1,721,423 research outputs found
On the Outage Capacity of Orthogonal Space-Time Block Codes Over Multi-Cluster Scattering MIMO Channels
No full textThe multiple cluster scattering MIMO channel is a useful model for pico-cellular MIMO networks. In this paper, space-time coded transmission over such a channel is considered, where the effective channel corresponds to a product of complex Gaussian matrices. An accurate closed-form approximation to the channel outage capacity using orthogonal space-time block codes has been derived. The result is valid for an arbitrary number of clusters of scatterers and an arbitrary antenna configuration. From the analytical and numerical results, we study the relative outage performance between the multi-cluster MIMO channel and the special case of Rayleigh-fading MIMO channe
Kpax3 : Bayesian bi-clustering of large sequence datasets
Full text linkMotivation: Estimation of the hidden population structure is an important step in many genetic studies. Often the aim is also to identify which sequence locations are the most discriminative between groups of samples for a given data partition. Automated discovery of interesting patterns that are present in the data can help to generate new biological hypotheses. Results: We introduce Kpax3, a Bayesian method for bi-clustering multiple sequence alignments. Influence of individual sites will be determined in a supervised manner by using informative prior distributions for the model parameters. Our inference method uses an implementation of both split-merge and Gibbs sampler type MCMC algorithms to traverse the joint posterior of partitions of samples and variables. We use a large Rotavirus sequence dataset to demonstrate the ability of Kpax3 to generate biologically important hypotheses about differential selective pressures across a virus protein.Peer reviewe
From Random Matrix Theory to Coding Theory : Volume of a Metric Ball in Unitary Group
Full text linkVolume estimates of metric balls in manifolds find diverse applications in information and coding theory. In this paper, new results for the volume of a metric ball in unitary group are derived via tools from random matrix theory. The first result is an integral representation of the exact volume, which involves a Toeplitz determinant of Bessel functions. A simple but accurate limiting volume formula is then obtained by invoking Szego's strong limit theorem for large Toeplitz matrices. The derived asymptotic volume formula enables analytical evaluation of some coding-theoretic bounds of unitary codes. In particular, the Gilbert-Varshamov lower bound and the Hamming upper bound on the cardinality as well as the resulting bounds on code rate and minimum distance are derived. Moreover, bounds on the scaling law of code rate are found. Finally, a closed-form bound on the diversity sum relevant to unitary space-time codes is obtained, which was only computed numerically in the literature.Peer reviewe
Bacmeta : simulator for genomic evolution in bacterial metapopulations
Full text linkThe advent of genomic data from densely sampled bacterial populations has created a need for flexible simulators by which models and hypotheses can be efficiently investigated in the light of empirical observations. Bacmeta provides fast stochastic simulation of neutral evolution within a large collection of interconnected bacterial populations with completely adjustable connectivity network. Stochastic events of mutations, recombinations, insertions/deletions, migrations and micro-epidemics can be simulated in discrete non-overlapping generations with a Wright-Fisher model that operates on explicit sequence data of any desired genome length. Each model component, including locus, bacterial strain, population and ultimately the whole metapopulation, is efficiently simulated using C++ objects and detailed metadata from each level can be acquired. The software can be executed in a cluster environment using simple textual input files, enabling, e.g. large-scale simulations and likelihood-free inference. Availability and implementation: Bacmeta is implemented with C++ for Linux, Mac and Windows. It is available at https://bitbucket.org/aleksisipola/bacmeta under the BSD 3-clause license. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.Peer reviewe
Identifying Multiple Potential Metabolic Cycles in Time-Series from Biolog Experiments
No full textBiolog Phenotype Microarray (PM) is a technology allowing simultaneous screening of the metabolic behaviour of bacteria under a large number of different conditions. Bacteria may often undergo several cycles of metabolic activity during a Biolog experiment. We introduce a novel algorithm to identify these metabolic cycles in PM experimental data, thus increasing the potential of PM technology in microbiology. Our method is based on a statistical decomposition of the time-series measurements into a set of growth models. We show that the method is robust to measurement noise and captures accurately the biologically relevant signals from the data. Our implementation is made freely available as a part of an R package for PM data analysis and can be found at www.helsinki.fi/bsg/software/Biolog_Decomposition.Peer reviewe
Mitogenome Sequencing in the Genus Camelus Reveals Evidence for Purifying Selection and Long-term Divergence between Wild and Domestic Bactrian Camels
Full text linkThe genus Camelus is an interesting model to study adaptive evolution in the mitochondrial genome, as the three extant Old World camel species inhabit hot and low-altitude as well as cold and high-altitude deserts. We sequenced 24 camel mitogenomes and combined them with three previously published sequences to study the role of natural selection under different environmental pressure, and to advance our understanding of the evolutionary history of the genus Camelus. We confirmed the heterogeneity of divergence across different components of the electron transport system. Lineage-specific analysis of mitochondrial protein evolution revealed a significant effect of purifying selection in the concatenated protein-coding genes in domestic Bactrian camels. The estimated dN/dSPeer reviewe
Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions.
Full text linkDiscovery of genetic variants underlying bacterial phenotypes and the prediction of phenotypes such as antibiotic resistance are fundamental tasks in bacterial genomics. Genome-wide association study (GWAS) methods have been applied to study these relations, but the plastic nature of bacterial genomes and the clonal structure of bacterial populations creates challenges. We introduce an alignment-free method which finds sets of loci associated with bacterial phenotypes, quantifies the total effect of genetics on the phenotype, and allows accurate phenotype prediction, all within a single computationally scalable joint modeling framework. Genetic variants covering the entire pangenome are compactly represented by extended DNA sequence words known as unitigs, and model fitting is achieved using elastic net penalization, an extension of standard multiple regression. Using an extensive set of state-of-the-art bacterial population genomic data sets, we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. Compared to those of previous approaches, which test each genotype-phenotype association separately for each variant and apply a significance threshold, the variants selected by our joint modeling approach overlap substantially.IMPORTANCE Being able to identify the genetic variants responsible for specific bacterial phenotypes has been the goal of bacterial genetics since its inception and is fundamental to our current level of understanding of bacteria. This identification has been based primarily on painstaking experimentation, but the availability of large data sets of whole genomes with associated phenotype metadata promises to revolutionize this approach, not least for important clinical phenotypes that are not amenable to laboratory analysis. These models of phenotype-genotype association can in the future be used for rapid prediction of clinically important phenotypes such as antibiotic resistance and virulence by rapid-turnaround or point-of-care tests. However, despite much effort being put into adapting genome-wide association study (GWAS) approaches to cope with bacterium-specific problems, such as strong population structure and horizontal gene exchange, current approaches are not yet optimal. We describe a method that advances methodology for both association and generation of portable prediction models
Systematic longitudinal survey of invasive Escherichia coli in England demonstrates a stable population structure only transiently disturbed by the emergence of ST131
Full text link associated with urinary tract infections and bacteremia has been intensively investigated, including recent work focusing on the virulent, globally disseminated, multidrug-resistant lineage ST131. To contextualize ST131 within the broader population associated with disease, we used genomics to analyze a systematic 11-yr hospital-based survey of associated with bacteremia using isolates collected from across England by the British Society for Antimicrobial Chemotherapy and from the Cambridge University Hospitals NHS Foundation Trust. Population dynamics analysis of the most successful lineages identified the emergence of ST131 and ST69 and their establishment as two of the five most common lineages along with ST73, ST95, and ST12. The most frequently identified lineage was ST73. Compared to ST131, ST73 was susceptible to most antibiotics, indicating that multidrug resistance was not the dominant reason for prevalence of lineages in this population. Temporal phylogenetic analysis of the emergence of ST69 and ST131 identified differences in the dynamics of emergence and showed that expansion of ST131 in this population was not driven by sequential emergence of increasingly resistant subclades. We showed that over time, the population was only transiently disturbed by the introduction of new lineages before a new equilibrium was rapidly achieved. Together, these findings suggest that the frequency of lineages in invasive disease is driven by negative frequency-dependent selection occurring outside of the hospital, most probably in the commensal niche, and that drug resistance is not a primary determinant of success in this niche
Patterns of cross‐resistance and collateral sensitivity between clinical antibiotics and natural antimicrobials
Full text linkThis is the final version. Available from Wiley open access via the DOI in this record.Bacteria interact with a multitude of other organisms, many of which produce antimicrobials. Selection for resistance to these antimicrobials has the potential to result in resistance to clinical antibiotics when active compounds target the same bacterial pathways. The possibility of such cross‐resistance between natural antimicrobials and antibiotics has to our knowledge received very little attention. The antimicrobial activity of extracts from seaweeds, known to be prolific producers of antimicrobials, is here tested against Staphylococcus aureus isolates with varied clinical antibiotic resistance profiles. An overall effect consistent with cross‐resistance is demonstrated, with multidrug‐resistant S. aureus strains being on average more resistant to seaweed extracts. This pattern could potentially indicate that evolution of resistance to antimicrobials in the natural environment could lead to resistance against clinical antibiotics. However, patterns of antimicrobial activity of individual seaweed extracts vary considerably and include collateral sensitivity, where increased resistance to a particular antibiotic is associated with decreased resistance to a particular seaweed extract. Our correlation‐based methods allow the identification of antimicrobial extracts bearing most promise for downstream active compound identification and pharmacological testing.Natural Environment Research Council (NERC)Medical Research CouncilAcademy of Finlan
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