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368 results for “Consensus”
Figure 7. The strict consensus tree obtained from the parsimony analysis with 35 in Descriptions and phylogenetic relationships of two new genera and four new species of Oligo-Miocene waterfowl (Aves: Anatidae) from Australia
Figure 7. The strict consensus tree obtained from the parsimony analysis with 35 characters ordered. Support values above lines at each node show bootstrap> 50% and Bayesian credibility values> 70% (100% = *). Values below lines are numbers of unambiguous synapomorphies for each node. Clades A, B, and C are referred to in text and Table 4.
Figure 24. Majority-rule consensus trees. A in Phylogeny of cardiid bivalves (cockles and giant clams): revision of the Cardiinae and the importance of fossils in explaining disjunct biogeographical distributions
Figure 24. Majority-rule consensus trees. A, Majority-rule of 16 941 trees from unordered analysis. B, Majority-rule of 208 most parsimonious trees resulting from ordering one character, shell shape. Number in plain typeface indicates percentage of most parsimonious trees which support node. Number in italics (if present) indicates bootstrap support for each node. Number in boldface (if present) indicates Bremer index for each node.
Figure 5. A, strict consensus tree from 11 in A new leptarctine (Carnivora: Mustelidae) from the early Miocene of the northern Tibetan Plateau: implications for the phylogeny and zoogeography of basal mustelids
Figure 5. A, strict consensus tree from 11 shortest trees (tree length = 79 steps) recovered using the Branch and Bound option in PAUP (Swofford, 1993) on a 17 ¥ 31 data matrix (Table 2); B, bootstrap analysis performed on the same data matrix. Numbers at the nodes indicate per cent bootstrap support from heuristic search based on 100 replicates. Only groups with a frequency of greater than 50% are retained.
FASTA consensus sequences obtained using amplicon-based genome sequencing of SARS-CoV-2
<p>Set of 22 FASTA consensus sequences that were produced during routine SARS-CoV-2 sequencing obtained using amplicon-based sequencing (ARTIC protocol). Those sequences were compared to those generated in NASCarD applications.</p>
Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group
<p>Example datasets and code for the recommended implementation of Quantitative Susceptibility Mapping (QSM) in "Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group".</p>
Consensus recommendations for opioid agonist treatment following the introduction of emergency clinical guidelines in Ireland during the COVID-19 pandemic: A national Delphi study
<p>Anonymous Delphi survey likert scale responses (round 1 (S1-S32) and 2 (R2S1-R2S15)) <a href="https://zenodo.org/api/files/92371fe3-6af6-4044-ba3f-83a26b2fe471/Delphi_likert_responses_ano.csv?versionId=7c3aaa7b-8b43-43da-bfeb-fe644f33d3e2">Delphi_likert_responses_ano.csv</a> and corresponding statements in <a href="https://zenodo.org/api/files/92371fe3-6af6-4044-ba3f-83a26b2fe471/STATEMENTS_REPO.csv?versionId=ada85e7c-ba48-4f61-8e1a-d90dab9b4f05">STATEMENTS_REPO.csv</a>.</p>
FIGURE 3 Bayesian consensus tree representing the known Bathynellidae taxa constructed using COI, 16S, 28S, ITS2 and 18S in The role of allopatric speciation and ancient origins of Bathynellidae (Crustacea) in the Pilbara (Western Australia): two new genera from the De Grey River catchment
FIGURE 3 Bayesian consensus tree representing the known Bathynellidae taxa constructed using COI, 16S, 28S, ITS2 and 18S alignments and model partitioning implemented in MrBayes. Numbers on branches represent Bayesian posterior probabilities followed by maximum likelihood bootstrap percentage. Bathynellinae and Gallobathynellinae clades are collapsed for easier interpretation.
FIGURE 2 Bayesian consensus single gene trees for COI, 16S, 28S and ITS2 in The role of allopatric speciation and ancient origins of Bathynellidae (Crustacea) in the Pilbara (Western Australia): two new genera from the De Grey River catchment
FIGURE 2 Bayesian consensus single gene trees for COI, 16S, 28S and ITS2. Numbers on branches represent Bayesian posterior probabilities followed by maximum likelihood bootstrap percentage. ABGD and PTP results are reported next to the trees. ABGD method: major partitions are showed; PTP: partitions with the highest support for each group are represented.
Scrutinizing the protein hydration shell from molecular dynamics simulations against consensus small-angle scattering data (Simulation input files)
<p>Simulation input files for gromacs to reproduce the data from the manuscript "Scrutinizing the protein hydration shell from molecular dynamics simulations against consensus small-angle scattering data" (submitted to Comm. Chem.)</p>
mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA gene
<p>mTAGs is a tool for the taxonomic profiling of metagenomes. It detects sequencing reads belonging to the small subunit of the ribosomal RNA (SSU-rRNA) gene and annotates them through the alignment to full-length degenerate consensus SSU-rRNA reference sequences. The tool is capable of processing single-end and pair-end metagenomic reads, takes advantage of the information contained in any region of the SSU-rRNA gene and provides relative abundance profiles at multiple taxonomic ranks (Domain, Phylum, Class, Order, Family, Genus and OTUs defined at a 97% sequence identity cutoff).</p>
Sunflower consensus scoring
Open the record for dataset details and reuse information.
Opinion dynamics in social network under competition: the role of influencing factors in consensus reaching
Open the record for dataset details and reuse information.
Consensus calling of MinION amplicon reads improves metabarcoding results
<p><strong>Background</strong>: Metabarcoding environmental DNA with high-throughput sequencing is a state-of-the-art method to assess biodiversity and to uncover dark taxa. MinION is the first handheld sequencer that can be taken into the field for on-site metabarcoding. This research aims to answer if bioinformatics can solve the issues that arise because of the higher error rate of MinION data.</p> <p><strong>Results</strong>: Biodiverse samples with a presumed large portion of dark taxa were selected from the Dutch Caribbean. The cytochrome oxidase 1 gene (CO1) is used as a barcode for identification at the species level or higher levels. Generating a consensus sequence from closely related sequences resulted in minimized random errors and increased species identification of 175% compared to unclustered MinION data. Additional to the formulation of the workflow, an ecological analysis was conducted that revealed co-occurrence of species in similar habitats, and that the proportion of dark taxa in the sampled region is 81.87%.</p> <p><strong>Conclusion</strong>: Although the workflow did not attain the results that the existing Illumina workflows do, the potential is evident. The high proportion of dark taxa in the sampled region of Statia and the Saba Bank indicates the need for continued barcoding of species in the Dutch Caribbean to resolve database limitations.</p>
A consistency account of advice taking: Integrating the effects of advice consensus and advice distance
<p>Which factors determine how individuals utilize advice? Previous research focused on either the consensus or the proximity of advice. We develop a general account of advice taking, arguing that both consensus and proximity influence the consistency (or variance) of the information on hand. From this account, we derive a number of predictions regarding the effects of consensus, distance, and amount of advice on confidence, judgment revision, and advice weighting. Across three experiments, we orthogonally manipulated the distance and consensus of advice. The amount of advice was either measured (Experiments 1 and 2) or manipulated (Experiment 3). The results provide strong support for our consistency account of advice taking. It allows explaining a complex pattern of findings that neither consensus nor proximity alone can account for. This research advances our theoretical understanding of advice taking, while adding to a broader literature that highlights the importance of consistency of information for judgment and decision making.</p>
Consensus based framework for digital mobility monitoring
<p>With this dataset, we provide the consensus data obtained in an adapted Delphi process to reach agreement on specific terminology related to real-world walking. </p> <p>A Delphi method was used to obtain agreed definitions related to real-world walking. In an online survey, 162 participants from a panel of academic, clinical and industrial stakeholders were asked for agreement on previously specified definitions. Descriptive statistics was used to evaluate whether consent was reached. Consensus was obtained in two rounds, whereas three definition were modified in the second round.</p> <p>Our dataset is the basis for creating a common terminological framework for the implementation of digital and mobile technologies for gait assessment.</p> <p><strong>Content</strong><br> We provide two .xlsx files:</p> <ul> <li>round1_data.xlsx</li> <li>round2_data.xlsx</li> </ul> <p>The dataset contains the survey results which were implemented on the ILIAS E-learning platform (version 5.4.5, ILIAS open source e-Learning e. V.). Both Excel tables are a direct output from the platform.</p>
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 6. Majority–rule consensus tree from 8 in A new species of the genus Lightiella: the first record of Cephalocarida (Crustacea) in Europe
Figure 6. Majority–rule consensus tree from 8 primary trees.
ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery
<p>All of the individual docking data and ESSENCE-Dock consensus results for 21 diverse DUD-E targets as presented in the paper "ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery".</p> <p>The data is sorted per DUD-E target. It contains the prepared data that was used for the docking calculations (in the Undocked directory), as well as our docking results. Finally, our ESSENCE-Dock Consensus results are included as well</p> <p>Docking calculations were performed using:</p> <ul> <li><a href="https://github.com/bio-hpc/metascreener">Metascreener (V1.1)</a> (Gnina and LeadFinder Calculations; prefix VS_GN_ and VS_LF_ respectively)</li> <li><a href="https://github.com/Jnelen/DiffDockHPC/tree/DiffDockHPCv1.0">DiffDockHPC (v1.0)</a> (DiffDock calculations; prefix VS_DD_ )</li> </ul> <p>The consensus calculations were performed using ESSENCE-Dock, available via <a href="https://github.com/bio-hpc/metascreener">Metascreener </a>as well.</p> <p>The whole methodology and all of the details are described in the ESSENCE-Dock paper: <a href="https://doi.org/10.1021/acs.jcim.3c01982">https://doi.org/10.1021/acs.jcim.3c01982</a></p> <p><strong>Paper Abstract</strong></p> <p>Drug development is a complex, costly, and time-consuming endeavor. While high-throughput screening (HTS) plays a critical role in the discovery stage, it is one of many factors contributing to these challenges. In certain contexts, virtual screening can complement HTS, potentially offering a more streamlined approach in the initial stages of drug discovery. Molecular docking is an example of a popular virtual screening technique that is often used for this purpose, however, its effectiveness can vary greatly. This has led to the use of consensus docking approaches, which combine results from different docking methods to improve the identification of active compounds and reduce the occurrence of false positives. However, many of these methods do not fully leverage the latest advancements in molecular docking.<br>In response, we present ESSENCE-Dock (Effective Structural Screening ENrichment ConsEnsus Dock), a new consensus docking workflow aimed at decreasing false positives and increasing the discovery of active compounds. By utilizing a combination of novel docking algorithms, we improve the selection process for potential active compounds. ESSENCE-Dock has been made to be user-friendly, requiring only a few simple commands to perform a complete screening, while also being designed for use in high-performance computing (HPC) environments.</p>
dataset of Delphi consensus on good practices for the use of technology fto support developmental dyslexia
<p>The dataset reports the answers collected during phase 2 and 3 of the Delphi survey conducted among Italian experts to define good practices for the use of technologies to support children with Developmental Dyslexia.All answers are expressed on a scale from 1 = strongly disagree to 5 = strongly agree.</p>
Building consensus for ambitious climate action through the World Climate Simulation
<p>Sociopolitical values are an important driver of climate change beliefs, attitudes, and policy preferences. People with 'individualist-hierarchical' values favor individual freedom, competition, and clearly defined social hierarchies, while communitarian-egalitarians value interdependence and equality across gender, age, heritage, and ethnicity. In the US, individualist-hierarchs generally perceive less risk from climate change and express lower support for actions to mitigate it than communitarian-egalitarians. Exposure to scientific information does little to change these views. Here, we ask if a widely-used experiential simulation, World Climate, can help overcome these barriers. World Climate combines an engaging role-play with an interactive computer model of the climate system. We examine pre- and post-World Climate survey responses from 2,080 participants in the US and use a general linear mixed model approach to analyze interactions among participants' sociopolitical values and gains in climate change knowledge, affect, and intent to take action. As expected, prior to the simulation, participants holding individualist-hierarchical values had lower levels of climate change knowledge, felt less urgency, and expressed lower intent to act than those holding communitarian-egalitarian values. However, individualist-hierarchs made significantly larger gains across all constructs, particularly urgency, than communitarian-egalitarians. Participants' sociopolitical values also shifted: those with individualistic-hierarchical values before the simulation showed a substantial, statistically significant shift toward a communitarian-egalitarian worldview. Simulation-based experiences like World Climate may help reduce polarization and build consensus towards science-based climate action.</p>
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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)
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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.