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15,277 results for “GENETICS”
Fig. 1 in Evaluation of field dispersal and survival capacity of the genetic sexing strain Tapachula-7 of Anastrepha ludens (Diptera: Tephritidae)
Fig. 1. Contours of displacement of the SMR strain (lef) and Tap-7 strain (right) of Anastrepha ludens inside the field plot. The density of the flies at each contour is indicated by the number.
Fig. 2 in Genetically modified maize resistant to corn earworm (Lepidoptera: Noctuidae) in Sinaloa, Mexico
Fig. 2. Percentage of corn ears ear damaged by Helicoverpa zea in Agrisure® VipteraTM 3111, AgrisureTM 3000 GT, and their respective isolines at El Dorado, Culiacan, and Navolato (Sinaloa, Mexico). 2012. Genetically modified hybrids and their respective isolines followed by the same letter do not differ significantly (LSD; P> 0.05). ic = insecticide control
Fig. 1 in Genetically modified maize resistant to corn earworm (Lepidoptera: Noctuidae) in Sinaloa, Mexico
Fig. 1. Percentage of corn ears damaged by Helicoverpa zea in AgrisureTM 3000 GT, Agrisure® VipteraTM 3110, and their respective isolines at Oso Viejo, Culiacan (Sinaloa, Mexico) during 2011.Genetically modified hybrids and their respective isolines followed by the same letter do not differ significantly (LSD; P> 0.05). ic = insecticide control.
Fig. 2. Canonical discriminant functional analyses showing 3 in Life history traits of three cryptic species Asia I, Asia II-1 and Asia II-7 of Bemisia tabaci (Hemiptera: Aleyrodidae) reconfirm their genetic identities
Fig. 2. Canonical discriminant functional analyses showing 3 genetic groups of Bemisia tabaci species complex.
Fig. 1 in Life history traits of three cryptic species Asia I, Asia II-1 and Asia II-7 of Bemisia tabaci (Hemiptera: Aleyrodidae) reconfirm their genetic identities
Fig. 1. Component analysis (PCA) showing the clustering of genetic groups of Bemisia tabaci species complex.
Tissue-aware interpretation of genetic variants advances the etiology of rare diseases
<p>Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a<br>few tissues and organs. However, variant effect prediction tools that aim to identify<br>pathogenic variants are typically oblivious to tissue contexts. Here we report a machine-<br>learning framework, denoted ‘Tissue Risk Assessment of Causality by Expression for<br>variants’ (TRACEvar, https://netbio.bgu.ac.il/TRACEvar/), that offers two advancements.<br>First, TRACEvar predicts pathogenic variants that disrupt the normal physiology of specific<br>tissues. This was achieved by creating 14 tissue-specific models that were trained on over<br>14,000 variants and combined 84 attributes of genetic variants with 495 attributes derived<br>from tissue omics. TRACEvar outperformed 10 well-established and tissue-oblivious variant<br>effect prediction tools. Second, the resulting models are interpretable, thereby illuminating<br>variants' mode-of-action. Application of TRACEvar to variants of 52 rare-disease patients<br>highlighted pathogenicity mechanisms and relevant disease processes. Lastly, interpretation<br>of large-scale models revealed that top-ranking determinants of pathogenicity included<br>attributes of disease-affected tissues, particularly cellular process activities. Hence, tissue<br>contexts and interpretable machine-learning models can greatly enhance the etiology of rare<br>diseases.</p> <p>Article link: https://www.embopress.org/doi/full/10.1038/s44320-024-00061-6</p> <p> </p>
Figure 8 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 8. TCS network of the studied S. limbata and their individuals (numbers indicated the populations based on Table 1).
Figure 6 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 6. STRUCTURE analysis of the studied populations, which revealed the best number of K=7 (numbers indicated the populations based on Table 1).
Figure 5 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 5. NJ tree of the evaluated populations and their individuals based on ISSR data (numbers indicated the populations based on Table 1).
Figure 4 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 4. UPGMA tree of the studied populations and their members according to ISSR data (numbers indicated the populations based on Table 1).
Figure 2 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 2. PCA plot of the evaluated populations and their individuals (numbers indicated populations according to Table 1).
Figure 7 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 7. Reticulation dendrogram of the studied populations that indicating gene flow among. Abbreviations: Arak (1- 3), Sangak (4-6), Semnan (7-9), Vidar (10-12), Ahovan (13-15), Zarandiyeh (16-18), Ghoochan (19-21) and Lashkarak (22-24).
Figure 1 in Genetic variability and population structure of some Iranian Salvia limbata C. A. Mey. populations
Figure 1. Distribution map of the investigated populations of S. limbata (numbers indicated populations according to Table 1).
Fig. 2 in Soluble proteins in Messor structor (Latreille, 1798) (Hymenoptera: Formicidae) populations from Bulgaria - genetic variability and possible usage as population-genetic markers
Fig. 2. Spectrum of soluble proteins of M. structor workers (7.5% PAGE): a. Elenovo population; b. Tsalapitsa population.
Fig. 3. a in Soluble proteins in Messor structor (Latreille, 1798) (Hymenoptera: Formicidae) populations from Bulgaria - genetic variability and possible usage as population-genetic markers
Fig. 3. a. UPGMA dendrogram (Sneath et al. 1973); b. Neighbour-joining dendrogram (Saitou & Nei 1987).
Fig. 1 in Morphological and genetic evidence for the synonymy of Reticulitermes species: Reticulitermes dichrous and Reticulitermes guangzhouensis (Isoptera: Rhinotermitidae)
Fig. 1. Photomicrographs of dorsal (A, D, E, F, I, and J), ventral (B and G), and lateral (C and H) views of Reticulitermes dichrous (A to E) and Reticulitermes guangzhouensis (F to J) soldier heads and pronotums.
Fig. 4 in Morphological and genetic evidence for the synonymy of Reticulitermes species: Reticulitermes dichrous and Reticulitermes guangzhouensis (Isoptera: Rhinotermitidae)
Fig. 4. Maximum likelihood phylogenetic tree of Reticulitermes guangzhouensis and Reticulitermes dichrous relative to other Reticulitermes species based on the 16S rRNA gene. Bootstrap values are indicated at the nodes and represent 1,000 pseudoreplicates.
Fig. 3 in Morphological and genetic evidence for the synonymy of Reticulitermes species: Reticulitermes dichrous and Reticulitermes guangzhouensis (Isoptera: Rhinotermitidae)
Fig. 3. Maximum likelihood phylogenetic tree of Reticulitermes guangzhouensis and Reticulitermes dichrous relative to other Reticulitermes species based on the COII gene. Bootstrap values are indicated at the nodes and represent 1,000 pseudoreplicates.
Fig. 2 in Morphological and genetic evidence for the synonymy of Reticulitermes species: Reticulitermes dichrous and Reticulitermes guangzhouensis (Isoptera: Rhinotermitidae)
Fig. 2. Cluster dendrogram of 12 populations of Reticulitermes guangzhouensis and 8 populations of Reticulitermes dichrous.
Fig. 1 in Effect of genetically modified Bt maize in an artificial diet on the survival of Cydia pomonella (Lepidoptera: Tortricidae)
Fig. 1. Probit response on log Bt concentration of Cydia pomonella larvae reared on a diet containing maize where the responses were: (A) larval mortality Y = 2.980 + 1.27(X); (B) delayed larval development, Y = 3.789 + 1.886(X) for experiment 1 and Y = 2.840 + 1.886(X) for experiment 2; (C) larvae leaving the diet, Y = 3.595 + 0.681(X); (D) total response or response A + B + C, Y = 4.133 + 2.344(X) for experiment 1 and Y = 3.592 + 2.344(X) for experiment 2. Y is the probit response and X is the log Bt concentration.
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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.