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11,177 results for “identify”
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Paul Frédéric Culmann, <a href="http://www.wikidata.org/entity/Q21509626">http://www.wikidata.org/entity/Q21509626</a>. Claims or attributions were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Impermanent Identifiers: Enhanced Source Code Comprehension and Refactoring
Open the record for dataset details and reuse information.
Single-cell multi-omics analysis identifies context specific gene regulatory gates and mechanisms
<p>There is a growing interest in inferring context specific gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data. This involves identifying the regulatory relationships between transcription factors (TFs) and genes in individual cells, and then characterizing these relationships at the level of specific cell types or cell states. <br>In this study, we introduce scGATE (single-cell gene regulatory gate) as a novel computational tool for inferring TF-gene interaction networks and reconstructing Boolean logic gates involving regulatory TFs using scRNA-seq data. In contrast to current Boolean models, scGATE eliminates the need for individual formulations and likelihood calculations for each Boolean rule (e.g., AND, OR, XOR). By employing a Bayesian framework, scGATE infers the Boolean rule after fitting the model to the data, resulting in significant reductions in time-complexities for logic-based studies. <br>We have applied assay for transposase-accessible chromatin with sequencing (scATAC-seq) data and TF DNA binding motifs to filter out non-relevant TFs in gene regulations. By integrating single-cell clustering with these external cues, scGATE is able to infer context specific networks. The performance of scGATE is evaluated using synthetic and real single-cell multi-omic data from mouse tissues and human blood, demonstrating its superiority over existing tools for reconstructing TF-gene networks. Additionally, scGATE provides a flexible framework for understanding the complex combinatorial and cooperative relationships among TFs regulating target genes by inferring Boolean logic gates among them.</p>
PFAS spectra library and identified PFAS spetra from wastewater samples
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Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Barbara P. Segedin, <a href="http://www.wikidata.org/entity/Q21608609">http://www.wikidata.org/entity/Q21608609</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Identifying Key Targets and Immune Environment in Wound Healing Based on Iron Overload-Related Genes
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Data and scripts for: Site-level connectivity identified from multiple sources of movement data to inform conservation of a migratory bird
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Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Erich Werdermann, <a href="http://www.wikidata.org/entity/Q77133">http://www.wikidata.org/entity/Q77133</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Larry E. Serpa, <a href="http://www.wikidata.org/entity/Q109677531">http://www.wikidata.org/entity/Q109677531</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Winona Hazel Welch, <a href="http://www.wikidata.org/entity/Q21340801">http://www.wikidata.org/entity/Q21340801</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by John Adolph Shafer, <a href="http://www.wikidata.org/entity/Q615605">http://www.wikidata.org/entity/Q615605</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Hans Glauning, <a href="http://www.wikidata.org/entity/Q1579831">http://www.wikidata.org/entity/Q1579831</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Juan Joaquín Rodríguez y Femenías, <a href="http://www.wikidata.org/entity/Q5950135">http://www.wikidata.org/entity/Q5950135</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Alexander Gilli, <a href="http://www.wikidata.org/entity/Q8194912">http://www.wikidata.org/entity/Q8194912</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Mariano Lagasca, <a href="http://www.wikidata.org/entity/Q891966">http://www.wikidata.org/entity/Q891966</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Zacharia C. Panțu, <a href="http://www.wikidata.org/entity/Q730640">http://www.wikidata.org/entity/Q730640</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Theodor Kotschy, <a href="http://www.wikidata.org/entity/Q113299">http://www.wikidata.org/entity/Q113299</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Michel Charles Durieu de Maisonneuve, <a href="http://www.wikidata.org/entity/Q703990">http://www.wikidata.org/entity/Q703990</a>. Claims or attributions were made on Bionomia, <a href="https://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
Identifying relationships between multi-scale social-ecological factors to explore ungulate health in a Western Kazakhstan rangeland
<p>1. Rangelands are multi-use landscapes which are socially and ecologically important in different ways. Among other interactions, shared use of rangelands by wildlife and livestock can lead to disease transmission. Understanding wildlife and livestock health and managing disease transmission in rangelands requires an integration of social and ecological knowledge.</p> <p>2. Using the example of Western Kazakhstan, home to two types of ungulate hosts, the critically-endangered saiga antelopes, <i>Saiga tatarica</i>, and livestock, we conducted a cross-scale analysis of social-economic, ecological and climatic factors that contribute to transmission of diseases. We focused on Gastro-intestinal Nematodes (GINs) because they are transmitted between hosts that share pasture and they affect ungulate fitness. We used an interdisciplinary social-ecological methods approach which included conducting fecal egg counts of GINs in saigas and livestock, semi-structured interviews and focus group discussions with livestock owners and herders in the region, and triangulation of information through secondary sources.</p> <p>3. Livestock rearing was done in two ways a) village-based livestock and b) outlying farms. The latter overlapped more with saigas. Village-based livestock had significantly higher worm burdens than those on outlying farms, which had comparable burdens to saigas. Various factors exacerbate GIN prevalence and transmission: Veterinary services are minimal; both saiga and livestock numbers are increasing; and changing climate is increasing farmers' dependence on shared pastures for hay production. It will be crucial for saiga conservationists to engage in multi-pronged conservation interventions, which are evaluated and adapted through the lens of rural livelihoods and the livestock health on which they depend.</p> <p>4. <em>Synthesis and Application: </em>Our work provides researchers and practitioners with an avenue to better understand complex inter-relationships and plan interventions within rangelands, while viewing host health from an interdisciplinary perspective - ultimately working towards wildlife conservation whilst safeguarding livelihoods across the world's rangelands.</p>
Fig. 1 in Fluctuating Asymmetry As A Tool In Identifying Population Stress In Hungarian Populations Of Bombina Bombina, B. Variegata And Their Hybrids
Fig. 1. Mean asymmetry compared among the two pure species and their hybrids for: a) femur and b) tibia length. Bars represent 95% confidence intervals
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.