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2,445 results for “Genetics: population”
Fig. 2 Maximum likelihood phylogenetic tree constructed using the mitochondrial cox1 gene for 103 in Genetic diversity and population genetics of large lungworms (Dictyocaulus, Nematoda) in wild deer in Hungary
ƒFig. 2 Maximum likelihood phylogenetic tree constructed using the mitochondrial cox1 gene for 103 Dictyocaulus lungworms originating from Hungary and five lungworms from GenBank indicated by their accession numbers (one dictyocaulid worm of red deer in New Zealand and four sequences of D. viviparus). Lungworms were collected from hunted deer (fallow, red and roe deer), indicated by triangle, square and circle, respectively. Geographical collecting regions are indicated for each sample
Fig. 3 in Genetic diversity and population genetics of large lungworms (Dictyocaulus, Nematoda) in wild deer in Hungary
Fig. 3 Observed and simulated (expected) mismatch frequency distributions under a model of population expansion for D. eckerti overall (a), D. capreolus overall (b) and the eastern population of
Fig. 1 in Genetic diversity and population genetics of large lungworms (Dictyocaulus, Nematoda) in wild deer in Hungary
Fig. 1 Map of collecting sites of Dictyocaulus in Hungary. Host species are indicated using different symbols (triangle: fallow deer; square: red deer; circle: roe deer), as are lungworm species (filled symbol: D. eckerti; empty symbol: D. capreolus; leaky symbol: D. sp. S-HU)
Fig. 2 in Genetic diversity and population structure of endangered Neofinetia falcata (Orchidaceae) in South Korea based on microsatellite analysis
Fig. 2. Structure analyses for putative genetic clusters of N. falcata. A: Graphs of ΔK values to determine the ideal number of groups present in the accessions of N. falcata. B: Estimated genetic structure of the 3 populations of brinjal based on STRUCTURE analysis K = 2 and K = 3.
A Genetic Algorithm Approach to Regenerate Image from a Reduce Scaled Image Using Bit Data Count-Figure 11. Initial population
<p>In figure 11 it is the initial population showed and figure 12 the population started to change and figure 13 we reached a convergence.</p>
data for the PCI publication "New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations"
<p><strong>Data analyzed int he article "New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations", doi </strong> <a href="https://arxiv.org/abs/1902.10240v5">https://arxiv.org/abs/1902.10240v5</a> <strong> doi of the PCI recommandation: </strong>https://doi.org/10.24072/pci.evolbiol.100083</p>
Fig. 2 in Genetic divergence of a newly documented population of the cecidogenous micromoth Eugnosta azapaensis Vargas & Moreira (Lepidoptera: Tortricidae) in the Atacama Desert of northern Chile
Fig. 2. Median joining network of the haplotypes of the DNA barcode fragment (658 bp) of the cytochrome c oxidase subunit I (COI) gene of Eugnosta azapaensis from Azapa (white) and Chaca (black) valleys, Atacama Desert of northern Chile. H1, H2, H3, H4 haplotypes; circles proportional to the frequency of the respective haplotype; numbers between circles indicates variable sites; gray triangle a median vector.
Fig. 1 in Genetic divergence of a newly documented population of the cecidogenous micromoth Eugnosta azapaensis Vargas & Moreira (Lepidoptera: Tortricidae) in the Atacama Desert of northern Chile
Fig. 1. The study area in South America (left) and the sampling sites (right) of Eugnosta azapaensis in the Atacama Desert of northern Chile. The type locality Azapa Valley (black circle) and the newly documented locality Chaca Valley (black triangle).
Fig. 2 in Genetic and morphological differentiation among populations of the narrowly endemic and karst forest-adapted Pilea pteridophylla (Urticaceae)
Fig. 2 Morphological variation among individuals of Pilea pteridophylla sampled along its distribution range in the tropical karst forest of southern Mexico. Plot of individual scores for the first two components of the principal component analysis using morphological data. Coloured symbols represent the two populations recognized for the species: red circles, Tabasco; and blue circles, Chiapas. Ellipses correspond to the 95% confidence intervals estimated for each population. The lines represent the dispersion of the individuals within each population
Fig. 3 in Genetic and morphological differentiation among populations of the narrowly endemic and karst forest-adapted Pilea pteridophylla (Urticaceae)
Fig. 3 Statistical parsimony networks of rps16-trnQ, trnL-trnF and rps16-trnQ + trnL-trnF dataset using the gaps as missing data. Coloured symbols represent the two populations recognized for the species: red circles, Tabasco; and blue circles, Chiapas. Open-white circles represent the number of mutational steps between haplotypes. The size of the circles is proportional to the frequency of each haplo-
Fig. 1 in Genetic and morphological differentiation among populations of the narrowly endemic and karst forest-adapted Pilea pteridophylla (Urticaceae)
Fig. 1 Mountain karst forests of Mexico and the studied species Pilea pteridophylla A. K. Monro (Urticaceae). A Geographic distribution of the Mountain karst forests of Mexico. B Individual from the Chiapas population. C Individual from the Tabasco population
Figure 3 in Determination of genetic variations between Apodemus mystacinus populations distributed in Turkey inferred from mtDNA PCR-RFLP
Figure 3. Restriction patterns of HinfI inferred from D-loop digestion (M: Marker–100bp DNA Ladder, 1. Ordu, 2. Trabzon, 3. Rize, 4. Artvin, 5–6. Erzincan, 7–8. Kahramanmaraş, 9. Adıyaman, 10–11. Adana, 12. Muğla, 13. Burdur, 14. Konya, 15. Antalya, 16. Mersin, 17. Kastamonu, 18. Zonguldak, 19. Düzce, 20. Balıkesir, 21. İzmir, 22. Aydın, 23. A. uralensis, 24. A. witherbyi, 25. D-loop PCR products).
Figure 2 in Determination of genetic variations between Apodemus mystacinus populations distributed in Turkey inferred from mtDNA PCR-RFLP
Figure 2. Restriction patterns of MboI, HaeIII, and RsaI inferred from cytb digestion (M: Marker–100bp DNA Ladder, 1. Ordu, 2. Trabzon, 3. Rize, 4. Artvin, 5. Erzincan, 6. Kahramanmaraş, 7. Adıyaman, 8. Adana, 9. Muğla, 10. Burdur, 11. Konya, 12. Antalya, 13. Mersin, 14. Kastamonu, 15. Zonguldak, 16. Düzce, 17. Balıkesir, 18. İzmir, 19. Aydın, 20. A. uralensis, 21. A. witherbyi, 22. Cytb PCR product).
Figure 5 in Determination of genetic variations between Apodemus mystacinus populations distributed in Turkey inferred from mtDNA PCR-RFLP
Figure 5. PCoA analysis of A. mystacinus clades. The scatter plot is of the scores of three principal eigenvalues inferred from NTSYS software. Each scatter point represents a specimen of A. mystacinus.
Figure 2 in Investigation of genetic variation among Turkish populations of Andricus lignicola using mitochondrial cytochrome b gene sequence data
Figure 2. Bayesian analysis tree. Posterior probability values are given on the branches. Outgroup haplotypes: Ac (Andricus caliciformis) and Ak (Andricus kollari).
Figure 1 in Determination of genetic variations between Apodemus mystacinus populations distributed in Turkey inferred from mtDNA PCR-RFLP
Figure 1. Sampling localities of A. mystacinus specimens. Table 2. Restriction enzymes and their digestion sites with reaction procedures.
Figure 2 in High genetic distinctiveness of wild and farm fox (Vulpes vulpes L.) populations in Poland: evidence from mitochondrial DNA analysis
Figure 2. Neighbor-joining haplotype network based on frequencies showing relationships between concatenated MT-CO1 and MTATP6 sequences of fur farm and wild red foxes.
Figure 1 in High genetic distinctiveness of wild and farm fox (Vulpes vulpes L.) populations in Poland: evidence from mitochondrial DNA analysis
Figure 1. Distribution of sampling sites of wild and fur-farm red foxes in Poland: light gray areas represent the provinces from which samples of wild foxes were taken; the darker gray area indicated with a black circle shows the location of investigated fox farms; the numbers represent fox fur-farms in particular voivodeships.
Figure 1 in Genetic diversity and Kdr mutations of natural Aedes (Stegomyia) aegypti (Diptera: Culicidae) populations of Brazil
Figure 1 Distribution of the kdr alleles in Aedes aegypti populations for each Paraná locality. The state is detached, showing its multiple cities of collection.
Figure 3 in Genetic diversity and Kdr mutations of natural Aedes (Stegomyia) aegypti (Diptera: Culicidae) populations of Brazil
Figure 3 Dendrogram of the 40 haplotypes of Aedes aegypti divided into four groups. Neighbor-joining (NJ) tree of A. aegypti haplotypes using the Tamura-Nei parameter genetic distance model. Bootstrap values are marked under the respective nodes. S. albopictus was considered as external group. AS - Alvorada do Sul; MR - Marilena; MG -Maringá, NL - Nova Londrina; PV - Paranavaí; SC - São Carlos do Ivaí.
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.