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.
15,277
datasets available to search
ShareScore release 0.9.0
Dataset results
15,277 results for “GENETICS”
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. 3 in Chloroplast genome of the conserved Aster altaicus var. uchiyamae B2015-0044 as genetic barcode
Fig. 3. The variable sites in the chloroplast genomes of Aster altaicus var. uchiyamae. Variable sequences are marked in red. GG: Yeoju, Gyeonggi Province, CB: Cheongju, Chungcheongbuk Province.
Fig. 2 in Chloroplast genome of the conserved Aster altaicus var. uchiyamae B2015-0044 as genetic barcode
Fig. 2. The sequence alignment of variable sites in the chloroplast genomes of Aster altaicus var. uchiyamae. Variable sequences are marked in red. GG: Yeoju, Gyeonggi Province, CB: Cheongju, Chungcheongbuk Province.
Fig. 2 in Testing microsatellite loci and preliminary genetic study for Eurasian otter in South Korea
Fig. 2. Locations of sampling for tissue (1. Hoengseong-gun, Gangwon-do, 2. Uljin-gun, Gyeongsangbuk-do, 3. Jeongeup-si, Jeollabukdo, 4. Muju-gun, Jeollabuk-do, 5. Hampyeong-gun, Jeollanam-do).
Fig. 2 in Chloroplast genome of white wild chrysanthemum, Dendranthema sp. K247003, as genetic barcode
Fig. 2. Comparison of chloroplast genomes of Dendranthema sp. K247003 and D. boreale IT121002 using mVISTA program. Grey arrows and thick black lines above the alignment indicate genes with their orientation and the position of the IRs, respectively. The Yscale represents the percent identity between 50-100%. Genome regions are color-coded: Coding regions in blue; noncoding sequences (CNS) in red.
FIGURE 4 in Morphological and genetic diversification of pygmy and marbled newts, with the description of a new species from the wider Lisbon Peninsula (Triturus, Salamandridae)
FIGURE 4 Geographical clines observed for 'Triturus pygmaeus' in a longitudinal transect across central Portugal (see fig. 3), with T. rudolfi nov. sp. in the west and T. pygmaeus in the east. The horizontal axis is distance in km, measured from the nominal centre of the contact zone at Entroncamento railway station. The vertical axes are from top to bottom, left column – PCA2 for 54 SNP markers and the frequency of the eastern mtDNA haplotype, and in the right-hand column – the number of links and body size (lnSVl1) of adult males and females. Solid dots represent populations and the grey areas represent the 95% credibility intervals. Note that the colour bar is applied to fig. 3B. The formal cline descriptions are in supplementary table S3.
FIGURE 2 in Morphological and genetic diversification of Old-World marbled newts, with the description of a new and 'not-at-all-cryptic' subspecies from the Iberian Peninsula (Triturus, Salamandridae)
FIGURE 2 The distribution of two species of marbled newts over the western part of the Iberian Peninsula, as inferred from the morphological character Nlinks. Triturus marmoratus is shown in two shades of blue, T. pygmaeus in two shades of red and four localities with both species are shown in grey (see colour legend). The spatial extrapolation does not exceed ca. 50 km. Note that southern Iberian populations are all T. pygmaeus, irrespective of high (cluster C1), low (C2), or bimodal Nlink counts (Doñana National Park). Populations that were studied morphometrically are highlighted by a box. The type locality for T. pygmaeus lusitanicus ssp. nov. is Granja, Portugal and is marked by an asterisk.
FIGURE A1 in Morphological and genetic diversification of pygmy and marbled newts, with the description of a new species from the wider Lisbon Peninsula (Triturus, Salamandridae)
FIGURE A1 Holotype of Triturus rudolfi sp. nov. at right (top) and left lateral view (middle), and in ventral view (bottom). Size bar is 1 cm. Stored at the Museo Nacional de Ciencias Naturales, Madrid, Spain under catalogue number 51784. Downloaded from Brill.com 07/10/2024 02:01:22PM via Open Access. This is an open access article distributed under the terms of the CC BY 4.0 license. https://creativecommons.org/licenses/by/4.0/
FIGURE 4 in Morphological and genetic diversification of Old-World marbled newts, with the description of a new and 'not-at-all-cryptic' subspecies from the Iberian Peninsula (Triturus, Salamandridae)
FIGURE 4 Morphological and genetic variation in Triturus pygmaeus from in and around Doñana National Park (DNP). A – histograms of Nlink counts for four population groups with, from top to bottom: southwestern cluster of T. pygmaeus (localities 65, 436, 438 and 1004 in the south of Portugal, together marked C1 in fig. 2), populations in the northern section of DNP (ER, locality 1005 and BS, locality 1006), population in the southern section of DNP (locality 271) and the Betic cluster of T. pygmaeus (localities 270, 463, 465 and 1003 in the very south of Spain, together marked C2 in fig. 1). Exceptionally, the northern Doñana museum material contains 15 juvenile specimens (open bars) along with three adults (shaded bars). B – geographical cline in microsatellite genetic variation. The horizontal axis shows 'Distance from the Guadalquivir River' in km and the vertical axis presents Structure Q-scores. The solid round symbols represent populations and the grey area shows the 95% credibility interval. The Structure Q-scores were extracted from a published figure (Albert & García-Navas, 2022: Figure 4) and are unavoidably imprecise. The position of the 'Torre Carbonero', a cultural landmark at the Doñana beach, is shown by an arrow (TC). Three populations with morphological data available, that can be associated to the transect are El Rocío (arrow marked ER) and the biological station (BS) in northern Doñana and Zacallón C. de los Junqueros in southern Doñana (arrow marked 271). For details, see table 1 and supplementary table S1.
FIGURE 5 in Morphological and genetic diversification of pygmy and marbled newts, with the description of a new species from the wider Lisbon Peninsula (Triturus, Salamandridae)
FIGURE 5 Histogram for the number of links (Nlinks) observed in Iberian large-bodied newts, with low values for Triturus marmoratus (top panel), intermediate values for T. rudolfi sp. nov. (middle panel) and low to high values for T. pygmaeus (bottom panel). A distinction is made between T. p. pygmaeus from the Betic region (grey bars) and T. p. lusitanicus from the remainder of the species range (open bars) (see Arntzen, 2024). The optimal separation of T. rudolfi nov. sp. versus T. p. lusitanicus is achieved at Nlinks = 6.8, as shown by an interrupted line. To the right examples are shown of individuals with low and high link counts. Animals are facing left, with T. marmoratus from Gerês, northern Portugal at the top and T. p. lusitanicus from Sagres, southern Portugal at the bottom. Links are counted over the left and right side of the newts' bodies, in between the insertion of the fore- and hind leg. THE IMAGERY IS REPRODUCED FROM ARNTZEN (2018)
FIGURE 3 in Morphological and genetic diversification of Old-World marbled newts, with the description of a new and 'not-at-all-cryptic' subspecies from the Iberian Peninsula (Triturus, Salamandridae)
FIGURE 3 Nine marbled newts from three (sub)species each in dorsal and ventral view. Link counts for the left and right side of the body are given in parentheses. Top row – Triturus marmoratus from Jublains, France; left male (3, 2) and right female (1, 1). Middle row – T. pygmaeus lusitanicus ssp. nov. from Cardeña, Spain; from left to right female (2, 4), male (4, 3) and male (4, 5). Bottom row – T. p. pygmaeus from Salinas, Spain; from left to right male (2, 1), male (1, 2) male (2,0) and female (3, 1). Note that the colour pattern in T. marmoratus and T. p. pygmaeus is horizontally banded whereas in T. p. lusitanicus ssp. nov. it is reticulated. PHOTOGRAPHY L. A. VAN DER LAAN
Fig. 2 in Morphological and genetic data suggest a complex pattern of inter-island colonisation and differentiation for mining bees (Hymenoptera: Anthophila: Andrena) on the Macaronesian Islands
Fig. 2 Median Joining network of Andrena species (Micrandrena) of the Canary Islands and the Madeira Archipelago. Circle size is relative to number of haplotype copies present in dataset. A branch represents a single nucleotide change (mutation); bars on branches represent inferred missing haplotypes (single nucleotide changes). LG La Gomera, LP La Palma. The colours correspond to those used to represent the location of species on islands in Fig. 1
Fig. 3 in Morphological and genetic data suggest a complex pattern of inter-island colonisation and differentiation for mining bees (Hymenoptera: Anthophila: Andrena) on the Macaronesian Islands
Fig. 3 Dated species tree demonstrating the phylogenetic relationships of the different island populations calculated with *BEAST compared to the outgroup species Andrena enslinella, A. subopaca, A. minutuloides, and A. semilaevis (all Micrandrena); dating is based
Fig. 6 in Morphological and genetic data suggest a complex pattern of inter-island colonisation and differentiation for mining bees (Hymenoptera: Anthophila: Andrena) on the Macaronesian Islands
Fig. 6 Correlation of genetic distance (ΦST) and A squared Mahalanobis distance of morphometric data (r2= 0.18) and B Euclidian distance of qualitative morphological data (r2= 0.12)
Fig. 1 in Morphological and genetic data suggest a complex pattern of inter-island colonisation and differentiation for mining bees (Hymenoptera: Anthophila: Andrena) on the Macaronesian Islands
Fig. 1 Location of the Azores, the Archipelago of Madeira, the Selvagens Islands, the Canary Islands, and Cape Verde (a). Close view to the islands of the Madeira Archipelago (b) and the Western Canary Islands (below, right) (c). Tenerife is characterised by the regions of Anaga, Teno, Las Cañadas/Teide, and Dorsal Rift. The taxa of the A. wollastoni group (Kratochwil, 2020) and the centres of their distri-
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.
BRAIN Journal-High Performance Data mining by Genetic Neural Network-Figure 8 . The Comparision of Run Times
<p>That is distinct that dynamic mutation rate or reduction idea for mutation operator is more<br> better of fixed rate. In fact obtain to high accuracy is result of our idea for mutation operator.<br> The number of hidden layer neurone is important problem for NN. The natural selection by<br> GA help finding the number of hidden layer neurone and it progress on duration generations.<br> The structured model of GANN finds better answer than NN but with much run time in<br> simulation. The learning of GA is much better than NN with back propagation because BP is a<br> method based on gradient descend and local optimum is a serious risk for that.<br> We hope that the number of training samples is more accurate without error, the new<br> algorithm is better. Tests show that the combination of genetic algorithms and neural networks to an<br> acceptable level solves the problem of overfitting.</p>
BRAIN Journal-High Performance Data mining by Genetic Neural Network-Figure 7 . Test Accuracy with prograess generation
<p>In the training phase, the neural network weights errors are minimized and network design<br> problem which the objective function to an acceptable level. In test step we have better results<br> because weights of neural network are adjusted by genetic algorithm and back propagation method.<br> Of course achievement to accuracy with 83.5% is reason using of good feature with minimum error.</p>
BRAIN Journal-High Performance Data mining by Genetic Neural Network-Figure 6. Training Accuracy with prograess generation
<p>There are many features will reduce the efficiency of the algorithm and its complexity.<br> Among the methods for selecting the appropriate features, the algorithm is a GA.<br> One of the important parameters for testing methods is accuracy rate on progress generation.<br> In fact accuracy is reverse error in algorithm results. As reader can compare the results of our paper<br> with another works. Figure 4 show that accuracy present for Training step. We achieve to best<br> answers of 800 generation to after generation.</p>
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.