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Daniel S. Peterson

Bio: Daniel S. Peterson is an academic researcher from Arizona State University. The author has contributed to research in topics: Balance (ability) & Gait (human). The author has an hindex of 22, co-authored 67 publications receiving 72201 citations. Previous affiliations of Daniel S. Peterson include Pennsylvania State University & University of Utah.


Papers
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Journal ArticleDOI
TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
Abstract: Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.

39,110 citations

Journal ArticleDOI
TL;DR: An advanced version of the Molecular Evolutionary Genetics Analysis software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis, is released, which enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny.
Abstract: We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www.megasoftware.net free of charge.

37,956 citations

Journal ArticleDOI
TL;DR: Higher C(w) and coactivation in older adults, along with the positive relationship between C(W) andCoactivation implies coactivation contributes to, higher C( w) of older adults.

173 citations

Journal ArticleDOI
TL;DR: A widespread supraspinal locomotor network including the cortex, cerebellum, basal ganglia, and brain stem contributes to the control of human locomotion, and altered activity of these structures underlies gait dysfunction due to Parkinson's disease.
Abstract: People with Parkinson's disease exhibit debilitating gait impairments, including gait slowness, increased step variability, and poor postural control. A widespread supraspinal locomotor network including the cortex, cerebellum, basal ganglia, and brain stem contributes to the control of human locomotion, and altered activity of these structures underlies gait dysfunction due to Parkinson's disease.

120 citations

Journal ArticleDOI
03 Mar 2014-PLOS ONE
TL;DR: Results suggest FoG+ exhibit dysfunction in a number of cortical and subcortical regions, possibly with asymmetric dysfunction towards the right hemisphere, as well as trends toward lower beta weights in other right-hemisphere locomotor regions
Abstract: Approximately 50% of people with Parkinson disease experience freezing of gait, described as a transient inability to produce effective stepping Complex gait tasks such as turning typically elicit freezing more commonly than simple gait tasks, such as forward walking Despite the frequency of this debilitating and dangerous symptom, the brain mechanisms underlying freezing remain unclear Gait imagery during functional magnetic resonance imaging permits investigation of brain activity associated with locomotion We used this approach to better understand neural function during gait-like tasks in people with Parkinson disease who experience freezing- “FoG+” and people who do not experience freezing- ”FoG−“ Nine FoG+ and nine FoG− imagined complex gait tasks (turning, backward walking), simple gait tasks (forward walking), and quiet standing during measurements of blood oxygen level dependent (BOLD) signal Changes in BOLD signal (ie beta weights) during imagined walking and imagined standing were analyzed across FoG+ and FoG− groups in locomotor brain regions including supplementary motor area, globus pallidus, putamen, mesencephalic locomotor region, and cerebellar locomotor region Beta weights in locomotor regions did not differ for complex tasks compared to simple tasks in either group Across imagined gait tasks, FoG+ demonstrated significantly lower beta weights in the right globus pallidus with respect to FoG− FoG+ also showed trends toward lower beta weights in other right-hemisphere locomotor regions (supplementary motor area, mesencephalic locomotor region) Finally, during imagined stand, FoG+ exhibited lower beta weights in the cerebellar locomotor region with respect to FoG− These data support previous results suggesting FoG+ exhibit dysfunction in a number of cortical and subcortical regions, possibly with asymmetric dysfunction towards the right hemisphere

93 citations


Cited by
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Journal ArticleDOI
TL;DR: An advanced version of the Molecular Evolutionary Genetics Analysis software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis, is released, which enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny.
Abstract: We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www.megasoftware.net free of charge.

37,956 citations

Journal ArticleDOI
TL;DR: The latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine, has been optimized for use on 64-bit computing systems for analyzing larger datasets.
Abstract: We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.

33,048 citations

01 Jan 2013
TL;DR: The Molecular Evolutionary Genetics Analysis (MEGA) software as discussed by the authors provides facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis, including the inference of timetrees.
Abstract: We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www. megasoftware.net free of charge.

30,478 citations

Journal ArticleDOI
03 Feb 2020-Nature
TL;DR: Phylogenetic and metagenomic analyses of the complete viral genome of a new coronavirus from the family Coronaviridae reveal that the virus is closely related to a group of SARS-like coronaviruses found in bats in China.
Abstract: Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health1–3. Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China5. This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans. Phylogenetic and metagenomic analyses of the complete viral genome of a new coronavirus from the family Coronaviridae reveal that the virus is closely related to a group of SARS-like coronaviruses found in bats in China.

9,231 citations