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Articles 1 - 7 of 7
Full-Text Articles in Genetics and Genomics
Haplotype Network Branch Diversity, A New Metric Combining Genetic And Topological Diversity To Compare The Complexity Of Haplotype Networks, Eric Garcia, Daniel Wright, Remy Gatkins, May B. Roberts, Hudson T. Pinheiro, Eva Salas, Jei-Ying Chen, Jacob R. Winnikoff, Giacomo Bernardi
Haplotype Network Branch Diversity, A New Metric Combining Genetic And Topological Diversity To Compare The Complexity Of Haplotype Networks, Eric Garcia, Daniel Wright, Remy Gatkins, May B. Roberts, Hudson T. Pinheiro, Eva Salas, Jei-Ying Chen, Jacob R. Winnikoff, Giacomo Bernardi
Biological Sciences Faculty Publications
A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore other network properties. Here, we present a new metric, haplotype network branch diversity (HBd), as an easy way to quantifiably compare haplotype network complexity. Our metric builds off the logic of combining genetic and topological diversity to estimate complexity previously used by the published metric haplotype network diversity (HNd). However, unlike HNd which uses a combination of network …
Consensus Guidelines For Advancing Coral Holobiont Genome And Specimen Voucher Deposition, Christian R. Voolstra, Kate M. Quigley, Sarah W. Davies, John Everett Parkinson, Raquel S. Peixoto, Manuel Aranda, Andrew C. Baker, Adam R. Barno, Daniel J. Barshis, Francesca Benzoni, Victor Bonito, David G. Bourne, Carol Buitrago-López, Tom C.L. Bridge, Cheong Xin Chan, David J. Combosch, Jamie Craggs, Jörg C. Frommlet, Santiago Herrera, Andrea M. Quattrini, Till Röthig, James D. Reimer, Esther Rubio-Portillo, David J. Suggett, Helena Villela, Maren Ziegler, Michael Sweet
Consensus Guidelines For Advancing Coral Holobiont Genome And Specimen Voucher Deposition, Christian R. Voolstra, Kate M. Quigley, Sarah W. Davies, John Everett Parkinson, Raquel S. Peixoto, Manuel Aranda, Andrew C. Baker, Adam R. Barno, Daniel J. Barshis, Francesca Benzoni, Victor Bonito, David G. Bourne, Carol Buitrago-López, Tom C.L. Bridge, Cheong Xin Chan, David J. Combosch, Jamie Craggs, Jörg C. Frommlet, Santiago Herrera, Andrea M. Quattrini, Till Röthig, James D. Reimer, Esther Rubio-Portillo, David J. Suggett, Helena Villela, Maren Ziegler, Michael Sweet
Biological Sciences Faculty Publications
Coral research is being ushered into the genomic era. To fully capitalize on the potential discoveries from this genomic revolution, the rapidly increasing number of high-quality genomes requires effective pairing with rigorous taxonomic characterizations of specimens and the contextualization of their ecological relevance. However, to date there is no formal framework that genomicists, taxonomists, and coral scientists can collectively use to systematically acquire and link these data. Spurred by the recently announced “Coral symbiosis sensitivity to environmental change hub” under the “Aquatic Symbiosis Genomics Project” - a collaboration between the Wellcome Sanger Institute and the Gordon and Betty Moore Foundation …
Complete Genome Sequence Of Rickettsia Parkeri Strain Black Gap, Sandor E. Karpathy, Christopher D. Paddock, Stephanie L. Grizzard, Dhwani Batra, Lori A. Rowe, David T. Gauthier
Complete Genome Sequence Of Rickettsia Parkeri Strain Black Gap, Sandor E. Karpathy, Christopher D. Paddock, Stephanie L. Grizzard, Dhwani Batra, Lori A. Rowe, David T. Gauthier
Biological Sciences Faculty Publications
A unique genotype of Rickettsia parkeri, designated R. parkeri strain Black Gap, has thus far been associated exclusively with the North American tick, Dermacentor parumapertus. The compete genome consists of a single circular chromosome with 1,329,522 bp and a G+C content of 32.5%.
Microbiomes Of Blood-Feeding Arthropods: Genes Coding For Essential Nutrients And Relation To Vector Fitness And Pathogenic Infections. A Review, Daniel E. Sonenshine, Philip E. Stewart
Microbiomes Of Blood-Feeding Arthropods: Genes Coding For Essential Nutrients And Relation To Vector Fitness And Pathogenic Infections. A Review, Daniel E. Sonenshine, Philip E. Stewart
Biological Sciences Faculty Publications
Blood-feeding arthropods support a diverse array of symbiotic microbes, some of which facilitate host growth and development whereas others are detrimental to vector-borne pathogens. We found a common core constituency among the microbiota of 16 different arthropod blood-sucking disease vectors, including Bacillaceae, Rickettsiaceae, Anaplasmataceae, Sphingomonadaceae, Enterobacteriaceae, Pseudomonadaceae, Moraxellaceae and Staphylococcaceae. By comparing 21 genomes of common bacterial symbionts in blood-feeding vectors versus non-blooding insects, we found that certain enteric bacteria benefit their hosts by upregulating numerous genes coding for essential nutrients. Bacteria of blood-sucking vectors expressed significantly more genes (p < 0.001) coding for these essential nutrients than those of non-blooding insects. Moreover, compared to endosymbionts, the genomes of enteric bacteria also contained significantly more genes (p < 0.001) that code for the synthesis of essential amino acids and proteins that detoxify reactive oxygen species. In contrast, microbes in non-blood-feeding insects expressed few gene families coding for these nutrient categories. We also discuss specific midgut bacteria essential for the normal development of pathogens (e.g., Leishmania) versus …
Fmri Feature Extraction Model For Adhd Classification Using Convolutional Neural Network, Senuri De Silva, Sanuwani Udara Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, Sampath Jayarathna
Fmri Feature Extraction Model For Adhd Classification Using Convolutional Neural Network, Senuri De Silva, Sanuwani Udara Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, Sampath Jayarathna
Computer Science Faculty Publications
Biomedical intelligence provides a predictive mechanism for the automatic diagnosis of diseases and disorders. With the advancements of computational biology, neuroimaging techniques have been used extensively in clinical data analysis. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder, with the symptomology of inattention, impulsivity, and hyperactivity, in which early diagnosis is crucial to prevent unwelcome outcomes. This study addresses ADHD identification using functional magnetic resonance imaging (fMRI) data for the resting state brain by evaluating multiple feature extraction methods. The features of seed-based correlation (SBC), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) are comparatively applied to …
Analysis Of Subtelomeric Rextal Assemblies Using Quast, Tunazzina Islam, Desh Ranjan, Mohammad Zubair, Eleanor Young, Ming Xiao, Harold Riethman
Analysis Of Subtelomeric Rextal Assemblies Using Quast, Tunazzina Islam, Desh Ranjan, Mohammad Zubair, Eleanor Young, Ming Xiao, Harold Riethman
Computer Science Faculty Publications
Genomic regions of high segmental duplication content and/or structural variation have led to gaps and misassemblies in the human reference sequence, and are refractory to assembly from whole-genome short-read datasets. Human subtelomere regions are highly enriched in both segmental duplication content and structural variations, and as a consequence are both impossible to assemble accurately and highly variable from individual to individual. Recently, we developed a pipeline for improved region-specific assembly called Regional Extension of Assemblies Using Linked-Reads (REXTAL). In this study, we evaluate REXTAL and genome-wide assembly (Supernova) approaches on 10X Genomics linked-reads data sets partitioned and barcoded using the …
Joint Modeling Of Rnaseq And Radiomics Data For Glioma Molecular Characterization And Prediction, Zeina A. Shboul, Norou Diawara, Arastoo Vossough, James Y. Chen, Khan M. Iftekharuddin
Joint Modeling Of Rnaseq And Radiomics Data For Glioma Molecular Characterization And Prediction, Zeina A. Shboul, Norou Diawara, Arastoo Vossough, James Y. Chen, Khan M. Iftekharuddin
Electrical & Computer Engineering Faculty Publications
RNA sequencing (RNAseq) is a recent technology that profiles gene expression by measuring the relative frequency of the RNAseq reads. RNAseq read counts data is increasingly used in oncologic care and while radiology features (radiomics) have also been gaining utility in radiology practice such as disease diagnosis, monitoring, and treatment planning. However, contemporary literature lacks appropriate RNA-radiomics (henceforth, radiogenomics) joint modeling where RNAseq distribution is adaptive and also preserves the nature of RNAseq read counts data for glioma grading and prediction. The Negative Binomial (NB) distribution may be useful to model RNAseq read counts data that addresses potential shortcomings. …