Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,466
datasets available to search
ShareScore release 0.7.1
Dataset results
1,466 results for “genetic structures”
Figure S1 in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure S1. Median-joining network shows the distribution of 13 Erinaceus roumanicus haplotypes from the Central Balkans, with pie chart area proportional to haplotype frequencies in relation to the four detected subpopulations.
Figure 1 in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure 1. Geographic position of sampled localities of E. roumanicus from the Central Balkans in this study. Numbers of localities correspond to those shown in Table 1, where the number of individuals sampled for each locality is also given. Localities were organized in four groups as suggested by Geneland analysis (NWC – black circles; NE – red squares; SE – green polygons; SW – blue triangles).
Figure 2 in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure 2. Distribution of haplotype frequencies in four detected groups of E. roumanicus from the Central Balkans. The size of pie charts is proportional to sample size. The numbers on the x and y axes correspond to longitude and latitude decimal degrees.
Figure 4 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China
Figure 4. Bayesian tree based on mitochondrial haplotypes (1053 bp, selected model of HKY+I+G). It exhibits the phylogenetic relationships of silver pheasant, and three species (L. hatinhensis, L. leucomelanos, and L. swinhoii) are noticeable outgroups. Above branches there are numbers indicating Bayesian posterior probabilities, whereas below branches there are bootstrap values produced by ML. Each colored line represents a geographic population, while the line in black represents the shared haplotype.
Figure 3 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China
Figure 3. mtDNA MJN for silver pheasant. Circle size represents proportion of haplotype. Circles with single color indicate a private haplotype, whereas circles with two or more colors represent a shared haplotype.
Figure 1 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China
Figure 1. According to geodistance and topographic characters, we sorted sampling sites into geographic populations. The sampling sites including 7 provinces: Sichuan, Anhui, Jiangxi, Fujian, Zhejiang, Hubei, and Hunan. The abbreviation are as follows: Sichuan (SC), Anhui (AH), Jiangxi (JX), Fujian (FJ), Zhejiang (ZJ), Hubei (HB), Hunan (HN).
Figure 2 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China
Figure 2. Bayesian skyline plot of whole population of silver pheasant. The expansion time was computed by tau = 2µkt. The solid line means the estimated average effective population size and the dashed line represents 95% confidence interval.
Figure 2 in Population Genetic Structure of Testudo hermanni boettgeri (Hermann's Tortoise) in Türkiye
Figure 2.UPGMA distance tree created using the Reynolds (1983) weighted model (the node values are bootstrap values estimated with 1000 permutations).
Figure 1 in Population Genetic Structure of Testudo hermanni boettgeri (Hermann's Tortoise) in Türkiye
Figure 1. Sampling localities of T. h. boettgeri (Loc 1: Malkara, Loc 2: Orhaniye, Loc 3: Hanlıyenice, Loc 4: Adasarhan, Loc 5: Balabanlı, Loc 6: İpsala, Loc 7: Hacılar, Loc 8: Şeytanderesi, Loc 9: Meriç, Loc10: Taşlısekban, Loc 11: Kırklareli, Loc 12: Çöpköy, Loc 13: Demirköy, Loc 14: Erikler, and Loc 15: Keşan; the colorations symbolize the clusters).
Figure 3 in Population Genetic Structure of Testudo hermanni boettgeri (Hermann's Tortoise) in Türkiye
Figure 3. Population assignment test performed with Structure. (A) Barplots that estimated membership coefficients of the analyzed individuals in each locality. (B) Barplot, K = 2, clusters for 8 groups in the UPGMA distance tree. (C) Graph of ∆K as a function of the number of groups K, (Evanno's method) (the numbers on the barplots symbolize the sampling localities).
Figure 4 in Population Genetic Structure of Testudo hermanni boettgeri (Hermann's Tortoise) in Türkiye
Figure 4. Maps of the population clusters (K) identified by GENELAND. (A) Map spatial distribution of each group defined, K = 2. (B) Map of the posterior probability defined, K = 2 (the numbers symbolize the sampling localities, the colors in A and B symbolize the clusters inferred in STRUCTURE).
Fig. 2 in Impacts of a highway on the population genetic structure of a threatened freshwater turtle (Glyptemys insculpta)
Fig. 2. Estimate of short-term gene flow among populations north and south of Interstate Highway 88 (gray bar) and the Susquehanna River (dashed line) shown with 95% confidence intervals. Circle size reflects relative sample size. Values inside of circles represent the contribution of gene flow from within populations.
Fig. 1. Study area. Interstate Highway 88 in Impacts of a highway on the population genetic structure of a threatened freshwater turtle (Glyptemys insculpta)
Fig. 1. Study area. Interstate Highway 88 (I-88) and the Susquehanna River (Susq.) bisect Otsego and Delaware Counties, New York, USA.
FIGURE 4 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 4 | Bayesian skyline plot (BSP) showing change in effective population size of Prochilodus lineatus in Feb_15 group from Cachoeira de Emas in the Mogi-Guaçu River based on Dloop marker. The y-axis, population size × generation time*; x-axis, time (indicated in thousands of years ago). *Generation time measured in million years. Solid lines represent median estimates, and shaded areas represent the 95% HPD limits.
FIGURE 3 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 3 | Median-joining network of Prochilodus lineatus, based on haplotypes of D-loop marker. Sizes of the circled are proportional to the frequencies of the haplotypes at issue. The colors indicate the groups according to the collections: red circles: Sep_03; yellow circles: Jan_05; purple circles: Aug_05; blue circles: Jan_06; pink circles: Jan_09; green circles: Sep_10; pastel pink circles: Feb_15. Hatch marks represent the number of mutations by which haplotypes differ.
FIGURE 1 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 1 | Map of the State of Sao Paulo showing the main components of the hydrographic system in the Southeast of Brazil. In detail square, the collection site of samples located in Cachoeira de Emas, Pirassununga-SP. The Mogi-Guaçu River is a component of the Upper Paraná River basin.
FIGURE 2 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 2 | Graph of the Bayesian analysis of population structure of microsatellites for Prochilodus lineatus. A. Delta(k) showing the highest value in a population structure of K = 3; B. The estimated mean log-likelihoods [ln(PrK)]; C. Structure bar plot. Black lines separate the different sampled populations based on temporal collection.
Figure 7 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 7. UPGMA tree of the evaluated samples based on the molecular ISSR data (treatment's code as in Table 1).
Figure 6 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 6. Results of the AMOVA test revealed a significant genetic diversity between the treated samples
Figure 5 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 5. UPGMA tree of the studied samples according to essential oil compositions (treatment's code as in Table 1).
ScienceDex guides
Understand access before you commit
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.