akkuratov, Evgeny E., et al. (författare)
  • Neanderthal and Denisovan ancestry in Papuans : A functional study
  • 2018
  • Ingår i: Journal of Bioinformatics and Computational Biology. - : Imperial College Press. - 0219-7200 .- 1757-6334. ; 16:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Sequencing of complete nuclear genomes of Neanderthal and Denisovan stimulated studies about their relationship with modern humans demonstrating, in particular, that DNA alleles from both Neanderthal and Denisovan genomes are present in genomes of modern humans. The Papuan genome is a unique object because it contains both Neanderthal and Denisovan alleles. Here, we have shown that the Papuan genomes contain different gene functional groups inherited from each of the ancient people. The Papuan genomes demonstrate a relative prevalence of Neanderthal alleles in genes responsible for the regulation of transcription and neurogenesis. The enrichment of specific functional groups with Denisovan alleles is less pronounced; these groups are responsible for bone and tissue remodeling. This analysis shows that introgression of alleles from Neanderthals and Denisovans to Papuans occurred independently and retention of these alleles may carry specific adaptive advantages.
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4.
  • Deo, Ameya, et al. (författare)
  • How to Choose a Normalization Strategy for miRNA Quantitative Real-Time (qPCR) Arrays
  • 2011
  • Ingår i: Journal of Bioinformatics and Computational Biology. - : Imperial College Press. - 0219-7200 .- 1757-6334. ; 9:6, s. 795-812
  • Tidskriftsartikel (refereegranskat)abstract
    • Low-density arrays for quantitative real-time PCR (qPCR) are increasingly being used as an experimental technique for miRNA expression profiling. As with gene expression profiling using microarrays, data from such experiments needs effective analysis methods to produce reliable and high-quality results. In the pre-processing of the data, one crucial analysis step is normalization, which aims to reduce measurement errors and technical variability among arrays that might have arisen during the execution of the experiments. However, there are currently a number of different approaches to choose among and an unsuitable applied method may induce misleading effects, which could affect the subsequent analysis steps and thereby any conclusions drawn from the results. The choice of normalization method is hence an important issue to consider. In this study we present the comparison of a number of data-driven normalization methods for TaqMan low-density arrays for qPCR and different descriptive statistical techniques that can facilitate the choice of normalization method. The performance of the normalization methods was assessed and compared against each other as well as against standard normalization using endogenous controls. The results clearly show that the data-driven methods reduce variation and represent robust alternatives to using endogenous controls.
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5.
  • Gamalielsson, Jonas, et al. (författare)
  • Gene Ontology-based Semantic Alignment of Biological Pathways by Evolutionary Search
  • 2008
  • Ingår i: Journal of Bioinformatics and Computational Biology. - : World Scientific Publishing. - 0219-7200 .- 1757-6334. ; 6:4, s. 825-842
  • Tidskriftsartikel (refereegranskat)abstract
    • A large number of biological pathways have been elucidated recently, and there is a need for methods to analyze these pathways. One class of methods compares pathways semantically in order to discover parts that are evolutionarily conserved between species or to discover intraspecies similarities. Such methods usually require that the topologies of the pathways being compared are known, i.e. that a query pathway is being aligned to a model pathway. However, sometimes the query only consists of an unordered set of gene products. Previous methods for mapping sets of gene products onto known pathways have not been based on semantic comparison of gene products using ontologies or other abstraction hierarchies. Therefore, we here propose an approach that uses a similarity function defined in Gene Ontology (GO) terms to find semantic alignments when comparing paths in biological pathways where the nodes are gene products. A known pathway graph is used as a model, and an evolutionary algorithm (EA) is used to evolve putative paths from a set of experimentally determined gene products. The method uses a measure of GO term similarity to calculate a match score between gene products, and the fitness value of each candidate path alignment is derived from these match scores. A statistical test is used to assess the significance of evolved alignments. The performance of the method has been tested using regulatory pathways for S. cerevisiae and M. musculus.
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6.
  • Gennemark, Peter, 1974, et al. (författare)
  • ODEion- a software module for structural identification of ordinary differential equations
  • 2014
  • Ingår i: Journal of Bioinformatics and Computational Biology. - 0219-7200 .- 1757-6334. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • In the systems biology field, algorithms for structural identification of ordinary differential equations (ODEs) have mainly focused on fixed model spaces like S-systems and/or on methods that require sufficiently good data so that derivatives can be accurately estimated. There is therefore a lack of methods and software that can handle more general models and realistic data. We present ODEion, a software module for structural identification of ODEs. Main characteristic features of the software are: • The model space is defined by arbitrary user-defined functions that can be nonlinear in both variables and parameters, such as for example chemical rate reactions. • ODEion implements computationally efficient algorithms that have been shown to efficiently handle sparse and noisy data. It can run a range of realistic problems that previously required a supercomputer. • ODEion is easy to use and provides SBML output. We describe the mathematical problem, the ODEion system itself, and provide several examples of how the system can be used. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219720013500157
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7.
  • Huang, Hui-Ling, et al. (författare)
  • ThermalProGAN : a sequence-based thermally stable protein generator trained using unpaired data
  • 2023
  • Ingår i: Journal of Bioinformatics and Computational Biology. - : World Scientific. - 0219-7200 .- 1757-6334. ; 21:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Motivation: The synthesis of proteins with novel desired properties is challenging but sought after by the industry and academia. The dominating approach is based on trial-and-error inducing point mutations, assisted by structural information or predictive models built with paired data that are difficult to collect. This study proposes a sequence-based unpaired-sample of novel protein inventor (SUNI) to build ThermalProGAN for generating thermally stable proteins based on sequence information.Results: The ThermalProGAN can strongly mutate the input sequence with a median number of 32 residues. A known normal protein, 1RG0, was used to generate a thermally stable form by mutating 51 residues. After superimposing the two structures, high similarity is shown, indicating that the basic function would be conserved. Eighty four molecular dynamics simulation results of 1RG0 and the COVID-19 vaccine candidates with a total simulation time of 840ns indicate that the thermal stability increased.Conclusion: This proof of concept demonstrated that transfer of a desired protein property from one set of proteins is feasible.
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8.
  • Kuhn, C., et al. (författare)
  • Modeling yeast osmoadaptation at different levels of resolution
  • 2013
  • Ingår i: Journal of Bioinformatics and Computational Biology. - : World Scientific Pub Co Pte Ltd. - 0219-7200 .- 1757-6334. ; 11:2
  • Tidskriftsartikel (refereegranskat)abstract
    • We review the proposed mathematical models of the response to osmotic stress in yeast. These models mainly differ in the choice of mathematical representation (e. g. Bayesian networks, ordinary differential equations, or rule-based models), the extent to which the modeling is data-driven, and predictability. The overview exemplifies how one biological system can be modeled with various modeling techniques and at different levels of resolution, and how the choice typically is based on the amount and quality of available data, prior information of the system, and the research question in focus. As a natural part of the overview, we discuss requirements, advantages, and limitations of the different modeling approaches.
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9.
  • Kühn, Clemens, et al. (författare)
  • Modeling yeast osmoadaptation at different levels of resolution
  • 2013
  • Ingår i: Journal of Bioinformatics and Computational Biology. - 0219-7200 .- 1757-6334. ; 11:2, s. 1330001-
  • Forskningsöversikt (refereegranskat)abstract
    • We review the proposed mathematical models of the response to osmotic stress in yeast. These models mainly differ in the choice of mathematical representation (e. g. Bayesian networks, ordinary differential equations, or rule-based models), the extent to which the modeling is data-driven, and predictability. The overview exemplifies how one biological system can be modeled with various modeling techniques and at different levels of resolution, and how the choice typically is based on the amount and quality of available data, prior information of the system, and the research question in focus. As a natural part of the overview, we discuss requirements, advantages, and limitations of the different modeling approaches.
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10.
  • Ma, Zhanyu, 1982-, et al. (författare)
  • A variational bayes beta mixture model for feature selection in DNA methylation studies
  • 2013
  • Ingår i: Journal of Bioinformatics and Computational Biology. - 0219-7200 .- 1757-6334. ; 11:4, s. 1350005-
  • Tidskriftsartikel (refereegranskat)abstract
    • An increasing number of studies are using beadarrays to measure DNA methylation on a genome-wide basis. The purpose is to identify novel biomarkers in a wide range of complex genetic diseases including cancer. A common difficulty encountered in these studies is distinguishing true biomarkers from false positives. While statistical methods aimed at improving the feature selection step have been developed for gene expression, relatively few methods have been adapted to DNA methylation data, which is naturally beta-distributed. Here we explore and propose an innovative application of a recently developed variational Bayesian beta-mixture model (VBBMM) to the feature selection problem in the context of DNA methylation data generated from a highly popular beadarray technology. We demonstrate that VBBMM offers significant improvements in inference and feature selection in this type of data compared to an Expectation-Maximization (EM) algorithm, at a significantly reduced computational cost. We further demonstrate the added value of VBBMM as a feature selection and prioritization step in the context of identifying prognostic markers in breast cancer. A variational Bayesian approach to feature selection of DNA methylation profiles should thus be of value to any study undergoing large-scale DNA methylation profiling in search of novel biomarkers.
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