The Experts below are selected from a list of 31395 Experts worldwide ranked by ideXlab platform
Sean R Eddy - One of the best experts on this subject based on the ideXlab platform.
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estimating the power of sequence Covariation for detecting conserved rna structure
Bioinformatics, 2020Co-Authors: Elena Rivas, Jody Clements, Sean R EddyAbstract:: Pairwise sequence Covariations are a signal of conserved RNA secondary structure. We describe a method for distinguishing when lack of Covariation signal can be taken as evidence against a conserved RNA structure, as opposed to when a sequence alignment merely has insufficient variation to detect Covariations. We find that alignments for several long non-coding RNAs previously shown to lack Covariation support do have adequate Covariation detection power, providing additional evidence against their proposed conserved structures. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online and from the R-scape web server eddylab.org/R-scape, with a link to download the source code. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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response to tavares et al Covariation analysis with improved parameters reveals conservation in lncrna structures
bioRxiv, 2020Co-Authors: Elena Rivas, Sean R EddyAbstract:Abstract Tavares’ conclusions depend on an assumption that the statistic they use (RAFS) is an appropriate measure of RNA base pair Covariation, but RAFS was not designed to measure Covariation alone. RAFS detects positive signals in common patterns of primary sequence conservation in absence of any Covariation. To illustrate the severity of the problem, we show that Tavares’ analysis reports “significantly covarying base pairs” in 100% identical sequence alignments with no variation or Covariation. We use Tavares’ sequence alignment of HOTAIR domain 1 as an example to show that the base pairs they identify as significantly covarying actually arise from primary sequence conservation patterns. Their analysis still reports similar numbers of “significant covarying” base pairs in a negative control in which we permute residues in independent alignment columns to destroy Covariation. There remains no significant Covariation support for evolutionarily conserved RNA structure in the HOTAIR lncRNA or other lncRNA structures and alignments we have analyzed.
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Estimating the power of sequence Covariation for detecting conserved RNA structure.
Bioinformatics, 2020Co-Authors: Elena Rivas, Jody Clements, Sean R EddyAbstract:Pairwise sequence Covariations are a signal of conserved RNA secondary structure. We describe a method for distinguishing when lack of Covariation signal can be taken as evidence against a conserved RNA structure, as opposed to when a sequence alignment merely has insufficient variation to detect Covariations. We find that alignments for several long non-coding RNAs previously shown to lack Covariation support do have adequate Covariation detection power, providing additional evidence against their proposed conserved structures. AVAILABILITY AND IMPLEMENTATION The R-scape web server is at eddylab.org/R-scape, with a link to download the source code. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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estimating the power of sequence Covariation for detecting conserved rna structure
bioRxiv, 2019Co-Authors: Elena Rivas, Jody Clements, Sean R EddyAbstract:Abstract Pairwise sequence Covariations are a signal of conserved RNA secondary structure. We describe a method for distinguishing when lack of Covariation signal can be taken as evidence against a conserved RNA structure, as opposed to when a sequence alignment merely has insufficient variation to detect Covariations. We find that alignments for several long noncoding RNAs previously shown to lack Covariation support do have adequate Covariation detection power, providing additional evidence against their proposed conserved structures.
Gabriel Marroig - One of the best experts on this subject based on the ideXlab platform.
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the evolution of phenotypic integration how directional selection reshapes Covariation in mice
Evolution, 2017Co-Authors: Anna Penna, Diogo Melo, Sandra Bernardi, Maria Ines Oyarzabal, Gabriel MarroigAbstract:Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, Covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate Covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of Covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of Covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available Covariation and suggests a much more complex view of how populations respond to selection. This article is protected by copyright. All rights reserved
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The evolution of phenotypic integration: How directional selection reshapes Covariation in mice.
Evolution, 2017Co-Authors: Anna Penna, Diogo Melo, Sandra Bernardi, Maria Ines Oyarzabal, Gabriel MarroigAbstract:Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, Covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate Covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of Covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of Covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available Covariation and suggests a much more complex view of how populations respond to selection.
Christopher Small - One of the best experts on this subject based on the ideXlab platform.
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comparative analysis of urban reflectance and surface temperature
Remote Sensing of Environment, 2006Co-Authors: Christopher SmallAbstract:Abstract Urban environmental conditions are strongly dependent on the biophysical properties and radiant thermal field of the land cover elements in the urban mosaic. Observations of urban reflectance and surface temperature provide valuable constraints on the physical properties that are determinants of mass and energy fluxes in the urban environment. Consistencies in the Covariation of surface temperature with reflectance properties can be parameterized to represent characteristics of the surface energy flux associated with different land covers and physical conditions. Linear mixture models can accurately represent Landsat ETM+ reflectances as fractions of generic spectral endmembers that correspond to land surface materials with distinct physical properties. Modeling heterogeneous land cover as mixtures of rock and/or soil Substrate, Vegetation and non-reflective Dark surface (SVD) generic endmembers makes it possible to quantify the dependence of aggregate surface temperature on the relative abundance of each physical component of the land cover, thereby distinguishing the effects of vegetation abundance, soil exposure, albedo and shadowing. Comparing these Covariations in a wide variety of urban settings and physical environments provides a more robust indication of the global variability in these parameter spaces than could be inferred from a single study area. A comparative analysis of 24 urban areas and their non-urban peripheries illustrates the variability in the urban thermal fields and its dependence on biophysical land surface components. Contrary to expectation, moderate resolution intra-urban variations in surface temperature are generally as large as regional surface heat island signatures in these urban areas. Many of the non-temperate urban areas did not have surface heat island signatures at all. However, the multivariate distributions of surface temperature and generic endmember fractions reveal consistent patterns of thermal fraction Covariation resulting from land cover characteristics. The Thermal-Vegetation (TV) fraction space illustrates the considerable variability in the well-known inverse correlation between surface temperature and vegetation fraction at moderate (
Aaron W Lukaszewski - One of the best experts on this subject based on the ideXlab platform.
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testing an adaptationist theory of trait Covariation relative bargaining power as a common calibrator of an interpersonal syndrome
European Journal of Personality, 2013Co-Authors: Aaron W LukaszewskiAbstract:This article provides the first test of an adaptationist 'common calibration' theory to explain the origins of trait Covariation, which holds that (i) personality traits are often facultatively calibrated in response to cues that ancestrally predicted the reproductive payoffs of different trait levels and (ii) distinct traits that are calibrated on the basis of common input cues will exhibit consistent patterns of Covariation. This theory is applied to explain the Covariation within a 'personality syndrome' encompassing various interpersonal trait dimensions (e.g. extraversion, emotionality and attachment styles). Specifically, it is hypothesized that these traits are inter-correlated because each is calibrated in response to relative bargaining power (RBP)—a joint function of one's ability to benefit others and harm others. Path analyses from a correlational study compellingly supported this theoretical model: Objective and self-perceived measures of RBP-enhancing phenotypic features (physical attractiveness and physical strength) influenced an internal regulatory variable indexing RBP (i.e. self-perceived RBP), which in turn had robust effects on each of the focal personality traits. Moreover, in support of the theory's core postulate, controlling for self- perceived RBP greatly reduced the Covariation within the interpersonal syndrome. These novel findings illustrate the promise of an evolutionary psychological approach to elucidating trait Covariation. Copyright © 2013 John Wiley & Sons, Ltd.
Anna Penna - One of the best experts on this subject based on the ideXlab platform.
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the evolution of phenotypic integration how directional selection reshapes Covariation in mice
Evolution, 2017Co-Authors: Anna Penna, Diogo Melo, Sandra Bernardi, Maria Ines Oyarzabal, Gabriel MarroigAbstract:Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, Covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate Covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of Covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of Covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available Covariation and suggests a much more complex view of how populations respond to selection. This article is protected by copyright. All rights reserved
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The evolution of phenotypic integration: How directional selection reshapes Covariation in mice.
Evolution, 2017Co-Authors: Anna Penna, Diogo Melo, Sandra Bernardi, Maria Ines Oyarzabal, Gabriel MarroigAbstract:Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, Covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate Covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of Covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of Covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available Covariation and suggests a much more complex view of how populations respond to selection.
