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.
2,785
datasets available to search
ShareScore release 0.7.1
Dataset results
2,785 results for “genotypes”
Fig. 11 in Morphological description and multilocus genotyping of Onchocerca spp. in red deer (Cervus elaphus) in Switzerland
Fig. 11. Different body width of one specimen of Onchocerca skrjabini in comparison. Midbody at left, tapering part in the middle, thin anterior body at right. Note Onchocerca typical structure of cuticle with ridges on the surface and striae in medulla in ratio 1: 4.
Fig. 13 in Morphological description and multilocus genotyping of Onchocerca spp. in red deer (Cervus elaphus) in Switzerland
Fig. 13. Onchocerca skrjabini female: cuticular ridges do not meet over the lateral line, they taper and disappear distant from each other.
Fig. 1 in Novel genotypes of Cryptosporidium and Enterocytozoon bieneusi detected in plateau zokors (Myospalax baileyi) from the Tibetan Plateau
Fig. 1. Phylogenetic relationships of Cryptosporidium sp. genotypes identified in the present study and other known genotypes and species on GenBank was inferred by a maximum-likelihood phylogenetic analysis of SSU rRNA gene sequences using the Tamura 3-parameter model and with 500 replicates. The Eimeria (GenBank: U40264.1) were used as the outgroup. The red circles and squares indicate the novel genotypes identified in this study. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 6 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 6. Phylogenetic tree based on the Maximum Likelihood analysis of the species of the Order Onchoproteocephalidea found in Octopus maya constructed on partial large subunit ribosomal gene (28S) (likelihood = – 9067.566753). Bootstrap support values for ML are provided at the nodes; ex = host; the stage of development of the cestode in parentheses.
Fig. 4 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 4. Phylogenetic tree based on the Maximum Likelihood (ML) analysis of the species of the Order Trypanorhyncha found in Octopus maya constructed on partial large subunit ribosomal gene (28S) (likelihood = – 15209.189111). Bootstrap support values for ML are provided at the nodes; ex = host; the stage of development of the cestode in parentheses.
Fig. 3 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 3. Scanning electron microscopy of whole specimens and the detail of scolecis of the cestodes found as parasites of Octopus maya. Trypanorhyncha (A–L): A-C Eutetrarhynchus sp.; D-F Kotorella pronosoma; G-I Nybelinia sp.; J-L Prochristianella sp. Onchoproteocephalidea (M–R): M-N Acanthobothrium sp. O–P Phoreiobothrium sp.; Q-R Prosobothrium sp.
Fig. 2 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 2. Schematic drawings and photographs of the stained specimens of cestode parasitizing Octopus maya. Trypanorhyncha (A–D): A- Eutetrarhynchus sp.; B. Kotorella pronosoma; C- Nybelinia sp.; D- Prochristianella sp. Onchoproteocephalidea (E–G): E- Acanthobothrium sp.; F- Phoreiobothrium sp.; G- Prosobothrium sp.- Abbreviations: as = apical sucker; bot = bothridia cc = calcareous corpuscles; lo = loculi; pb = pars bulbosa; pbo = pars bothrialis; ppb = pars postbulbosa; ps = pedunculus scolecis; pv = pars vaginalis; sc = scolex; sp = septa; st = strobilo; vel = velum.
Fig. 5 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 5. Phylogenetic tree based on the Maximum Likelihood analysis of the species of the Order Trypanorhyncha found in Octopus maya constructed on partial small subunit ribosomal gene (18S) (likelihood = – 7987.787948). Bootstrap support values for ML are provided at the nodes; ex = host; the stage of development of the cestode in parentheses.
Fig. 1 in Epidemiology of a major honey bee pathogen, deformed wing virus: potential worldwide replacement of genotype A by genotype B
Fig. 1. Relative proportion of DWV genotype A and B reads in publicly available NCBI transcriptome datasets of honey bees, V. destructor mites and bumble bees.
Fig. 2 in Epidemiology of a major honey bee pathogen, deformed wing virus: potential worldwide replacement of genotype A by genotype B
Fig. 2. First published records of DWV genotype B in Varroa destructor (closed box) or in Apis mellifera (red boxes: pre-2010; open boxes: 2010 onwards) from a country or geographic region; citations are in Table 3. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in Epidemiology of a major honey bee pathogen, deformed wing virus: potential worldwide replacement of genotype A by genotype B
Fig. 4. Temporal change in the proportion of DWV-A to DWV-B across our own datasets (a) (prevalence in Fig. 3); in published datasets (b) (UK data in Kevill et al. (2021); continental USA data in Ryabov et al. (2017); and Hawaii data in Grindrod et al. (2021)); and (c) in NCBI NGS honey bee datasets of Fig. 1 presented by geographic origin.
Fig. 3 in Epidemiology of a major honey bee pathogen, deformed wing virus: potential worldwide replacement of genotype A by genotype B
Fig. 3. Temporal change in the prevalence of DWV-A and DWV-B in honey bees in three original datasets separated by 5–6 years from the same sampling localities in the UK (individual honey bees collected at flowers), Germany (pooled honey bees from collapsing colonies) and Italy (NGS reads from pooled or individual honey bees); Germany 2019 samples were summed 2019–2020; Italy 2011 samples were summed 2009–2013 and Italy 2019 samples were summed 2018–2020.
Fig. 3 in Prevalence and new genotypes of Enterocytozoon bieneusi in wild rhesus macaque (Macaca mulatta) in China: A zoonotic concern
Fig. 3. Sequence variation in the ITS region of the rRNA gene of Enterocytozoon bieneusi isolates from rhesus macaque. The ITS sequences of 5 known genotypes (D, PL9, CAF4, EbpC, and SCC-2) and 8 novel genotypes (Mul6 to 13) identified in this study, were aligned with each other. The dots and transverse lines indicate base identities and deletions, respectively, relative to the ITS sequence of genotype D.
Fig. 2. Phylogenetic relationship among the Enterocytozoon bieneusi groups. The relationship between the E in Prevalence and new genotypes of Enterocytozoon bieneusi in wild rhesus macaque (Macaca mulatta) in China: A zoonotic concern
Fig. 2. Phylogenetic relationship among the Enterocytozoon bieneusi groups. The relationship between the E. bieneusi genotypes identified in this study and other known genotypes deposited in GenBank was inferred by neighbor-joining analysis of ITS sequences based on genetic distance using the Kimura-2-parameter model. The numbers on the branches represent percent bootstrapping values from 1000 replicates, with more than 50% shown in the tree. Each sequence is identified by its accession number, genotype designation, and host origin. Genotypes marked with black dot are identified in this study.
Fig. 1 in Surveillance and genotype characterization of zoonotic trypanosomatidae in Didelphis marsupialis in two endemic sites of rural Panama
Fig. 1. Map showing the communities of Las Pavas (LP) (top set of images) and Trinidad de Las Minas (TM) (bottom set of images) with the number of opossums captured and infected with T. cruzi in the 3 collection sites in each community. A. Map with the geographic location of the LP and TM communities in the country of Panama. Satellite view of the P: Peridomicile (B), R1: remnant 1 (C) and R2: remnant 2 (D) collection site each with its 4 transects in the LP community. Satellite view of the P: Peridomicile (E), R1: remnant 1 (F) and R2: remnant 2 (G) collection site each with its 4 transects in the TM community.
Fig. 1 in Molecular detection and characterization of a novel Theileria genotype in Dama Gazelle (Nanger dama)
Fig. 1. Phylogenetic analyses of sequence data for 393bp 18S rRNA gene of Theileria spp. in gazelles by Maximum Likelihood method with bootstrap of 1000 replications using MEGA software version10.
Fig. 1 in From wildlife to humans: The global distribution of Trichinella species and genotypes in wildlife and wildlife-associated human trichinellosis
Fig. 1. Sylvatic life cycle and potential transmission routes of Trichinella spp. Created with BioRender.com.
Fig. 3 in From wildlife to humans: The global distribution of Trichinella species and genotypes in wildlife and wildlife-associated human trichinellosis
Fig. 3. Global distribution of sylvatic Trichinella species and genotypes adapted from Pozio (2016); Gottstein et al. (2009).
Figure 2 in Expression analysis of phosphate induced genes in contrasting maize genotypes for phosphorus use efficiency
Figure 2. Phylogenetic analysis based on nucleotide sequences of plant phosphate transporters. Plant phosphate transporters were assembled using ClustalX, and NJ-plot was used to develop the tree. Abbreviations are shown for respective transporters: ZmPTs: Zea mays phosphate transporters;AtPT: Arabidopsis thaliana phosphate transporters;LePT: Lycopersicon esculentum phosphate transporters; OsPT: Oryza sativa phosphate transporters; HvPT: Hordeum vulgare phosphate transporters; SbPT: Sorghum bicolor phosphate transporters.
Figure 1. A – P in Expression analysis of phosphate induced genes in contrasting maize genotypes for phosphorus use efficiency
Figure 1. A – P-efficient and P-inefficient maize plants grown in the Cerrado under low Pi conditions.B – Dry weight of maize genotypes. C – Root/shoot ratio of maize plants. D and E – Phosphorus content. F – Anthocyanin concentration. G and H – Units of APA activity. B to H, The maize plants were grown in hydroponics culture in the presence (250 µM Pi - gray bar) or absence (0 µM Pi – black bar) of phosphate harvested after 15 days in treatment. Each bar is the mean of three replicates with a standard deviation.
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.