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1,048 results for “interpreting”
ENDES2019 Dataset with interpretation on depressive symptomatology in Peruvian adults with HTA
<p>ENDES2019 Dataset with interpretation on depressive symptomatology in Peruvian adults with HTA</p>
Data from: Evidence for climate-driven diversification? A caution for interpreting ABC inferences of simultaneous historical events
Approximate Bayesian computation (ABC) is rapidly gaining popularity in population genetics. One example, msBayes, infers the distribution of divergence times among pairs of taxa, allowing phylogeographers to test hypotheses about historical causes of diversification in co-distributed groups of organisms. Using msBayes, we infer the distribution of divergence times among 22 pairs of populations of vertebrates distributed across the Philippine Archipelago. Our objective was to test whether sea-level oscillations during the Pleistocene caused diversification across the islands. To guide interpretation of our results, we perform a suite of simulation-based power analyses. Our empirical results strongly support a recent simultaneous divergence event for all 22 taxon pairs, consistent with the prediction of the Pleistocene-driven diversification hypothesis. However, our empirical estimates are sensitive to changes in prior distributions, and our simulations reveal low power of the method to detect random variation in divergence times and bias toward supporting clustered divergences. Our results demonstrate that analyses exploring power and prior sensitivity should accompany ABC model-selection inferences. The problems we identify are potentially mitigable with uniform priors over divergence models (rather than classes of models) and more flexible prior distributions on demographic and divergence-time parameters.
Data from: The analysis and interpretation of critical temperatures
Critical temperatures are widely used to quantify the upper and lower thermal limits of organisms. But measured critical temperatures often vary with methodological details, leading to spirited discussions about the potential consequences of stress and acclimation during the experiments. We review a model based on the simple assumption that failure rate increases with increasing temperature, independent of previous temperature exposure, water loss or metabolism during the experiment. The model predicts that mean critical thermal maximal temperatures (CTmax) increases nonlinearly with starting temperature and ramping rate, a pattern frequently observed in empirical studies. We then develop a statistical model that estimates a failure rate function (the relationship between failure rate and current temperature) using maximum likelihood; the best model accounts for 58% of the variation in CTmax in an exemplary dataset for tsetse flies. We then extend the model to incorporate potential effects of stress and acclimation on the failure rate function; the results show how stress accumulation at low ramping rate may increase the failure rate and reduce observed values of CTmax. We also applied the model to an acclimation experiment with hornworm larvae that used a single starting temperature and ramping rate; the analyses show that increasing acclimation temperature significantly reduced the slope of the failure rate function, increasing the temperature at which failure occurred. The model directly applies to critical thermal minima, and can utilize data from both ramping and constant temperature assays. Our model provides a new approach to analyzing and interpreting critical temperatures.
Data from: Markov switching autoregressive models for interpreting vertical movement data with application to an endangered marine apex predator
1.Time series of animal movement obtained from bio-loggers are becoming widely used across all taxa. These data are nowadays of high quality, combining high resolution with precision, as the tags are able to collect for longer times and store larger quantities of data. Due to their nature, high-frequency data sequences often pose non-trivial problems in time series analysis: non-linearity, non-Normality, non-stationarity, and long memory. These issues can be tackled by modelling the data sequence as a realization of a stochastic regime switching process. 2. We suggest a novel Markov switching autoregressive model where the hidden Markov chain is non-homogeneous, with time-varying transition probabilities, whose dynamics depend on the dynamics of some contemporary categorical covariates. 3. To illustrate the use of the method, we apply it to the depth profiles of four individuals of flapper skate (Dipturus cf. intermedia) in order to identify swimming behaviours. Individual time series were obtained from data storage tags that recorded pressure every two minutes. The environmental covariates used were lunar phase (a proxy for the spring-neap tidal cycle), lunar cycle, and diel cycle. For all individuals two states (or regimes) were always selected (the autoregressive order was either three or four), representing different regimes of animal activity, i.e., state 1 for resting or horizontal swimming or slow vertical movement; state 2 for fast ascending and descending. The cycle of the four lunar phases was the only environmental covariate that explained the hidden state dynamics in all individuals, whereas lunar cycle was selected for two individuals and diel cycle for one only. 4. The method is an efficient approach to fit one-dimensional tag data using categorical environmental covariates, and to classify the observations into a small number of states representing individual behaviours of tagged individuals.
Data from: Stalking the fourth domain in metagenomic data: searching for, discovering, and interpreting novel, deep branches in phylogenetic trees of phylogenetic marker genes
BACKGROUND: Most of our knowledge about the ancient evolutionary history of organisms has been derived from data associated with specific known organisms (i.e., organisms that we can study directly such as plants, metazoans, and culturable microbes). Recently, however, a new source of data for such studies has arrived: DNA sequence data generated directly from environmental samples. Such metagenomic data has enormous potential in a variety of areas including, as we argue here, in studies of very early events in the evolution of gene families and of species. METHODOLOGY/PRINCIPAL FINDINGS: We designed and implemented new methods for analyzing metagenomic data and used them to search the Global Ocean Sampling (GOS) Expedition data set for novel lineages in three gene families commonly used in phylogenetic studies of known and unknown organisms: small subunit rRNA and the recA and rpoB superfamilies. Though the methods available could not accurately identify very deeply branched ss-rRNAs (largely due to difficulties in making robust sequence alignments for novel rRNA fragments), our analysis revealed the existence of multiple novel branches in the recA and rpoB gene families. Analysis of available sequence data likely from the same genomes as these novel recA and rpoB homologs was then used to further characterize the possible organismal source of the novel sequences. CONCLUSIONS/SIGNIFICANCE: Of the novel recA and rpoB homologs identified in the metagenomic data, some likely come from uncharacterized viruses while others may represent ancient paralogs not yet seen in any cultured organism. A third possibility is that some come from novel cellular lineages that are only distantly related to any organisms for which sequence data is currently available. If there exist any major, but so-far-undiscovered, deeply branching lineages in the tree of life, we suggest that methods such as those described herein currently offer the best way to search for them.
Data from: Linkage mapping reveals strong chiasma interference in sockeye salmon: implications for interpreting genomic data
Meiotic recombination is fundamental for generating new genetic variation and for securing proper disjunction. Further, recombination plays an essential role during the rediploidization process of polyploid-origin genomes because crossovers between pairs of homeologous chromosomes retain duplicated regions. A better understanding of how recombination affects genome evolution is crucial for interpreting genomic data; unfortunately, current knowledge mainly originates from a few model species. Salmonid fishes provide a valuable system for studying the effects of recombination in nonmodel species. Salmonid females generally produce thousands of embryos, providing large families for conducting inheritance studies. Further, salmonid genomes are currently rediploidizing after a whole genome duplication and can serve as models for studying the role of homeologous crossovers on genome evolution. Here, we present a detailed interrogation of recombination patterns in sockeye salmon (Oncorhynchus nerka). First, we use RAD sequencing of haploid and diploid gynogenetic families to construct a dense linkage map that includes paralogous loci and location of centromeres. We find a nonrandom distribution of paralogs that mainly cluster in extended regions distally located on 11 different chromosomes, consistent with ongoing homeologous recombination in these regions. We also estimate the strength of interference across each chromosome; results reveal strong interference and crossovers are mostly limited to one per arm. Interference was further shown to continue across centromeres, but metacentric chromosomes generally had at least one crossover on each arm. We discuss the relevance of these findings for both mapping and population genomic studies.
M. Szymanik | Golden Duck | Image Interpretation
Golden Duck in Warsaw Source: Objaverse 1.0 / Sketchfab
FIGURES 1–9 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 1–9. Stenichnus godarti. Mature larva patrolling the arena (1–2) and eating an oribatid mite (3–4); pupa five days after pupation (5, 8–9), teneral adult eating uropodine mite (6), and prepupa (7).
FIGURES 23–24 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 23–24. Alternative cephalic setal homology between Stenichnus godarti (23) and St. collaris (24; after Jałoszyński 2013). Setae are organize in presumably homologous groups: labrofrontal I (Lbf1), labrofrontal II (Lbf2), mediolateral (Ml), prestigmal-postantennal (Prs), poststigmal (Pst), dorsal epicranial I (Dep1), dorsal epicranial II (Dep2), and dorsal epicranial posterior (Depp). Abbreviations: AnI, antennal insertion; Es, frontal arm of epicranial suture; Est, epicranial stem; sEs, hypothetically 'shifted' epicranial suture; St, stemma.
FIGURES 21–22 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 21–22. Larva of Stenichnus godarti. Abdomen in dorsal (21) and ventral (22) view (if one half of tergite or sternite bears more setae, setation of the other half is treated as incomplete). Abbreviations: AM, anal membrane; L, lateral seta; l, lentiform structure; mt, microtrichion; P, posterior seta; Sp, spiracle; V, ventral seta.
FIGURES 19–20 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 19–20. Larva of Stenichnus godarti. Thorax in dorsal (19) and ventral (20) views. Abbreviations: A, anterior seta; Cxc, coxal cavity; D, dorsal seta; L, lateral seta; l, lentiform structure; P, posterior seta; Sp, spiracle; T1d, pronotum; T1v, prosternum; T2d, mesonotum; T2v, mesosternum; T3d, metanotum; T3v, metasternum; V, ventral seta; Vl, ventrolateral seta.
FIGURES 29–32 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 29–32. Alternative mesonotal (29, 31) and metanotal (30, 32) setal homology between Stenichnus godarti (29–30) and St. collaris (31–32; after Jałoszyński 2013). Setae are organized in presumably homologous rows: dorsal (D), lateral (L) and posterior (P). Within incomplete rows hypothetically absent setae are marked by asterisks (*).
FIGURES 16–18 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 16–18. Larva of Stenichnus godarti. Left fore leg in posterior view (16), right middle leg in posterior view (17) and right hind leg in anterior view (18). Abbreviations: A, anterior seta; Cx, coxa; D, dorsal seta; Fe, femur; Pd, posterodorsal seta; Pr, pretarsus; Pv, posteroventral seta; sp, spines; Ti, tibiotarsus; Tr, trochanter; V, ventral seta.
FIGURES 25–28 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 25–28. Alternative pronotal setal homology between Stenichnus godarti (25–26) and St. collaris (27–28; after Jałoszyński 2013); variant I (25, 27) and variant II (26, 28) discussed in the text. Setae are organized in presumably homologous rows: dorsal (D) and lateral (L).
FIGURE 1 in The interpretation of some Conopidae (Diptera) described by RobineauDesvoidy
FIGURE 1: Original labels of the lectotype of Zodion carceli ROBINEAUDESVOIDY, 1830; Right: an original label in the hand of RobineauDesvoidy.
FIGURE 3. S8 in Revision of the Panurgus dargius Warncke, 1972 interpretation (Hymenoptera: Andrenidae), comparison with the morphologically close species
FIGURE 3. S8 apex: a. ventrally tetrahedroid shaped in Panurgus cephalotes; b. triangular dorsal section of the top in Panurgus cephalotes; c. blade S8 top in Panurgus dargius; d. subelliptic section of the S8 top in Panurgus dargius. Same scale as Fig. 1.
FIGURES 6–7 in Geoplana multicolor Graff (Platyhelminthes: Tricladida): new records and taxonomic re-interpretation of morphological characters
FIGURES 6–7. Diagrammatic sagittal composite reconstructions of the copulatory apparatus of G. multicolor: (6) from São Francisco de Paula (MZU PL.00083); (7) from Santa Maria (MZU PL.00100). (cov) common glandular oviduct, (e) ejaculate, (ef) efferent duct, (ej) ejaculatory duct, (fa) female atrium, (go) gonopore, (ma) male atrium, (ov) oviducts, (pp) penis papilla, (pv) prostatic vesicle, (sc) secretory cells, (sg) shell glands, (va) vagina. Scale bar: 1mm.
FIGURE 4 in Geoplana multicolor Graff (Platyhelminthes: Tricladida): new records and taxonomic re-interpretation of morphological characters
FIGURE 4. Detail of the pre-pharyngeal region in transverse section of specimen MZU PL.00091 of G. multicolor Graff, 1899. (cm) cutaneous musculature, (de) dorsal epidermis, (gm) glandular margin, (i) intestine, (mm) mesenchymatical muscles, (t) testes. Scale bar: 1mm.
FIGURES 2–3 in Geoplana multicolor Graff (Platyhelminthes: Tricladida): new records and taxonomic re-interpretation of morphological characters
FIGURES 2–3. Detail of colour pattern of preserved specimens of G. multicolor Graff, 1899 from Southern Brazil: (2) specimen MZU PL.00092, from Santa Maria; (3) specimen MZU PL.00095, from Caxias do Sul. (e) eyes, (m) median stripe, (pm) paramedian stripes. Scale bar: 1mm.
FIGURE 1 in Geoplana multicolor Graff (Platyhelminthes: Tricladida): new records and taxonomic re-interpretation of morphological characters
FIGURE 1. Photograph of a live specimen of G. multicolor Graff, 1899, in dorsal view, from São Francisco de Paula.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.