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.
3,761
datasets available to search
ShareScore release 0.9.0
Dataset results
3,761 results for “phylogenetic relationship”
Figs 7–13. 7a in Phylogenetic relationships of family groups in Pentatomoidea based on morphology and DNA sequences (Insecta: Heteroptera)
Figs 7–13. 7a. Antennal segments of Megymenum sp.; 7b. antennal segments of Eumenotes obscura; 7c. flattened 2nd antennal segment of E. obscura in cross-section; 7d. antennal segments of Natalicola pallidens; 7e. flattened 2nd antennal segment of N. pallidens in cross-section; 7f. antennal segments of Phloea corticata. 8. Thaumastella namaquensis (Thaumastellidae): lygaeid type of head (Štys, 1964a); humeral angles not developed. 9. Lestonia haustorifera (Lestoniidae). Scutellum long almost attaining apex of abdomen but not covering conexivum and corium of hemelytra; base of corium expanded. 10. Canopus caesus (Canopidae), dorsal view. Well-developed scutellum, completely covering abdominal dorsum and hemelytra; spheroid form. 11. Body foliations: 11a. Phloea corticata (Phloeidae), female; 11b. Serbana borneensis (Phloeidae), male. 12. Garsauriella haglundi (Cydnidae). Corium subdivided by a medial longitudinal fracture (mlf = median longitudinal fracture). 13. Tessaratoma papillosa (Tessaratomidae). Hindwing stridulitrum. (S = stridulitrum)
Figs 2–6. 2a in Phylogenetic relationships of family groups in Pentatomoidea based on morphology and DNA sequences (Insecta: Heteroptera)
Figs 2–6. 2a. Poecilometis sp. (Pentatomidae): post-ocular tubercles and ''neck'' absent; first antennal segment long; pronotum with humeral and posterior angles developed; claval comissure absent; 2b. Trisecus pictus (Idiostolidae): post-ocular tubercles absent; antenniferous tubercles lateral on head partially obscured by mandibular plates; 2c. Trisecus pictus (Idiostolidae): claval comissure well developed. 3. Urolabida sp. (Urostylididae). Base of head forming a ''neck''; first antennal segment long. 4a. Saileriola sandakanensis (Saileriolidae): antenniferous tubercles lateral on head, visible in dorsal view; head conical; ocelli closer; 4b. S. sandakanensis: claval comissure obsolete; 4c. Amnestus sp. (Cydnidae): claval comissure reduced. 5. Ceratocoris sp. (Plataspididae). Antenniferous tubercles ventral on head, completely covered by the development of mandibular plates. 6. Canopus caesus (Canopidae), ventral view. Prosternum deeply sulcate and strongly carinate; trichobothria longitudinal.
FIGURE 6B in Phylogenetic relationships and biological features reveal that male Ostrinia furnacalis (Lepidoptera: Crambidae) in Northeast China can be categorized into postmedial line-based clades
FIGURE 6B. Male dynamics of Ostrina furnacalis clades I, II & III in various field in 2016.
FIGURE 6A in Phylogenetic relationships and biological features reveal that male Ostrinia furnacalis (Lepidoptera: Crambidae) in Northeast China can be categorized into postmedial line-based clades
FIGURE 6A. Male dynamics of Ostrinia furnacalis clades in 2015 (I~III =Clade I, II&III).
Data from: Extracting phylogenetic signal from phylogenomic data: higher-level relationships of the nightbirds (Strisores)
A well-resolved phylogeny would facilitate study of adaptation to nocturnality in the avian superorder Strisores, a group that includes both nocturnal and diurnal lineages. Based on previous estimates, it could be hypothesized that there were multiple independent origins of nocturnality in this group. In order to refine the Strisores phylogeny, we generated genome-scale datasets of 2,289 – 4,243 ultra-conserved elements for 23 taxa representing all major living lineages in the group. Among the considerations for using genome-scale, molecular sequence data in phylogenomic analysis are issues related to GC content, GC variance and their effects on model selection. In this study, we employed a variety of analytical techniques to empirically investigate those issues in our data, as well as biases and errors resulting from alignment trimming, taxon selection and matrix completeness. Extensive analyses revealed conflict within the data, especially in regard to variation in GC content, that would not have been detected with more cursory study. Our results indicate that readily available models of molecular evolution are insufficient to encapsulate all phenomena present in genome-scale matrices, and that this problem may be at the root of many current issues in phylogenomic analysis. The analytical methods employed in this study are relevant to phylogenomic analysis of any large, heterogeneous matrix. In conclusion, we present a strongly supported estimate of the Strisores tree and discuss potential evolutionary pathways of nocturnality in this clade.
Relationships of song structure to phylogenetic history, habitat, and morphology in the vireos, greenlets, and allies (Passeriformes: Vireonidae)
<p>Acoustic signals show immense variation among passerines, and several hypotheses have been proposed to explain this diversity. In this study, we tested, for the first time, the relationships of song structure to phylogeny, habitat type, and morphology in the vireos and allies (Vireonidae). Every measure of song structure considered in this study had moderate and significant phylogenetic signal. Furthermore, two song-constraining morphological traits, bill shape and body mass, also exhibited significant phylogenetic signal. Song length showed the largest within-clade similarity; longer songs were highly conserved in part of the greenlet (<i>Hylophilus</i>) clade, whereas shorter songs characterized the remaining seven genera. We found no differences in song structure among vireonids living in different habitat types. However, vireonids with shorter, stouter bills and larger bodies sang songs with lower minimum and maximum peak frequency, compared with species with longer, thinner bills and smaller bodies. We conclude that Vireonidae song evolution is driven partially by phylogenetically conserved morphological traits. Our findings support the phylogenetic signal and morphological constraints hypotheses explaining structural diversity in avian acoustic signals.</p>
Figure 2 from: Valuyskikh OE, Teteryuk LV, Pylina YI, Sushentsov OE, Martynenko NA, Shadrin DM (2020) Phylogenetic relationships and status of taxa of Pulsatilla uralensis and P. patens s.str. (Ranunculaceae) in north-eastern European Russia. PhytoKeys 162: 113-130. https://doi.org/10.3897/phytokeys.162.53361
Figure 2 Pulsatilla patens s.str. (L.) Mill. (P. patens subsp. patens) A–C flowers with different perianth colour D herbarium specimen of a flowering shoot and typical leaf blade E plant just after flowering with unripe fruits. The photographs show sample number 5 (A, D), sample number 15 (B) and sample number 18 (C).
Figure 1 from: Valuyskikh OE, Teteryuk LV, Pylina YI, Sushentsov OE, Martynenko NA, Shadrin DM (2020) Phylogenetic relationships and status of taxa of Pulsatilla uralensis and P. patens s.str. (Ranunculaceae) in north-eastern European Russia. PhytoKeys 162: 113-130. https://doi.org/10.3897/phytokeys.162.53361
Figure 1 Distribution map of the sampling sites of P. patens s.str. and P. uralensis in north-eastern European Russia and the Urals. The colour on the diagrams indicates the colour of the perianth in different taxa: blue-violet – P. patens s.str., yellow – P. uralensis. The locations (I–X) and samples correspond to Table 2.
Supplementary material 2 from: Valuyskikh OE, Teteryuk LV, Pylina YI, Sushentsov OE, Martynenko NA, Shadrin DM (2020) Phylogenetic relationships and status of taxa of Pulsatilla uralensis and P. patens s.str. (Ranunculaceae) in north-eastern European Russia. PhytoKeys 162: 113-130. https://doi.org/10.3897/phytokeys.162.53361
Informative nucleotide sites in cpDNA (matK, rbcL) for Pulsatilla
Figure 4 from: Valuyskikh OE, Teteryuk LV, Pylina YI, Sushentsov OE, Martynenko NA, Shadrin DM (2020) Phylogenetic relationships and status of taxa of Pulsatilla uralensis and P. patens s.str. (Ranunculaceae) in north-eastern European Russia. PhytoKeys 162: 113-130. https://doi.org/10.3897/phytokeys.162.53361
Figure 4 Combined Maximum Likelihood (ML) and Bayesian Inference (BI) phylogenetic tree (rbcL+ matK+ITS2) of 37 Pulsatilla samples and 10 outgroup samples. All new 28 samples of P. patens s.str. and P. uralensis are marked with dots. Outgroups include Anemone, Anemoclema, Clematis and Hepatica species. ML bootstrap support (left) and BI posterior probability (right) are recorded along branches. Values below 50% are not shown.
Figure 3 from: Valuyskikh OE, Teteryuk LV, Pylina YI, Sushentsov OE, Martynenko NA, Shadrin DM (2020) Phylogenetic relationships and status of taxa of Pulsatilla uralensis and P. patens s.str. (Ranunculaceae) in north-eastern European Russia. PhytoKeys 162: 113-130. https://doi.org/10.3897/phytokeys.162.53361
Figure 3 Pulsatilla uralensis (Zamelis) Tzvelev A–C flowers with different perianth colour D herbarium specimen of a flowering plant and different leaf blades E fruiting plant. The photographs show sample number 6 (B), sample number 7 (C) and sample number 25 (D).
Supplementary material 1 from: Valuyskikh OE, Teteryuk LV, Pylina YI, Sushentsov OE, Martynenko NA, Shadrin DM (2020) Phylogenetic relationships and status of taxa of Pulsatilla uralensis and P. patens s.str. (Ranunculaceae) in north-eastern European Russia. PhytoKeys 162: 113-130. https://doi.org/10.3897/phytokeys.162.53361
Maximum Likelihood and Bayesian Inference phylogenetic tree (rbcL)
Figure 2 from: Xue B, Chen Y, Saunders RMK (2020) Phylogenetic relationships of 'Polyalthia' in Fiji. PhytoKeys 165: 99-113. https://doi.org/10.3897/phytokeys.165.57094
Figure 2 Type specimens of the four Fijian Huberantha species AHuberantha amoena (A.C. Smith 6423, A) BH. capillata (A.C. Smith 4581, A) CH. loriformis (J.W. Gillespie 3639, GH) DH. vitiensis (B. Seemann 4, K).
Figure 1 from: Xue B, Chen Y, Saunders RMK (2020) Phylogenetic relationships of 'Polyalthia' in Fiji. PhytoKeys 165: 99-113. https://doi.org/10.3897/phytokeys.165.57094
Figure 1 Bayesian 50% majority-rule consensus tree inferred from combined data of matK, rbcL and trnL-F under three-partitioned models. Numbers at the nodes indicate BI posterior probabilities and ML bootstrap values (> 50%). Species names of previous Fijian Polyalthia are in bold.
Figure 5 from: Sun G, Zhao C, Xia T, Wei Q, Yang X, Feng S, Sha W, Zhang H (2020) Sequence and organisation of the mitochondrial genome of Japanese Grosbeak (Eophona personata), and the phylogenetic relationships of Fringillidae. ZooKeys 995: 67-80. https://doi.org/10.3897/zookeys.995.34432
Figure 5 The phylogenetic tree generated for 17 species of Fringillidae. The values indicated at the nodes are Bayesian posterior probabilities (left) and ML bootstrap proportions (right).
Figure 1 from: Sun G, Zhao C, Xia T, Wei Q, Yang X, Feng S, Sha W, Zhang H (2020) Sequence and organisation of the mitochondrial genome of Japanese Grosbeak (Eophona personata), and the phylogenetic relationships of Fringillidae. ZooKeys 995: 67-80. https://doi.org/10.3897/zookeys.995.34432
Figure 1 Circular map of the mitochondrial genome of Eophona personata. tRNAs are denoted as one-letter symbols according to IUPAC-IUB single-letter amino acid codes; L1 = UUR, L2 = CUN, S1 = UCN, S2 = AGY.
FIGURE 2 in A new species of the cardinalfish genus Apogon (Teleostei, Apogonidae) from the southern Red Sea and Indian Ocean with comments on phylogenetic relationships within the Apogonini
FIGURE 2. Distribution map of Apogon fugax n. sp. Red circle = holotype; black squares = paratypes.
Fig. 22 in Revision of the morphology, phylogenetic relationships, behaviour and diversity of the Iberian and Italian ant-like Tachydromia Meigen, 1803 (Diptera: Hybotidae)
Fig. 22. Image obtained by scanning electron microscope (SEM) of the micropterous wing of a male of Tachydromia apterygon Plant & Deeming, 2006. Scale bar: 10 μm.
Data from: Relationships among taxonomic, functional, and phylogenetic ant diversity across the biogeographic regions of Europe
Understanding how different biodiversity components are related across different environmental conditions is a major goal in macroecology and conservation biogeography. We investigated correlations among alpha and beta taxonomic (TD), phylogenetic (PD), and functional diversity (FD) in ant communities in the five biogeographic regions most representative of western Europe; we also examined the degree of niche conservatism. We combined data from 349 ant communities composed of 154 total species, which were characterized by 10 functional traits and by phylogenetic relatedness. We computed TD, PD, and FD using the Rao quadratic entropy index, which allows each biodiversity component to be partitioned into α and β diversity within the same mathematical framework. We ran generalized least squares and multiple matrix regressions with randomization to investigate relationships among the diversity components. We used Pagel's λ test to explore niche conservatism in each biogeographic region. At the alpha scale, TD was consistently, positively related to PD and FD, although the strength and scatter of this relationship changed among the biogeographic regions. Meanwhile, PD and FD consistently matched up across regions. Accordingly, we found similar degrees of niche conservatism across regions. Nonetheless, these alpha-scale relationships had low coefficients of determination. At the beta scale, the three diversity components were highly correlated across all regions (especially TD and FD, as well as PD and FD). Our results imply that the different diversity components, and especially PD and FD, are consistently related across biogeographic regions and analytical scale. However, the alpha-scale relationships were quite weak, suggesting environmental factors might influence the degree of association among diversity components at the alpha level. In conclusion, conservation programs should seek to preserve functional and phylogenetic diversity in addition to species richness, and this approach should be applied universally, regardless of the biogeographic locations of the sites to be protected.
Fig. 2 in Taxonomic revision and phylogenetic relationships of Dasyloricaria Isbrücker & Nijssen, 1979 (Siluriformes: Loricariidae), with description of a new species
Fig. 2. Map of northwestern South America (Colombia, Panama and Venezuela) showing the distributions of species of Dasyloricaria. Black dots: Dasyloricaria filamentosa; black squares: D. paucisquama; black triangles: D. latiura; white circle: holotype of Loricaria filamentosa seminuda (= Dasyloricaria filamentosa); white square: holotype of D. paucisquama; white triangle: lectotype of Loricaria filamentosa latiura; and white star: holotype of Loricaria capetensis (= Dasyloricaria latiura) and holotype of L. tuyrensis (= Dasyloricaria latiura).
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.