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118 results for “identification tool”
Agonum sordidum, Fig_6 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum sordidum,</p> <p>Fig_6 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum rugicolle, Fig_5 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum rugicolle,</p> <p>Fig_5 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum_nigrum, Fig_4 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum_nigrum,</p> <p>Fig_4 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum_mesostictum, Fig_2 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum_mesostictum,</p> <p>Fig_2 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum monachum syriacum, Fig_3 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum monachum syriacum,</p> <p>Fig_3 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum_marginatum, Fig_1 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum_marginatum,</p> <p>Fig_1 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p> <p> </p>
Genome-wide tool for rapid de novo identification and visualisation of interspersed and tandem
<p><span>Genomic repeats are functionally ubiquitous structural units found in all genomes. Studying these repeats of different origins is essential for the evolution and adaptation of a given organism. These repeating patterns have manifold signatures and structures with varying degrees of homology, making their identification challenging. To address this challenge, we developed a new algorithm and software that can rapidly and accurately detect any repeated sequences <em>de novo</em> with varying degrees of homology in genomic sequences in interspersed or clustered repeats. Numerous forms of repeated sequences and complex patterns can be identified, even for complex sequence variants and implicit or mixed types of repeat blocks. Direct and inverted-repeat elements, perfect and imperfect microsatellite repeats, and any short- or long-tandem repeat belonging to a wide range of higher-order repeat structures of telomers or large satellite sequences can be detected. By combining precision and versatility, our tool contributes significantly to elucidating the intricate landscape of genomic repeats.</span></p>
Fig. 4 in First record of Atherigona reversura Villeneuve (Diptera: Muscidae) feeding on Bermudagrass (Cynodon dactylon cv. Jiggs, Poaceae) in Brazil: morphological and molecular tools for identification
Fig. 4. Analysis using Bayesian posterior probabilities (values shown) using 10 COI sequences for seven species of Atherigona and Cyrtoneuropsis veniseta.
Fig. 3 in First record of Atherigona reversura Villeneuve (Diptera: Muscidae) feeding on Bermudagrass (Cynodon dactylon cv. Jiggs, Poaceae) in Brazil: morphological and molecular tools for identification
Fig. 3. Atherigona (Atherigona) reversura: (A) trifoliate process, dorsal view; (B) trifoliate process, lateral view; (C) hypopygial prominence, lateral view.
Databases for MyCodentifier: A tool for routine identification of nontuberculous mycobacteria using MGIT enriched shotgun metagenomics.
<p>Databases used for MyCodentifier a Nextflow pipeline to identify Mycobacterium tuberculosis complex (MTBC) and Nontuberculous mycobacteria (NTM) species from Next-generation sequencing (NGS) data.<br> <br> <strong>Short description:</strong><br> The pipeline is constructed using nextflow as workflow manager running in a docker container. It is able to identify species of MTBC/NTM from positive Mycobacterial Growth Indicator Tube (MGIT) cultures. To do so it uses an hsp65 database for fast identification coupled with a Metagenomic method using centrifuge to identify on genome level. For TB it also is able to identify subspecies. Results are presented in automated pdf and html reports.</p> <table> <caption><strong>Databases</strong></caption> <tbody> <tr> <td><strong>Name</strong></td> <td><strong>Short Description</strong></td> </tr> <tr> <td>20220726_ref.tar.gz</td> <td>7 major mycobacterial genomes as centrifuge classification database, used for reference-based mapping and genotype resistance prediction</td> </tr> <tr> <td>20220726_wgs_centrifuge_db_Radboudumc_MB.tar.gz</td> <td>centrifuge classification database using Tortoli <em>et al</em> 2017 Mycobacterium strains + additional strains</td> </tr> <tr> <td>genomes.tar.gz</td> <td>7 major mycobacterial genomes, annotation and Genbank files. Files are paired with 20220726_ref.tar.gz</td> </tr> <tr> <td>snpEff.tar.gz</td> <td>7 major mycobacterial genomes annotation models for snpEff.</td> </tr> <tr> <td>Tortoli_etal_hsp65.tar.gz</td> <td>KMA database of hsp65 gene extractions of the Tortoli <em>et al</em> 2017 Mycobacterium strains.</td> </tr> <tr> <td> <p>Used in the study:<br> p_compressed+h+v.tar.gz (12/06/2016)</p> </td> <td> <p>Databases available via <a>ftp://ftp.ccb.jhu.edu/pub/infphilo/centrifuge/data</a> or <a href="https://ccb.jhu.edu/software/centrifuge/manual.shtml#custom-database">https://ccb.jhu.edu/software/centrifuge/manual.shtml#custom-database</a></p> </td> </tr> </tbody> </table> <p><strong>MyCodentifier Github:</strong></p> <p><a href="https://jordycoolen.github.io/MyCodentifier/">https://jordycoolen.github.io/MyCodentifier/</a></p> <p> </p> <p> </p>
RAIDE: a tool for Assertion Roulette and Duplicate Assert identification and refactoring
<p>Video presentation of the article entitled "RAIDE: a tool for Assertion Roulette and Duplicate Assert identification and refactoring" of the 34th Brazilian Symposium on Software Engineering (SBES’20).</p>
Chemical variations in Quercus pollen as a tool for taxonomic identification: implications for long-term ecological and biogeographical research
<p><strong>Aim</strong> </p> <p>Fossil pollen is an important tool for understanding biogeographic patterns in the past, but the taxonomic resolution of the fossil-pollen record may be limited to genus or even family level. Chemical analysis of pollen grains has the potential to increase the taxonomic resolution of pollen, but present-day chemical variability is poorly understood. This study aims to investigate whether a phylogenetic signal is present in the chemical variations of <em>Quercus</em> L. pollen and to assess the prospects of chemical techniques for identification in biogeographic research.</p> <p><strong>Location</strong> </p> <p>Portugal</p> <p><strong>Taxon</strong> </p> <p>Six taxa (five species, one subspecies) of <em>Quercus</em> L., <em>Q. faginea, Q. robur, Q. robur</em> ssp. <em>estremadurensis, Q. coccifera, Q. rotundifolia</em> and <em>Q. suber</em> belonging to three sections: <em>Cerris, Ilex</em>, and <em>Quercus</em> (<a href="https://www.biorxiv.org/content/10.1101/761148v2#ref-13">Denk, Grimm, Manos, Deng, & Hipp, 2017</a>)</p> <p><strong>Methods</strong> </p> <p>We collected pollen samples from 297 individual <em>Quercus</em> trees across a 4° (∼450 km) latitudinal gradient and determined chemical differences using Fourier-transform infrared spectroscopy (FTIR). We used canonical powered partial least-squares regression (CPPLS) and discriminant analysis to describe within- and between-species chemical variability.</p> <p><strong>Results</strong> </p> <p>We find clear differences in the FTIR spectra from <em>Quercus</em> pollen at the section level (<em>Cerris</em>: ∼98%; <em>Ilex</em>: ∼100%; <em>Quercus</em>: ∼97%). Successful discrimination is based on spectral signals related to lipids and sporopollenins. However, discrimination of species within individual <em>Quercus</em> sections is more difficult: overall, species recall is ∼76% and species misidentifications within sections lie between 18% and 31% of the test-set.</p> <p><strong>Main Conclusions</strong> </p> <p>Our results demonstrate that subgenus level differentiation of <em>Quercus</em> pollen is possible using FTIR methods, with successful classification at the section level. This indicates that operator-independent FTIR approaches can surpass traditional morphological techniques using the light microscope. Our results have implications both for providing new insights into past colonisation pathways of <em>Quercus</em>, and likewise for forecasting future responses to climate change. However, before FTIR techniques can be applied more broadly across palaeoecology and biogeography, our results also highlight a number of research challenges that still need to be addressed, including developing sporopollenin-specific taxonomic discriminators and determining a more complete understanding of the effects of environmental variation on pollen-chemical signatures in <em>Quercus</em>.</p>
Data from: A universal tool for marine metazoan species identification – Towards best practices in proteomic fingerprinting
<p><span>Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1,246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species.</span></p>
ZooMS identification of a whale bone tool from Bronze Age Heiloo, the Netherlands
<p>This dataset contains the ZooMS data used in the palaeoproteomic identification of a whale bone tool from Bronze Age Heiloo, the Netherlands. The same project was also analysed using LC-MS/MS. The reference to the data repository containing the LC-MS/MS data can be found in the associated publication.</p>
Identification of starch granules on ground stone tools exposed to fire
<p>Intense wildfires destroy everything in their path, including archaeological sites. Prehistorically, archaeological sites were regularly and intentionally burned. In what ways does burning affect those sites? With increased wildfire activity, research has begun to describe the effects of fire on archaeological materials through post-fire and experimental treatment, yet, little is known about the effects of fire on microbotanical remains, such as starch granules. Although some studies address the impact of fire on starch-rich foods, there is virtually no research on the fire effects of starch granules embedded in ground stone tools. The current study examines changes in the morphology of starch granules embedded in ground stone tools before and after exposure to flame combustion. A measurable amount of intact and identifiable starch granules was recovered from all of the treated samples. However, significantly fewer intact, identifiable granules were found as tools were exposed to higher temperatures for longer periods of time.</p>
NMR AS A TOOL FOR COMPOUND IDENTIFICATION IN MIXTURES
<p>Data set used for the paper NMR AS A TOOL FOR COMPOUND IDENTIFICATION IN MIXTURES.</p>
Comparison between ribosomal assembly and machine learning tools for microbial identification of organisms with different characteristics
<p><strong>DNABERT+DeLUCS_notebooks.zip </strong></p> <ul> <li>Code notebooks for running DNABERT and DeLUCS</li> </ul> <p> </p> <p><strong>images-20230519T015235Z-001.zip </strong></p> <ul> <li>Heatmaps</li> <li>Factor plots</li> </ul> <p> </p> <p><strong>Data-20230518T191203Z-003.zip </strong></p> <ul> <li>MBARC and Hot Springs datasets <ul> <li>Reference genomes</li> <li>16S sequences (barrnap)</li> </ul> </li> </ul> <p> </p> <p><strong>hot-springs-reads.gz </strong></p> <ul> <li>Reads data for Hot Springs dataset</li> </ul> <p> </p> <p><strong>mbarc-reads-download.txt</strong></p> <ul> <li>Reads data for MBARC dataset <ul> <li>Link to download from NCBI</li> </ul> </li> </ul> <p> </p> <p><strong>assemblies.zip</strong></p> <ul> <li>Megahit and MetaSPAdes assemblies for both MBARC and Hot Springs</li> </ul>
Can a Novel Telemedicine Tool Reduce Disparities Related to the Identification of Preschool Children With Autism?
ClinicalTrials.gov study NCT05373173. IPD Sharing: NO. Countries: 1. Publications: 1.
Identification of starch granules on ground stone tools exposed to fire
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Chemical variations in Quercus pollen as a tool for taxonomic identification: implications for long-term ecological and biogeographical research
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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.