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700 results for “Molecular identification”
FIGURE 3 in Morphological and molecular identification of a new species of Perenniporia (Polyporales, Basidiomycota) in North America
FIGURE 3. Microscopic structures of Perenniporia bostonensis (drawn from the holotype). a. Basidiospores. b. Basidia and basidioles. c. Cystidioles. d. Hyphae from trama. e. Hyphae from subiculum. Bars: a–5 μm; b–e–10 μm.
FIGURE 4 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 4. ML tree based on matK sequences from samples investigated. Dianthus cyathophorus subsp. minae was added as outgroup.
FIGURE 3 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 3. Discriminant analysis based on the 25 considered morphological characters, with groups corresponding to the five subspecies. Axis 1: Eigenvalue 34.93, % variance 77.75; Axis 2: Eigenvalue 5.2509, % variance 11.69. Blue: Dianthus rupicola subsp. aeolicus, pink: D. rupicola subsp. bocchorianus, brown: D. rupicola subsp. hermaeensis, orange: D. rupicola subsp. lopadusanus, green: D. rupicola subsp. rupicola.
FIGURE 2 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 2. Principal components analysis based on the 25 considered morphological characters, with groups corresponding to the five subspecies. PC1: Eigenvalue 193.5, % variance 48.31; PC2: Eigenvalue 69.8597, % variance 17.441. Blue: D. rupicola subsp. aeolicus, pink: D. rupicola subsp. bocchorianus, brown: D. rupicola subsp. hermaeensis, orange: D. rupicola subsp. lopadusanus, green: D. rupicola subsp. rupicola.
FIGURE 1 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 1. Distribution of the studied populations of Dianthus rupicola. Blue: D. rupicola subsp. aeolicus, pink: D. rupicola subsp. bocchorianus, brown: D. rupicola subsp. hermaeensis, orange: D. rupicola subsp. lopadusanus, green: D. rupicola subsp. rupicola.
FIGURE 7 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 7. ML tree based on the combined sequences of the loci trnH-psbA+rpl32-trnL+matK, from samples investigated. Dianthus cyathophorus subsp. minae was added as outgroup.
FIGURE 5 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 5. ML tree based on rpl32-trnL sequences from samples investigated. Dianthus cyathophorus subsp. minae was added as outgroup.
FIGURE 6 in Contribution to the identification of Dianthus rupicola (Caryophyllaceae) subspecies using morphological and molecular approaches
FIGURE 6. ML tree based on trnH-psbA sequences from samples investigated. Dianthus cyathophorus subsp. minae was added as outgroup.
FIGURE 1 in Morphological and molecular identification of a new species of Atraporiella (Polyporales, Basidiomycota) in China
FIGURE 1. Maximum Parsimony strict consensus tree illustrating the phylogeny of Atraporiella yunnanensis and related species in Polyporales based on ITS+nLSU sequences. Branches are labeled with maximum likelihood bootstrap higher than 70%, parsimony bootstrap proportions higher than 50% and Bayesian posterior probabilities more than 0.95 respectively. Clade names follow Binder et al. (2013).
FIGURE 3 in Morphological and molecular identification of a new species of Atraporiella (Polyporales, Basidiomycota) in China
FIGURE 3. Microscopic structures of Atraporiella yunnanensis (drawn from the holotype). a basidiospores. b basidia and basidioles. c hyphae from trama. d hyphae from subiculum. Bars: a—5 μm; b–d—10 μm.
FIGURE 1 in Morphological and molecular identification of Alternaria hedjaroudei sp. nov., a new species in section Panax from Iran
FIGURE 1. Bayesian inference (BI) tree obtained by phylogenetic analysis using a combined ITS, GAPDH, RPB2 and TEF sequences data of Alternaria species from different sections. Bayesian posterior probabilities (BPP) and bootstrap support values from maximum parsimony (MP-BS) above 50% are indicated at the nodes (BPP/MP-BS). The tree was rooted to Stemphylium vesicarium (CBS 191.86). The scale bar indicates the number of expected substitutions per position. The isolates from the current study are in bold.
FIGURE 3. Alternaria hedjaroudei. a–c in Morphological and molecular identification of Alternaria hedjaroudei sp. nov., a new species in section Panax from Iran
FIGURE 3. Alternaria hedjaroudei. a–c, Ascomata formed on PCA culture medium. d–e, Ascomata wall. f–g, Hymenium. h–j, 8-spored mature asci. k, Pseudoparaphyses. l–z, Ascospores. Scale bars 20 µm.
FIGURE 2. Alternaria hedjaroudei. a-d, Colonies after 7 in Morphological and molecular identification of Alternaria hedjaroudei sp. nov., a new species in section Panax from Iran
FIGURE 2. Alternaria hedjaroudei. a-d, Colonies after 7 days on PDA (a), PCA (b), HA (c), and V8–A (d). e–f, Sporulation pattern. g–l, Primary conidiophores. m–o, Secondary conidiophores. p–z, Conidia. Scale bars 25 µm.
Data from: Give me a sample of air and I will tell which species are found from your region – molecular identification of fungi from airborne spore samples
Fungi are a megadiverse group of organisms, they play major roles in ecosystem functioning, and are important for human health, food production, and nature conservation. Our knowledge on fungal diversity and fungal ecology is however still very limited, in part because surveying and identifying fungi is time demanding and requires expert knowledge. We present a method that allows anyone to generate a list of fungal species likely to occur in a region of interest, with minimal effort and without requiring taxonomical expertise. The method consists of using a cyclone sampler to acquire fungal spores directly from the air to an Eppendorf tube, and applying DNA barcoding with probabilistic species identification to generate a list of species from the sample. We tested the feasibility of the method by acquiring replicate air samples from different geographical regions within Finland. Our results show that air sampling is adequate for regional-level surveys, with samples collected >100 km apart varying but samples collected <10 km apart not varying in their species composition. The data show marked phenology, and thus that obtaining a representative species list requires aerial sampling that covers the entire fruiting season. In sum, aerial sampling combined with probabilistic molecular species identification offers a highly effective method for generating a species list of airborne dispersed fungi. The method presented here has the potential to revolutionize fungal surveys, as it provides a highly cost-efficient way to include fungi as a part of large-scale biodiversity assessments and monitoring programs.
FIGURE 2 in A newly recognized species in the Anopheles Hyrcanus Group and molecular identification of related species from the Republic of South Korea (Diptera: Culicidae)
FIGURE 2. Results of amplification of rDNA ITS2 of An. sinensis (lane, progeny brood number): (1) KS8(67), (2) KS8(94); An. lesteri: (3) KS8(59), (4) KS8(88); An. pullus: (5) KS8(76), (6) KS8(86); An. unknown 1: (7) KS8(12), (8) KS7(27); An. unknown 2: (9) KS26(2) and (10) KS4 2(1); (11) positive control, complete ITS2 amplicon of KS8(67), An. sinensis; (12) negative control, no template. M: DNA ladder consisting of lambda DNA digested by Hind III, and phiX174 DNA digested with Hae III (Sigma, St. Louis, MO).
FIGURE 1. Ribosomal DNA ITS2 in A newly recognized species in the Anopheles Hyrcanus Group and molecular identification of related species from the Republic of South Korea (Diptera: Culicidae)
FIGURE 1. Ribosomal DNA ITS2 sequence for five Anopheles Hyrcanus Group species from the Republic of South Korea. Bases in the gray areas are common to all species. Speciesspecific primers and direction of amplification are indicated by arrows: sin = An. sinensis, unk1 = An. unknown 1, pul = An. pullus, unk2 = An. unknown 2, les = An. lesteri. Two numbers are given at the end of the figure: 1) ITS2 length, and 2) total length of amplified fragment, which includes 135 bases from the flanking regions.
FIGURE 4 in A review of the subgenus Euprepiosaurus of Varanus (Squamata: Varanidae): morphological and molecular phylogeny, distribution and zoogeography, with an identification key for the members of the V. indicus and the V. prasinus species groups
FIGURE 4. Maximum parsimony (MP) cladogram based on 548 bp of the mitochondrial 16S ribosomal RNA gene sequences. Values above the nodes represent bootstrap values in percent.
FIGURE 6 in A review of the subgenus Euprepiosaurus of Varanus (Squamata: Varanidae): morphological and molecular phylogeny, distribution and zoogeography, with an identification key for the members of the V. indicus and the V. prasinus species groups
FIGURE 6. Bayesian (PP) reconstruction based on 548 bp of the mitochondrial 16S ribosomal RNA gene sequences. Values above the nodes are Bayesian posterior probabilities.
FIGURE 5 in A review of the subgenus Euprepiosaurus of Varanus (Squamata: Varanidae): morphological and molecular phylogeny, distribution and zoogeography, with an identification key for the members of the V. indicus and the V. prasinus species groups
FIGURE 5. Neighbour-joining (NJ) phylogram based on 548 bp of the mitochondrial 16S ribosomal RNA gene sequences. Values above the nodes represent bootstrap values in percent.
FIGURE 3 in A review of the subgenus Euprepiosaurus of Varanus (Squamata: Varanidae): morphological and molecular phylogeny, distribution and zoogeography, with an identification key for the members of the V. indicus and the V. prasinus species groups
FIGURE 3. Distribution of the members of the V. prasinus species group in relation to significant biogeographic discontinuities within the Indo-Australian Archipelago (We — Weber's line, Ly — Lydekker's line): V. prasinus (1), V. beccarii (2), V. kordensis (3), V. bogerti (4), V. keithhornei (5), V. telenesetes (6), V. macraei (7), V. boehmei (8), V. reisingeri (9).
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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.