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1,291 results for “gap”
Systematic evaluation of GAPs and GEFs identifies ARHGAP45 as a targetable leukemia-specific RhoGAP dependency
GEO Series GSE273164. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing; Other.
Axolotl mandible regeneration occurs through mechanical gap closure and a shared regenerative program with the limb
GEO Series GSE271056. Ambystoma mexicanum. 8 samples. Type: Expression profiling by high throughput sequencing.
Shrinking the Psoriasis assessment gap: Early gene-expression profiling accurately predicts response to long-term treatment
GEO Series GSE85034. Homo sapiens. 179 samples. Type: Expression profiling by array.
Abrogation Of Gap Junctional Communication In ES Cells Results In A Disruption Of Primitive Endoderm Formation In Embryoid Bodies
GEO Series GSE77852. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.
Gene expression profile at single cell level of cells isolated from the bone fracture gap and un-injured bone marrow in mouse osteotomy models
GEO Series GSE230260. Mus musculus. 15 samples. Type: Expression profiling by high throughput sequencing.
Deciphering the direct transcriptional targets of the Drosophila Activating transcription factor 3 (Atf3) via ChIp-seq: Atf3 bridges the gap between cell polarity and the nucleus
GEO Series GSE71206. Drosophila melanogaster. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Sequence and expression analysis of human chromosome 20 gaps
GEO Series GSE35405. Homo sapiens. 7 samples. Type: Other; Methylation profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Halobacterium NRC-1 oxygen, light and gap perturbation
GEO Series GSE7738. Halobacterium salinarum NRC-1. 8 samples. Type: Expression profiling by array.
RGS4 controls airway hyperresponsiveness through GAP-independent mechanisms
GEO Series GSE242546. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP-arrays
GEO Series GSE18799. Homo sapiens. 21 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
Carcinoma-astrocyte gap junctions promote brain metastasis by cytosolic dsDNA response transfer
GEO Series GSE79256. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
GAP: Forecasting Commit Activity in git Projects
<p>This entry contains the replication package for our paper <em>GAP: Forecasting Commit Activity in git Projects</em> accepted for publication in Journal of Systems and Software.</p> <p>Abandonment of active developers poses a significant risk for many open source software projects. This risk can be reduced by forecasting the future activity of contributors involved in such projects. Focusing on the commit activity of individuals involved in git repositories, this paper proposes a practicable probabilistic forecasting model based on the statistical technique of survival analysis. The model is empirically validated on a wide variety of projects accounting for 7,528 git repositories and 5,947 active contributors. We found that a model based on the last 20 observed days of commit activity per contributor provides the best concordance. We also found that the predictions provided by the model are generally close to actual observations, with slight underestimations for low probability predictions and slight overestimations for higher probability predictions. This model is implemented as part of an open source tool, called gap, that predicts future commit activity.</p> <p><strong>Replication package</strong></p> <p>The model is explained and defined in <em>"notebooks/Survival analysis.ipynb"</em>. This is a Jupyter notebook created with Jupyter Lab. The dependencies required to run this notebook are listed in <em>requirements.txt</em> and can be automatically installed using <code>pip install -r requirements.txt</code>. Consider making use of a virtual environment to ensure a proper replication of the analyses.</p> <p>The data used to validate the model can be found in <em>data/cargo.csv.gz</em>. They were produced with the script <em>data/convert.py</em> that requires file <em>data-raw/cargo_all_proj_commits_id.csv.gz</em>. This file was created by retrieving all the commits of all projects hosted on github that are related to a project distributed on Cargo. To identify such projects, we relied on libraries.io dataset. GitHub API was then queried to obtain the username of each author (if available) to allow some basic identity merging task. Data about repositories were extracted from libraries.io 1.4.0 dataset and can be found in <em>data/repositories.csv.gz</em>.</p> <p><strong>The GAP tool</strong></p> <p>GAP is made available on <a href="https://github.com/AlexandreDecan/gap">https://github.com/AlexandreDecan/gap</a></p>
Figure 3 from: Balke M, Ribera I (2020) A subterranean species of Exocelina diving beetle from the Malay Peninsula filling a 4,000 km distribution gap between Melanesia and southern China. Subterranean Biology 34: 25-37. https://doi.org/10.3897/subtbiol.34.50148
Figure 3 Ventral view of AExocelina sugayai sp. nov. male and BExocelina abdita.
Figure 1 in First survey of the ants (Hymenopteraı Formicidae) of Piauí: filling a major knowledge gap about ant diversity in Brazil
Figure 1. Areas with ant records in the state of Piauí, Brazil, based on literature review (black circles) and collecting expeditions of the present study to the Serra das Confusões (red circle) and Serra da Capivara (blue circle) National Parks.
Evaluation of DNA barcode libraries used in the UK and developing an action plan to fill priority gaps: Appendices 3 and 4
<p>Supplementary data for the DEFRA Centre of Excellence for DNA Methods report: Evaluation of DNA barcode libraries used in the UK and developing an action plan to fill priority gaps. Appendix 3: Priority species identified during the survey and consultation Appendix 4: Raw data for gap analyses</p>
Data from: Re-evaluating the geological evidence for Late Holocene marine incursion events along the Guerrero Seismic Gap on the Pacific Coast of Mexico
Despite the large number of tsunamis that impact Mexico's Pacific coast, stratigraphic studies focusing on geological impacts are scanty, making it difficult to assess the long-term risks for this vulnerable region. Surface samples and six cores were taken from Laguna Mitla near Acapulco to examine sedimentological and geochemical evidence for marine incursion events. Sediment cores collected from behind the beach barrier are dominated by intercalated layers of peat and inorganic sediments, mostly silt and clay, with little or no sand. Sand- and shell-rich clastic layers with high levels of sulfur, calcium, and strontium only occur adjacent to the relict beach ridge remnants near the center of the lagoon. With the exception of one thin fine sand layer, the absence of sand in the near-shore cores and the predominance of the terrigenous element titanium in the inorganic layers, evidently eroded from the surrounding hillslopes, suggests that these large-grained intervals do not represent episodic marine incursions, but rather were likely formed by the erosion and redeposition of older marine deposits derived from the beach ridge remnants when water levels were high. These results do not support the occurrence of a large tsunami event at Laguna Mitla during the Late Holocene.
Enhancing the excitation gap of a quantum-dot-based Kitaev chain
<p>Code used to produce the numerical results presented in "Enhancing the excitation gap of a quantum-dot-based Kitaev chain" manuscript.</p>
An Investigation On The Use Of Au@SiO2@Au Nanomatryoshkas As Gap Enhanced Raman Tags Dataset
<p>Gap-enhanced Raman tags are a new type of optical probe that have wide applications in sensing and detection. A gap-enhanced Raman tag is prepared by embedding Raman molecules inside a gap between two plasmonic metals such as an Au core and Au shell. Even though placing Raman tags beneath an Au shell seems counter-intuitive, it has been shown that such systems produce a stronger surface-enhanced Raman scattering response due to the strong electric field inside the gap. While the theoretical support of the stronger electric field inside the gap was provided in the literature, a comprehensive understanding of how the electric field inside the gap compares with that of the outer surface of the particle was not readily available. We investigated Au@SiO$_2$@Au nanoparticles with diameters ranging from 35 nm to 70 nm with varying shell (2.5--10 nm) and gap (2.5--15 nm) thicknesses and obtained both far-field and near-field spectra. The extinction spectra from these particles always have two peaks. The low-energy peak redshifts with the decreasing shell thickness. However, when the gap thickness decreases, the low-energy peaks first blueshift and then redshift, producing a C-shape in the peak position. For every system we investigated, the near-field enhancement spectra were stronger inside the gap than on the outer surface of the nanoparticle. We find that a thin shell combined with a thin gap will produce the greatest near-field enhancement inside the gap. Our work fills the knowledge gap between the exciting potential applications of gap-enhanced Raman tags and the fundamental knowledge of enhancement provided by the gap.</p>
Figure 2 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 2. Binary maps of potential distribution of (A) chacoan peccary, (B) cougar, (C) brown brocket deer, (D) collared peccary and (E) anteater. The gray pixels indicate the places of presence of the species.
Figure 1 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 1. Study area. Geometric figures of different colors indicating the sites of presence of the selected mammalian species used for the distribution models.
ScienceDex guides
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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.