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11,177 results for “identify”
Doodleverse/Segmentation Zoo Res-UNet models for identifying water in Sentinel-2 RGB images of coasts. SWED-only version
<p><strong>Doodleverse/Segmentation Zoo Res-UNet models for identifying water in Sentinel-2 RGB images of coasts.</strong></p> <p><strong>Based on SWED*** data</strong></p> <p>https://openmldata.ukho.gov.uk/</p> <p>These Residual-UNet model data are based on images of coasts and associated labels. Models have been fitted to the following types of data</p> <p>1. RGB (3 band): red, green, blue</p> <p>Classes are: {0: null, 1: water}.</p> <p>These files are used in conjunction with Segmentation Zoo*</p> <p>For each model, there are 3 files with the same root name:</p> <p>1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse.</p> <p> </p> <p>2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images</p> <p> </p> <p>3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model</p> <p>4. <strong>'_history.npz'</strong> files contain model training metrics</p> <p> </p> <p>One additional file, BEST_MODEL.txt, contains the name of the model with the highest validation accuracy</p> <p> </p> <p>References</p> <p>* https://github.com/Doodleverse/segmentation_zoo</p> <p>** https://github.com/Doodleverse/segmentation_gym</p> <p>*** https://www.sciencedirect.com/science/article/abs/pii/S0034425722001584</p>
Data and R scripts for: Identifying existing management practices in the control of Striga asiatica within rice–maize systems in mid-west Madagascar
<p>Infestations by the parasitic weed genus <i>Striga</i> result in significant losses to cereal crop yields across sub-Saharan Africa. The problem disproportionately affects subsistence farmers who frequently lack access to novel technologies. Effective <i>Striga </i>management therefore requires the development of strategies utilising existing cultural management practices. We report a multi-year, landscape-scale monitoring project for <i>Striga</i> asiatica in the mid-west of Madagascar, undertaken over 2019-2020 with the aims of examining cultural, climatic and edaphic factors currently driving abundance and distribution. Long-distance transects were established across the middle-west region of Madagascar, over which <i>Striga asiatica</i> abundance in fields was estimated. Analysis of the data highlights the importance of crop variety and legumes in driving <i>Striga </i>density. Moreover, the dataset revealed significant effect of precipitation seasonality, mean temperature and altitude in determining abundance. A composite management index indicated the effect of a range of cultural practices on changes in <i>Striga </i>abundance<i>. </i>The findings support the assertion that single measures are not sufficient for the effective, long-term management of <i>Striga</i>. Furthermore, the composite score has potential as a significant guide of integrated <i>Striga </i>management beyond the geographic range of this study. </p>
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Karen Salazar, <a href="https://orcid.org/0000-0002-2284-6379">https://orcid.org/0000-0002-2284-6379</a>. Claims 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>.
Data and code availibility for the paper "Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multi-modal freezing model" by Alpert et al.
<p>The data and codes used in the paper "Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multi-modal freezing model" by Alpert et al., published in <em>Science Advances</em> are included in this collection. Detailed descriptions of the files are given in the readme file.</p>
Identifying a novel ferroptosis-related prognostic score for predicting prognosis in chronic lymphocytic leukemia
<p><span><strong>Background</strong>:</span><span> Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. Although the treatment landscape for CLL is rapidly evolving, there are still some patients who remain drug resistance or disease refractory. Ferroptosis is a type of lipid peroxidation-induced cell death and has been suggested with a prognostic value in several cancers. Our research aims to build a prognostic model to improve risk stratification in CLL patients and facilitate more accurate assessment for clinical management.</span></p> <p><span><strong>Methods</strong>: </span><span>The differentially expressed ferroptosis-related genes (</span><span>FRGs) in CLL were filtered through univariate Cox regression analysis based on public databases. Least Absolute Shrinkage and Selection Operator (LASSO) Cox algorithms were performed to construct a prognostic risk model. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were performed to estimate the immune infiltration score and immune-related pathways. A total of thirty-six CLL patients in our center were enrolled in this study as a validation cohort. Moreover, a nomogram model was established to predict the prognosis.</span></p> <p><span><strong>Results</strong>: </span><span>A total of differentially expressed 15 FRGs with prognostic significance were screened out. After minimizing the potential risk of overfitting, we constructed a novel ferroptosis-related prognostic score (FPS) model with nine FRGs (AKR1C3, BECN1, CAV1, CDKN2A, CXCL2, JDP2, SIRT1, SLC1A5 and SP1), and stratified patients into low-risk and high-risk groups. Kaplan–Meier analysis showed that patients with high FPS had worse overall survival (OS) (P<0.0001) and treatment-free survival (TFS) (P<0.0001). ROC curves evaluated the prognostic prediction ability of the FPS model. Additionally, the immune cell types and immune-related pathways were correlated with the risk scores in CLL patients. In the validation cohort, the results confirmed </span><span>that the </span><span>high</span><span>-</span><span>risk group was related to worse OS (P<0.0001), progress-free survival (PFS) (P=0.0140) and TFS (P=0.0072). </span><span>In</span><span> the multivariate analysis, only FPS (P=0.011) and CLL-IPI (P=0.010) were independent risk indicators for OS. Furthermore, we established a nomogram including FPS and CLL-IPI which could strongly and reliably predict individual prognosis.</span></p> <p><span><strong>Conclusion</strong>: </span><span>A novel FPS model could be used in CLL for prognostic prediction. The model index may also facilitate the development of new clinical ferroptosis-targeted therapies in patients with CLL.</span></p>
A dual selection system for directed evolution to identify allosteric transcription factor PobR variants responsive to different aromatic compounds
<p>This dataset includes all the raw data of our characterization experiments during the work titled “A dual selection system for directed evolution to identify allosteric transcription factor PobR variants responsive to different aromatic compounds”.</p>
oLIVER progress presentation 2022: Identifying biomarkers for diagnosis and treatment evaluation of NAFLD
<p>This is a recorded talk with head of the oLIVER project - Jørgen Kjems, where he presents the latest project progress.</p> <p>The talk was given at one of ODIN's (the Open Discovery Innovation Network) Knowledge Sharing Events in May 2022.</p>
Compass To Publish un outil d'aide pour identifier les revues prédatrices
<p>Cette vidéo présente Compass To Publish, un outil d'aide pour identifier les revues prédatrices développé par ULiège. Elle a été réalisée par le groupe de travail "Tutoriel" de ULiège Library et déposée sur Youtube le 3 février 2021 : <a href="https://youtu.be/DwisQdgHWWs">https://youtu.be/DwisQdgHWWs</a></p> <p>Elle s’accompagne de deux fichiers adjuvants qui ont pour but d’expliquer et de partager les méthodes de travail du groupe dans sa création de ressources éducatives libres, à savoir : </p> <ul> <li> <p>le script de la vidéo accompagné d’informations technico-pédagogiques en vis-à-vis (pour l’enregistrement studio de la ressource)</p> </li> <li> <p>la taxonomie des rôles et contributions utilisée pour créditer les différentes personnes ayant participé à la création de cette ressource (adapté de la taxonomie <a href="https://casrai.org/credit/">CRediT</a> (Contributor Roles Taxonomy) pour nos besoins. </p> </li> </ul>
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Leanne Elder, <a href="https://orcid.org/0000-0001-5244-9780">https://orcid.org/0000-0001-5244-9780</a>. Claims 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>.
Data and codes for: A link model approach to identify congestion hotspots
<p>Congestion emerges when high demand peaks put transportation systems under stress. Understanding the interplay between the spatial organization of demand, the route choices of citizens, and the underlying infrastructures is thus crucial to locate congestion hotspots and mitigate the delay. Here we develop a model where links are responsible for the processing of vehicles, which can be solved analytically before and after the onset of congestion, and provide insights into the global and local congestion. We apply our method to synthetic and real transportation networks, observing a strong agreement between the analytical solutions and the Monte Carlo simulations, and a reasonable agreement with the travel times observed in 12 cities under congested phase. Our framework can incorporate any type of routing extracted from real trajectory data to provide a more detailed description of congestion phenomena and could be used to dynamically adapt the capacity of road segments according to the flow of vehicles, or reduce congestion through hotspot pricing.</p>
Pseudomonas syringae virulence factors identified by HMMER
<p>JSON object containing Pseudomonas syringae accession numbers as primary keys, containing protein accession numbers, e-value, and NCBI annotations for every HMMER hit for common <em>P. syringae</em> virulence factors. includes: canonical type III secretion system genes, type III effector subfamilies as described by the <em>Pseudomonas syringae</em> effector compendium, and ewoody host or Pseudomonas (WHOP) genes.</p>
Identifying knowledge gap -- Pergubi workshop series
<p>Choosing research topic and posing research questions can be hard. A good literature search and review are the two main ingredient to identify knowledge/research gap to build a good research question.</p> <p>The slides are available on Slideshare: https://www.slideshare.net/d_erwin_irawan/knowledge-gap-identification.</p> <p>I gave this talk on 06.10.2017 at Aston Braga Hotel, Bandung.</p> <p> </p>
Identifying conceptual neural responses to symbolic numerals
<p>The goal of measuring conceptual processing in numerical cognition is distanced by the possibility that neural responses to symbolic numerals are influenced by physical stimulus confounds. Here, we targeted conceptual responses to parity (even <em>vs. </em>odd), using electroencephalographic (EEG) frequency-tagging with a symmetry/asymmetry design. Arabic numerals (2–9) were presented at 7.5 Hz in 50-s sequences; odd and even numbers were alternated to target differential, "asymmetry" responses to parity at 3.75 Hz (7.5 Hz/2). Parity responses were probed with four different stimulus sets, increasing in intra-numeral stimulus variability, and with two control conditions comprised of non-conceptual numeral alternations. Significant asymmetry responses were found over the occipitotemporal cortex to all conditions, even for the arbitrary controls. The large physical-differences control condition elicited the largest response in the stimulus set with the lowest level of variability (1 font). Only in the stimulus set with the highest level of variability (20 drawn, colored exemplars/numeral) did the response to parity surpass both control conditions. These findings show that physical differences across small sets of Arabic numerals can strongly influence, and even account for, automatic brain responses. However, carefully designed control conditions and highly variable stimulus sets may be used towards identifying truly conceptual neural responses.</p>
From tetraploid to diploid, a pangenomic approach to identify genes lost during synthetic diploidization of Eragrostis curvula
<p><strong>Introduction:</strong> In <em>Eragrostis curvula</em>, commonly known as weeping lovegrass, a synthetic diploidization event of the facultative apomictic tetraploid Tanganyika INTA cv. originated from the sexual diploid Victoria cv. Apomixis is an asexual reproduction by seeds in which the progeny is genetically identical to the maternal plant.</p> <p><strong>Methods:</strong> To assess the genomic changes related to ploidy and to the reproductive mode occurring during diploidization, a mapping approach was followed to obtain the first <em>E. curvula</em> pangenome assembly. In this way, gDNA of Tanganyika INTA was extracted and sequenced in 2x250 Illumina pair-end reads and mapped against the Victoria genome assembly. The unmapped reads were used for variant calling, while the mapped reads were assembled using Masurca software.</p> <p><strong>Results:</strong> The length of the assembly was 28,982,419 bp distributed in 18,032 contigs, and the variable genes annotated in these contigs rendered 3,952 gene models. Functional annotation of the genes showed that the reproductive pathway was differentially enriched. PCR amplification in gDNA and cDNA of Tanganyika INTA and Victoria was conducted to validate the presence/absence variation in five genes related to reproduction and ploidy. The polyploid nature of the Tanganyika INTA genome was also evaluated through the variant calling analysis showing the single nucleotide polymorphism (SNP) coverage and allele frequency distribution with a segmental allotetraploid pairing behavior.</p>
Fig. 1 Screening flow, testing 1600 FDA compounds against S in Assessment of FDA-approved drugs against StrongyloideS rAtti in vitro and in vivo to identify potentially active drugs against strongyloidiasis
Fig. 1 Screening flow, testing 1600 FDA compounds against S. ratti
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Brandão, Simone N., <a href="https://orcid.org/0000-0002-3487-6129">https://orcid.org/0000-0002-3487-6129</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>.
Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.
<p>*.sh and *.R are codes to test rare coding variants for association with ISCAD.</p> <p>Petrazzini_etal_2024_*_level_meta_analysis.txt.gz are summary statistics of variant- and gene-level associations of rare coding variants in the exome sequences of 604,914 individuals with an in-silico score for coronary artery disease (ISCAD).</p> <p>Chromosomal positions are mapped to the GRCh38 (hg38) human genome reference.</p> <p>Directions of effect correspond to associations in the UK Biobank, the All of Us Research Program, the BioMe Biobank sample 1 and the BioMe Biobank sample 2, in that order.</p>
Spatial Mapping of Mobile Genetic Elements and their Cognate Hosts in Complex Microbiomes - Identifying the host taxon of a previously undescribed plasmid
<p>We investigated the taxonomic association of an unknown plasmid within a plaque biofilm of a patient diagnosed with stage 3 periodontitis. We combined long- and short- read sequencing to identify a complete plasmid with minimal homology to any sequence in the RefSeq database. The plasmid carried several predicted genes for mobilization and toxin-antitoxin systems. We designed MGE-FISH probes for the plasmid and combined this MGE-FISH stain with an 18-genera HiPR-FISH panel.</p> <p>Images are labeled by collection time such that the laser order for a given field of view (fov) is: 488nm Lambda, 514nm Lambda, 561nm Lambda, 633nm Airyscan, 405nm Lambda. We used Flye (https://github.com/fenderglass/Flye) to assemble the plasmid using long read Nanopore sequencing only and we used OPERA-MS (https://github.com/CSB5/OPERA-MS) to do hybrid assembly with Illumina short reads and Nanopore long reads. The assemblies are in the fasta files and the reads that map to the assemblies are in the fastq files. </p>
Genome-wide association study identifies genomic regions associated with key reproductive traits in Korean Hanwoo cows
<p><strong>Background</strong></p> <p>Conducting genome-wide association studies (GWAS) for reproductive traits in Hanwoo cattle, including age at first calving (AFC), calving interval (CI), gestation length (GL), and number of artificial inseminations per conception (NAIPC), is of paramount significance. These analyses provided a thorough exploration of the genetic basis of these traits, facilitating the identification of key markers for targeted trait improvement. Breeders can optimize their selection strategies, leading to more efficient and sustainable breeding programs, by incorporating genetic insights. This impact extends beyond individual traits and contributes to the overall productivity and profitability of the Hanwoo beef cattle industry. Ultimately, GWAS is essential in ensuring the long-term genetic resilience and adaptability of Hanwoo cattle populations. The primary goal of this study was to identify significant single nucleotide polymorphisms (SNPs) or quantitative trait loci (QTLs) associated with the studied reproductive traits and subsequently map the underlying genes that hold promise for trait improvement.</p> <p><strong>Results</strong></p> <p>A genome-wide association study of reproductive traits identified 68 significant single nucleotide polymorphisms (SNPs) distributed across 29 <em>Bos taurus</em> autosomes (BTA). Among them, BTA14 exhibited the highest number of identified SNPs (25), whereas BTA6, BTA7, BTA8, BTA10, BTA13, BTA17, and BTA20 exhibited 8, 5, 5, 3, 8, 2, and 12 significant SNPs, respectively. Annotation of candidate genes within a 500 kb region surrounding the significant SNPs led to the identification of ten candidate genes relevant to age at first calving. These genes were: <em>FANCG</em>, <em>UNC13B</em>, <em>TESK1</em>, <em>TLN1</em>, and <em>CREB3</em> on BTA8; <em>FAM110B</em>, <em>UBXN2B</em>, <em>SDCBP</em>, and <em>TOX</em> on BTA14; and <em>MAP3K1</em> on BTA20. Additionally, <em>APBA3</em>, <em>TCF12</em>, and <em>ZFR2</em>, located on BTA7 and BTA10, were associated with the calving interval; <em>PAX1</em>, <em>SGCD</em>, and <em>HAND1</em>, located on BTA7 and BTA13, were linked to gestation length; and <em>RBM47</em>, <em>UBE2K</em>, and <em>GPX8</em>, located on BTA6 and BTA20, were linked to the number of artificial inseminations per conception in Hanwoo cows.</p> <p><strong>Conclusions</strong></p> <p>The findings of this study enhance our knowledge of the genetic factors that influence reproductive traits in Hanwoo cattle populations and provide a foundation for future breeding strategies focused on improving desirable traits in beef cattle. This research offers new evidence and insights into the genetic variants and genome regions associated with reproductive traits and contributes valuable information to guide future efforts in cattle breeding.</p>
Testing novel climate accounting identifies animal agriculture as the leading emissions sector
<p>Data and spreadsheet supporting the paper <span>"Testing novel climate accounting identifies animal agriculture as the leading emissions sector" G Wedderburn-Bisshop, 2024</span></p>
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.