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9 results for “evolutionary forces”
Polymorphism-aware estimation of species trees and evolutionary forces from genomic sequences with RevBayes
<p>Supplementary files of Polymorphism-aware estimation of species trees and evolutionary forces from genomic sequences with RevBayes by Borges, Boussau, Höhna, Pereira and Kosiol<br> </p>
Data from: A brief history and popularity of methods and tools used to estimate micro-evolutionary forces
<p class="western">Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces – mutation, gene flow, genetic drift and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and High Throughput Sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.</p>
Figure 3. Strict consensus trees from the constrained analyses. First constrained analysis forcing a in Taxonomic, palaeobiological and evolutionary implications of a phylogenetic hypothesis for Ornithischia (Archosauria: Dinosauria)
Figure 3. Strict consensus trees from the constrained analyses. First constrained analysis forcing a monophyletic Silesauridae apart from the 'traditional ornithischians'. Abbreviations: Aphan, Aphanosauria; Herrer, Herrerasauridae. Silhouettes are based on artwork by Márcio L. Castro, Gabriel Lio, Rodrigo T. Müller, Maurício S. Garcia, John Sibbick and Douglas M. Heman.
Figure 4. Second constrained analysis forcing a in Taxonomic, palaeobiological and evolutionary implications of a phylogenetic hypothesis for Ornithischia (Archosauria: Dinosauria)
Figure 4. Second constrained analysis forcing a monophyletic Ornithoscelida. Abbreviations: Aphan, Aphanosauria; Herrer, Herrerasauridae. Silhouettes are based on artwork by Márcio L. Castro, Gabriel Lio, Rodrigo T. Müller, Maurício S. Garcia, John Sibbick and Douglas M. Heman.
Data from: A brief history and popularity of methods and tools used to estimate micro-evolutionary forces
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Data from: Parallel evolutionary forces influence the evolution of male and female songs in a tropical songbird
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Fig 2 from: Strauß J (2019) What determines the number of auditory sensilla in the tympanal hearing organs of Tettigoniidae? Perspectives from comparative neuroanatomy and evolutionary forces. Journal of Orthoptera Research 28(2): 205-219. https://doi.org/10.3897/jor.28.33586
Fig 2 Standardized effects of call patterns in Neoconocephalus on the number of CA sensilla and CA length for a. Pulse rate; b. Structure of continuous or discontinuous calls; and c. Pulse pattern. The evolutionary derived call characters are a slow pulse rate, discontinuous calls, and double pulses. Significance levels: * 0.05 > p > 0.01; ** 0.01 > p > 0.001. Adapted from Strauß et al. 2017, with permission from John Wiley and Sons.
Fig 1 from: Strauß J (2019) What determines the number of auditory sensilla in the tympanal hearing organs of Tettigoniidae? Perspectives from comparative neuroanatomy and evolutionary forces. Journal of Orthoptera Research 28(2): 205-219. https://doi.org/10.3897/jor.28.33586
Fig 1 The auditory system of bushcrickets. a. Schematic of the acoustic trachea (at) from the acoustic spiracle (as) in the thorax into the foreleg with tympanal membranes (ty) in the proximal tibia; b. Transverse section of the tibia at the level of the tympana and crista acustica in Gampsocleis gratiosa; in Gampsocleis gratiosa; c. The sensory organs in the proximal tibia of the male Tettigonia viridissima. The dorsal cuticle has been removed after axonal tracing of the tympanal nerve with cobalt solution to stain sensory neurons of the subgenual organ (SGO), intermediate organ (IO) and crista acustica. The crista acustica is placed between the anterior tympanum (aty) and posterior tympanum (pty). The tympanal flaps (tf) cover the tympanal membranes. Arrows indicate the tectorial membrane; d. Morphological differences of sensory neurons along the crista acustica from G. gratiosa, showing the (di) third-most proximal, (dii) middle, and (diii) third-most distal sensillum. Abbreviations: at, anterior trachea; aty, anterior tympanum; cc, cap cell; de, dendrite; dow, dorsal tracheal wall; hc, haemolymph channel; IO, intermediate organ; nmc, nerve muscle channel; nsc, nucleus of scolopale cell; pn, perikarya of sensory neurons; pt, posterior trachea; pty, posterior tympanum; s, septum; sb, supporting band; scol, scolopale cap and rods; SGO, subgenual organ; sli, slit; sn, sensory neuron; tf, tympanal flap; tm, tectorial membrane. Scales: 500 µm (B), 100 µm (C), 50 µm (D). Figure a. reprinted from Strauß et al. 2014, with permission from John Wiley and Sons. b., d. redrawn from Lin et al. 1994, with permission from John Wiley and Sons.
L1 retrotransposons exploit RNA m6A modification as an evolutionary driving force
GEO Series GSE152328. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.