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40 results for “internal genes”
USEARCH Clustering Data for the Influenza Internal Genes
<p>These are the aligned sequence clusters and centroid datasets for the USEARCH clustering of the influenza A internal genes. </p>
Single-Stranded DNA with Internal Base Modifications Mediates Highly Efficient Gene Insertion in Primary Cells
<p>The manuscript describes the use of ssDNA with chemical modifications in internal bases to improve gene insertion. The dataset contains an excel file with the data corresponding to the figures in this manuscript. In addition, it has results from next-generation sequencing used in Figure 2B. </p>
datset of "Networks and genes modulated by posterior hypothalamic stimulation in patients with aggressive behaviours: Analysis of probabilistic mapping, normative connectomics, and atlas-derived transcriptomics of the largest international multi-centre dataset"
<p>This dataset accompanies the manuscript:<br> "Networks and genes modulated by posterior hypothalamic stimulation in patients with aggressive behaviours: Analysis of probabilistic mapping, normative connectomics, and atlas-derived transcriptomics of the largest international multi-centre dataset."<br> DOI: (https://doi.org/10.1101/2022.10.29.22281666)</p> <p>by</p> <p>Flavia Venetucci Gouveia1,2,3*†,Jürgen Germann4,5†, Gavin JB Elias4,5, Alexandre Boutet4,6, Aaron Loh4,5, Adriana Lucia Lopez Rios7,8, Cristina V Torres Diaz9, William Omar Contreras Lopez10,11, Raquel CR Martinez3,12, Erich T Fonoff13, Juan C Benedetti-Isaac14, Peter Giacobbe 2,15,16, Pablo M Arango Pava17, Han Yan5,18, George M Ibrahim5, 18,19,20, Nir Lipsman2,5,15, Andres M Lozano4,5, Clement Hamani2,5,15*</p> <p>1. Neuroscience and Mental Health, Hospital for Sick Children Research Institute; Toronto, Canada <br> 2. Sunnybrook Research Institute; Toronto, Canada<br> 3. Division of Neuroscience, Sírio-Libanês Hospital; São Paulo, Brazil<br> 4. Division of Neurosurgery, Department of Surgery, University Health Network, Toronto, Canada<br> 5. Division of Neurosurgery, Department of Surgery, University of Toronto; Toronto, Canada<br> 6. Joint Department of Medical Imaging, University of Toronto; Toronto, Canada<br> 7. Department of Functional and Stereotactic Neurosurgery, University Hospital San Vicente Fundación,<br> Medellín, Colombia<br> 8. Department of Functional and Stereotactic Neurosurgery, San Vicente Fundación, Rionegro, Colombia<br> 9. Department of Neurosurgery, University Hospital La Princesa; Madrid, Spain<br> 10. Nemod Research Group, Universidad Autónoma de Bucaramanga; Bucaramanga, Colombia<br> 11. Division of Functional Neurosurgery, Department of Neurosurgery, FOSCAL Clinic; Bucaramanga,<br> Colombia<br> 12. LIM 23, Institute of Psychiatry, School of Medicine, University of São Paulo; São Paulo, Brazil<br> 13. Department of Neurology, Integrated Clinic of Neuroscience, School of Medicine, University of São Paulo;<br> São Paulo, Brazil.<br> 14. Stereotactic and Functional Neurosurgery Division of the International Misericordia Clinic; Barranquilla,<br> Colombia<br> 15. Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre; Toronto, Canada<br> 16. Department of Psychiatry, University of Toronto; Toronto, Canada<br> 17. Servicio de Neuocirugia Funcional y Esterotaxia, Clinica Comuneros Bucaramanga, Clinica Desa y Clinica<br> Dime Neurocardiovascular de Cali; Clinica Nueva del Lago, Bogota, Colombia.<br> 18. Division of Neurosurgery, The Hospital for Sick Children; Toronto, Canada<br> 19. Institute of Biomedical Engineering, University of Toronto; Toronto, Canada<br> 20. Institute of Medical Science, University of Toronto; Toronto, Canada<br> † Flavia Venetucci Gouveia and Jürgen Germann contributed equally to this work and share first authorship.</p> <p>* Corresponding Author: Dr. Flavia Venetucci Gouveia. Neuroscience and Mental Health, Hospital for Sick Children Research Institute. 686, Bay Street, Toronto, ON, M5G 0A4, Canada. flavia.venetuccigouveia@sickkids.ca<br> * Corresponding Author: Dr. Clement Hamani. Sunnybrook Research Institute. 2075 Bayview Ave, S126. Toronto, ON, M4N3M5, Canada. clement.hamani@sunnybrook.ca</p> <p>It contains a zip folder ("estimated_binary_Volume_of_Tissue_Activated.zip") with one file (in nii.gz format) per patient estimating the Volume of Activated Tissue for that patient (the estimated 'reach' of the active DBS stimulation) and a demographics file.<br> The case numbers are identical to Table 1 in the manuscript.</p>
International Observational Study of Intranasal 15-Gene AAV9-PHP.eB Therapy for Children With Chronic Hypoxic-Ischemic Encephalopathy (Cerebral Palsy)
ClinicalTrials.gov study NCT07264166. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Supplementary material 2 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Component data at the four successive thresholds used to illustrate Figure 5: Explanation note: Component data are used to illustrate the structure of the subset of Bactrocera carambolae and Bactrocera dorsalis populations. The highest Betweenness-centrality is highlighted in blue.
Supplementary material 1 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Component data at the five successive thresholds used to illustrate Figure 4: Explanation note: Component data are used to illustrate the structure of the subset of Bactrocera carambolae populations. The Highest Betweenness-centrality is highlighted in blue.
Supplementary material 4 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Comparisons among three different the individual admixture plots: Explanation note: Comparisons among the individual admixture plots of 289 individuals, for K = 3, considering correlated allele frequency, uncorrelated allele frequency, and missing data as recessive homozygotes for the null alleles, respectively.
Supplementary material 3 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Component data at the four successive thresholds used to illustrate Figure 6: Explanation note: Component data are used to illustrate the structure of the subset of the Salaya5 strain and wild populations. The highest Betweenness-centrality is highlighted in blue.
Data from: Utility of internally transcribed spacer region of rDNA (ITS) and β-tubulin gene sequences to infer genetic diversity and migration patterns of Colletotrichum truncatum infecting Capsicum spp.
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Data from: Expansion of genotypic diversity and establishment of 2009 H1N1 pandemic-origin internal genes in pigs in China
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Figure 5 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Figure 5 - Simplified network of Bactrocera carambolae and Bactrocera dorsalis groups, and the sequential disconnection of the network. The network was constructed using eight SSRs. Scanning was done for decreasing thresholds A is the fully connected network B is the percolation threshold (Dp = 0.20, with all links corresponding to distances superior to Dp excluded). DP, JK, and NT are connecting between Bactrocera carambolae and Bactrocera dorsalis groups. Red dashed lines with number are corresponded to the threshold values, revealing serial disconnection of the network C is the lowest threshold (thr = 0.15).
Figure 4 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Figure 4 - Simplified network of seven Bactrocera carambolae populations, and the sequential forms of cluster. The network was constructed using eight SSRs. Scanning was done for decreasing thresholds A is the fully connected network B is the percolation threshold (Dp = 0.52, with all links corresponding to distances superior to Dp excluded). JK plays an important role connecting between native and introduced populations C–D are the lower thresholds chosen (thr = 0.40 and 0.15, respectively) to reveal sub-structured network.
Figure 3 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Figure 3 - The individual admixture plot for K = 3. Each bar reveals a single individual. Each color of bars represents each genetic cluster. Samples of Bactrocera carambolae belong to clusters 2 and 3 (green and blue, respectively) while samples of Bactrocera dorsalis belong to cluster 1 (red). Potential hybrids have a proportion of genetic cluster (Q) between 0.100 to 0.900 (0.100 ≤ Q ≤ 0.900) as identified with asterisk (*).
Figure 1 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Figure 1 - Sampling collections of Bactrocera carambolae and Bactrocera dorsalis in this study. Seven populations of Bactrocera carambolae (blue dots) were collected from Southeast Asia and Suriname. Three populations of Bactrocera dorsalis (red dots) were sampled from East and Southeast Asia. Two other unidentified populations (purple dots) were included. Information for each population is described in Table 1.
Figure 6 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Figure 6 - Simplified network of the SY5 strain and wild populations, and the sequential disconnection of the network. The network was constructed using seven SSRs. Scanning was done for decreasing thresholds A is the fully connected network B is the percolation threshold (Dp = 0.23, with all links corresponding to distances superior to Dp excluded). DP, JK, and NT are connecting between Bactrocera carambolae and Bactrocera dorsalis groups C is the lowest threshold (thr = 0.15). Red dashed lines with number are corresponded to the threshold values, revealing serial disconnection of the network.
Figure 2 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058
Figure 2 - Three-dimensional plot of Principal Coordinate Analysis (PCoA) and STRUCTURE analysis. A the planes of the first three principal coordinates explain 43.65%, 20.13%, and 16.91% of total genetic variation, respectively, for seven Bactrocera carambolae populations using eight SSRs B the planes of the first three principal coordinates explain 33.05%, 23.17%, and 15.87%, respectively, for Bactrocera carambolae and Bactrocera dorsalis groups using eight SSRs C the planes of the first three principal coordinates explain 30.50%, 22.14%, and 18.53%, respectively, for the SY5 strain and wild populations using seven SSRs. Pie graphs, consisting of different colored sections, represent co-ancestor distribution of 185, 289, and 321 individuals in A two, B three, and C two hypothetical clusters, respectively.
Data from: A synchronized global sweep of the internal genes of modern avian influenza virus
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Effects of a Closed Space Environment on Gene Expression in Hair Follicles of Astronauts in the International Space Station
In recent times long-term stay has become a common occurrence in the International Space Station (ISS). However adaptation to the space environment can sometimes pose physiological problems to the astronauts after their return. Therefore it is important to develop healthcare technologies for astronauts. In this study hair an easy-to-obtain sample was identified as the candidate. In order to investigate the genetic changes in human hair during space flight the hair follicles of 10 astronauts were analyzed by DNA microarray and real time q-PCR analyses. Space environment induced gene expression of hair follicles of astronaut was measured 6 differnent times included 2 in flight on orbit. Ten independent experiments were performed on differing astronauts. and the sampling day was differed for each astronaut because of their schedules.
Gene expression in blood of mice with internal exposure to Cs-137
Cesium-137 is a radionuclide of concern in fallout from reactor accidents or nuclear detonations. When ingested or inhaled it can expose the entire body for an extended period of time potentially contributing to serious health consequences ranging from acute radiation syndrome to increased cancer risks. In order to identify changes in gene expression that may be informative for detecting such exposure and to begin examining the molecular responses involved we have profiled global gene expression in mice injected with 137CsCl. We extracted RNA from the blood of control or 137CsCl-injected mice at 2 3 5 20 or 30 days after exposure. Gene expression was measured using Agilent Whole Mouse Genome Microarrays and the data was analyzed using BRB-ArrayTools. Three-month old male C57Bl/6 mice were injected intraperitoneally with 8.0 xc2 xb1 0.3 MBq 137CsCl solution in a volume of 50 xce xbcL or left as controls. Groups of treated and control mice were sacrificed at intervals during the first 2-30 days after exposure and total blood was collected using cardiac puncture. RNA was extracted from the blood globin-transcript reduced and subjected to whole genome expression microarray analysis.
Gene expression in blood of mice with internal exposure to Cs-137
GEO Series GSE52690. Mus musculus. 48 samples. Type: Expression profiling by array.
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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.