scholarly journals Viral Taxonomy Derived From Evolutionary Genome Relationships

2018 ◽  
Author(s):  
Tyler J. Dougan ◽  
Stephen R. Quake
Keyword(s):  
Information Theory ◽  
Genetic Relationships ◽  
Computational Cost ◽  
Pairwise Comparisons ◽  
Genome Alignment ◽  
Evolutionary Genetic ◽  
Novel Virus ◽  
Global Classification ◽  
Ncbi Blast

AbstractWe describe a new genome alignment-based model for classification of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of k-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified.

scholarly journals Global classification of NPGCs

2014 ◽  
Vol 13 (12) ◽  
pp. 888-888
Author(s):  
Sarah Crunkhorn
Keyword(s):  
Global Classification

scholarly journals An inshore–offshore sorting system revealed from global classification of ocean litter

2021 ◽  
Vol 4 (6) ◽  
pp. 484-493
Author(s):  
Carmen Morales-Caselles ◽  
Josué Viejo ◽  
Elisa Martí ◽  
Daniel González-Fernández ◽  
Hannah Pragnell-Raasch ◽  
...  
Keyword(s):  
Global Classification ◽  
Sorting System

Toward a global classification of mast cell activation diseases

2011 ◽  
Vol 127 (5) ◽  
pp. 1311 ◽  
Author(s):  
Gerhard J. Molderings ◽  
Jürgen Homann ◽  
Martin Raithel ◽  
Thomas Frieling
Keyword(s):  
Mast Cell ◽  
Cell Activation ◽  
Mast Cell Activation ◽  
Global Classification

Phenotypic and Genotypic Associations Between Migraine and Lipoprotein Subtractions

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012919
Author(s):  
Yanjun Guo ◽  
Iyas Daghlas ◽  
Padhraig Gormley ◽  
Franco Giulianini ◽  
Paul M Ridker ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Genetic Relationships ◽  
Meta Analysis ◽  
European Ancestry ◽  
Health Study ◽  
Lipoprotein Subfractions ◽  
Genetic Components ◽  
The Uk ◽  
Summary Data

Background and Objective:To evaluate phenotypic and genetic relationships between migraine and lipoprotein subfractions.Methods:We evaluated phenotypic associations between migraine and 19 lipoprotein subfractions measures in the Women’s Genome Health Study (WGHS, N=22,788). We then investigated genetic relationships between these traits using summary statistics from the International Headache Genetics Consortium (IHGC) for migraine (Ncase=54,552, Ncontrol=297,970) and combined summary data for lipoprotein subfractions (N up to 47,713).Results:There was a significant phenotypic association (odds ratio=1.27 [95% confidence interval:1.12-1.44]) and a significant genetic correlation at 0.18 (P=0.001) between migraine and triglyceride-rich lipoproteins (TRLP) concentration but not for LDL or HDL subfractions. Mendelian randomization (MR) estimates were largely null implying that pleiotropy rather than causality underlies the genetic correlation between migraine and lipoprotein subfractions. Pleiotropy was further supported in cross-trait meta-analysis revealing significant shared signals at four loci (chr2p21 harboring THADA, chr5q13.3 harboring HMGCR, chr6q22.31 harboring HEY2, and chr7q11.23 harboring MLXIPL) between migraine and lipoprotein subfractions. Three of these loci were replicated for migraine (P<0.05) in a smaller sample from the UK Biobank. The shared signal at chr5q13.3 colocalized with expression of HMGCR, ANKDD1B, and COL4A3BP in multiple tissues.Conclusions:The current study supports the association between certain lipoprotein subfractions, especially for TRLP, and migraine in populations of European ancestry. The corresponding shared genetic components may be help identify potential targets for future migraine therapeutics.Classification of Evidence:This study provides Class I evidence that migraine is significantly associated with some lipoprotein subfractions.

Classification of cultivated barley (Hordeum vulgare). 1. Historical aspects, and phenetic character analysis of some characters by information theory and by spatial autocorrelation

1986 ◽  
Vol 64 (11) ◽  
pp. 2769-2773
Author(s):  
Bernard B. Baum
Keyword(s):  
Information Theory ◽  
Hordeum Vulgare ◽  
Spatial Autocorrelation ◽  
Theory Model ◽  
Kernel Weight ◽  
Hordeum Vulgare L ◽  
Department Of Agriculture ◽  
Character Analysis ◽  
Barley Cultivars

A brief historical sketch of the classification of barley (Hordeum vulgare L.) cultivars is presented along with reference to key reviews on this subject. Characters, utilized in the comprehensive study on the barley cultivars of North America by Aberg and Wiebe (U.S. Department of Agriculture Technical Bulletin 942), were subjected to a series of phenetic character analyses using an information theory model and a spatial autocorrelation model. The ranking of the 48 characters in order of their importance (for classification and identification purposes) from the character analysis by information theory was compared with the previous rating of characters made by Aberg and Wiebe and was found to differ significantly. Numerous trials of character analysis by spatial autocorrelation using various Minkowski distances, setting various values among three parameters, never yielded results comparable with those obtained by Aberg and Wiebe. Among those trials, a few combinations of values for the three parameters (X, Y, and Z) yielded results comparable with those obtained with character analysis by information theory. Those same combinations of values were found by Estabrook and Gates (Taxon, 33: 13–25) in their study of Banisteriopsis in 1984, where they also developed the method of character analysis by spatial autocorrelation. Kernel weight was found to be the most important character.

scholarly journals Assessment of genetic diversity in Indian Barnyard millet (Echinochloa spp. complex) using morphological and molecular markers

2016 ◽  
Vol 8 (3) ◽  
pp. 1643-1648 ◽  
Author(s):  
M. P. Moharil ◽  
Dipti Gawai ◽  
N. Dikshit ◽  
M.S. Dudhare ◽  
P. V. Jadhav
Keyword(s):  
Genetic Diversity ◽  
Molecular Markers ◽  
Genetic Improvement ◽  
Molecular Diversity ◽  
Genetic Relationships ◽  
Barnyard Millet ◽  
Clear Cut ◽  
Cultivated Species ◽  
High Degree

In the present study, morphological and molecular markers (RAPD primers) were used to analyze the genetic diversity and genetic relationships among 21 accessions of Echinochloa spp. complex comprising the wild and cultivated species collected from Melghat and adjoining regions of Vidarbha, Maharashtra. The availability of diverse genetic resources is a prerequisite for genetic improvement of any crop including barnyard millet. A high degree of molecular diversity among the landraces was detected. Among the 21 genotypes, two major groups (A and B) were formed, at 67.28 % similarity, which clearly encompasses 15 accessions of E. frumentacea and 6 accessions of E. colona. Higher similarity was observed in accessions of E. frumentacea. The accessions IC 597322 and IC 597323 also IC 597302 and IC 597304 showed more than 94% similarity among themselves. The classification of genetic diversity has enabled clear-cut grouping of barnyard millet accessions into two morphological races (E. frumentacea and E. colona).

scholarly journals A CAUSAL HIERARCHICAL MARKOV FRAMEWORK FOR THE CLASSIFICATION OF MULTIRESOLUTION AND MULTISENSOR REMOTE SENSING IMAGES

2020 ◽  
Vol V-3-2020 ◽  
pp. 269-277
Author(s):  
A. Montaldo ◽  
L. Fronda ◽  
I. Hedhli ◽  
G. Moser ◽  
S. B. Serpico ◽  
...  
Keyword(s):  
High Resolution ◽  
Markov Chain Model ◽  
Computational Cost ◽  
Order Relation ◽  
Boosted Regression Trees ◽  
Chain Model ◽  
Remotely Sensed Data ◽  
Space Filling Curve ◽  
Very High

Abstract. In this paper, a multiscale Markov framework is proposed in order to address the problem of the classification of multiresolution and multisensor remotely sensed data. The proposed framework makes use of a quadtree to model the interactions across different spatial resolutions and a Markov model with respect to a generic total order relation to deal with contextual information at each scale in order to favor applicability to very high resolution imagery. The methodological properties of the proposed hierarchical framework are investigated. Firstly, we prove the causality of the overall proposed model, a particularly advantageous property in terms of computational cost of the inference. Secondly, we prove the expression of the marginal posterior mode criterion for inference on the proposed framework. Within this framework, a specific algorithm is formulated by defining, within each layer of the quadtree, a Markov chain model with respect to a pixel scan that combines both a zig-zag trajectory and a Hilbert space-filling curve. Data collected by distinct sensors at the same spatial resolution are fused through gradient boosted regression trees. The developed algorithm was experimentally validated with two very high resolution datasets including multispectral, panchromatic and radar satellite images. The experimental results confirm the effectiveness of the proposed algorithm as compared to previous techniques based on alternate approaches to multiresolution fusion.

scholarly journals Watching a Small Portion could be as Good as Watching All: Towards Efficient Video Classification

2018 ◽  
Author(s):  
Hehe Fan ◽  
Zhongwen Xu ◽  
Linchao Zhu ◽  
Chenggang Yan ◽  
Jianjun Ge ◽  
...  
Keyword(s):  
Large Scale ◽  
Sampling Rate ◽  
Computational Cost ◽  
Confidence Score ◽  
Video Content ◽  
Video Classification ◽  
Video Frames ◽  
Similar Accuracy ◽  
Efficient Video

We aim to significantly reduce the computational cost for classification of temporally untrimmed videos while retaining similar accuracy. Existing video classification methods sample frames with a predefined frequency over entire video. Differently, we propose an end-to-end deep reinforcement approach which enables an agent to classify videos by watching a very small portion of frames like what we do. We make two main contributions. First, information is not equally distributed in video frames along time. An agent needs to watch more carefully when a clip is informative and skip the frames if they are redundant or irrelevant. The proposed approach enables the agent to adapt sampling rate to video content and skip most of the frames without the loss of information. Second, in order to have a confident decision, the number of frames that should be watched by an agent varies greatly from one video to another. We incorporate an adaptive stop network to measure confidence score and generate timely trigger to stop the agent watching videos, which improves efficiency without loss of accuracy. Our approach reduces the computational cost significantly for the large-scale YouTube-8M dataset, while the accuracy remains the same.

scholarly journals Cultural Issues Related to ICD-11 Mental, Behavioural and Neurodevelopmental Disorders

10.17816/cp67 ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 7-15
Author(s):  
Pratap Sharan ◽  
Gagan Hans
Keyword(s):  
Neurodevelopmental Disorders ◽  
Cultural Issues ◽  
Cultural Variations ◽  
Cultural Challenges ◽  
Global Classification ◽  
Specific Disorders ◽  
Successive Generations ◽  
Classificatory System

The challenge of producing a classificatory system that is truly representative of different regions and cultural variations is difficult. This can be conceptualized as an ongoing process, achievable by constant commitment in this regard from various stakeholders over successive generations of the classificatory systems. The objective of this article is to conduct a qualitative review of the process and outcome of the efforts that resulted in the ICD-11 classification of mental, behavioural and neurodevelopmental disorders becoming a global classification. The ICD-11 represents an important, albeit iterative, advance in the classification of mental, behavioural and neurodevelopmental disorders. Significant changes have been incorporated in this regard, such as the introduction of new, culturally-relevant categories, modifications of the diagnostic guidelines, based on culturally informed data and the incorporation of culture-related features for specific disorders. Notwithstanding, there are still certain significant shortcomings and areas for further improvement and research. Some of the key limitations of ICD-11 relate to the paucity of research on the role of culture in the pathogenesis of illnesses. To ensure a classificatory system that is fair, reliable and culturally useful, there is a need to generate empirical evidence on diversity in the form of illnesses, as well as mechanisms that explain these in all the regions of the world. In this review, we try to delineate the various cultural challenges and their influences in the formulation of ICD-11, along with potential shortcomings and areas in need of more improvement and research in this regard.

Automatic Texture Based Classification of the Dynamics of One-Dimensional Binary Cellular Automata

2019 ◽  
Vol 8 (4) ◽  
pp. 41-61
Author(s):  
Marcelo Arbori Nogueira ◽  
Pedro Paulo Balbi de Oliveira
Keyword(s):  
Cellular Automata ◽  
Dynamic Behavior ◽  
Temporal Evolution ◽  
Computational Cost ◽  
Great Variability ◽  
Texture Descriptor ◽  
One Dimensional ◽  
Binary Images ◽  
Elementary Cellular Automata

Cellular automata present great variability in their temporal evolutions due to the number of rules and initial configurations. The possibility of automatically classifying its dynamic behavior would be of great value when studying properties of its dynamics. By counting on elementary cellular automata, and considering its temporal evolution as binary images, the authors created a texture descriptor of the images - based on the neighborhood configurations of the cells in temporal evolutions - so that it could be associated to each dynamic behavior class, following the scheme of Wolfram's classic classification. It was then possible to predict the class of rules of a temporal evolution of an elementary rule in a more effective way than others in the literature in terms of precision and computational cost. By applying the classifier to the larger neighborhood space containing 4 cells, accuracy decreased to just over 70%. However, the classifier is still able to provide some information about the dynamics of an unknown larger space with reduced computational cost.

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