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20 results for “Shuffling”
The Cassandra retrotransposon landscape in sugar beet (Beta vulgaris): Recombination and re-shuffling leads to a high structural variability
<p>Here we provide supplementary data for our study of non-autonomous Cassandra terminal-repeat retrotransposons in miniature (TRIMs) in sugar beet and related genomes.</p> <p>Cassandra sequences are distributed across the plant kingdom and share a unique feature: conserved 5S rDNA promoter motifs within their long terminal repeats (LTRs). This dataset contains two multiple sequence alignments and a sequence list of tandemly-arranged (TA) Cassandra sequences in FASTA format. Alignments cover LTR and internal regions of all Amaranthaceae Cassandra (Ama-Cassandra) from our study. This includes Cassandra full-length sequences from <em>B. vulgaris</em> (Ama_Cassandra_Beet_full-length) and <em>C. quinoa</em> (Ama_Cassandra_Quinoa_full-length). Sequence names include information on host plant, subfamily classification, localisation (scaffold), start and stop position, a Lab-unique TE identifier and sequence orientation. For the tandemly-arranged Cassandra sequences from sugar beet, we provide a sequence list of twelve sequences (Ama_Cassandra_TA_Beet_list). Here, sequence names refer to TA copy number, host, localisation (scaffold), start and stop position, a Lab-unique TE identifier and sequence orientation.</p> <p>All sequences were identified in the recent genome assemblys of <em>B. vulgaris</em> (RefBeet1.2; Dohm <em>et al</em>. 2014) and <em>C. quinoa</em> (ASM168347v1; Jarvis <em>et al</em>., 2017).</p>
Dataset "Shuffling Softy, Sighing Deeply"
<p>Dataset used for the analyses in the research article "Shuffling Softly, Sighing Deeply: A Digital Inquiry into Representations of Older Men and Women in Literature for Different Ages" submitted to the journal <em>Social Sciences</em>. Data was obtained using a syntactic parser developed in collaboration with TEXTUA, the Text Mining Centre of the University of Antwerp. For copyright reasons, part of the data, which contains full sentences from the texts, was removed. However, the resulting dataset is sufficient to replicate the study.</p> <p>The filenames are formatted as follows: age of the intended reader_AUTHOR_book title_year_character's age_gender_word type.json</p> <p>The following word types associated with relevant characters were extracted from the texts:</p> <ul> <li>1: verbs</li> <li>2: possessions</li> <li>3: attributive adjectives</li> <li>4: predicative adjectives</li> </ul>
DWAEF_Sarc_Dataset & simile_non_simile_shuffled
<p>'DWAEF_Sarc_Dataset' was compiled for the deep weighted average ensemble-based framework (DWAEF). This dataset contains 2,891 sentences written in English. The sentences have been sourced from various platforms, including Twitter, News Headlines and the SARC datasets. Out of these, 1,538 were sarcastic and were compiled from various sources- i) 520 sentences were extracted from Twitter with hashtags- #sarcasm, #not, #sarcastic, #irony, #satire between the time period of June 2022-October 2022; ii) 520 were taken from the News Headlines dataset.; iii) remaining 498 were taken from the SARC dataset.. The 1,353 non-sarcastic sentences were compiled from Twitter and the News Headlines dataset. These sources do not belong to the same domain or topic. Twitter data, for instance, encompasses a broad range of subjects, whereas News Headlines may concentrate on specific areas, such as politics, sports, or entertainment.</p> <p>For pretraining the GNN-based framework for simile detection the present study curated a dataset 'simile_non_simile_shuffled' comprising approximately 3,512 English language sentences that have been systematically categorized into two groups, i.e., sentences containing similes and those that do not. The dataset was curated through online sources and it underwent a rigorous process of double-annotation to ensure its accuracy and reliability. This dataset offers the opportunity for future research on the impact of similes in both written and spoken language, thereby contributing to a better understanding of figurative language in general.</p>
Research data supporting: "Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling"
<p>This repository contains the set of data shown in the paper "Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling" published on PNAS (DOI: 10.1073/pnas.2300565120).</p>
Updating splits, lumps, and shuffles: Reconciling GenBank names with standardized avian taxonomies
Abstract Biodiversity research has advanced by testing expectations of ecological and evolutionary hypotheses through the linking of large-scale genetic, distributional, and trait datasets. The rise of molecular systematics over the past 30 years has resulted in a wealth of DNA sequences from around the globe. Yet, advances in molecular systematics also have created taxonomic instability, as new estimates of evolutionary relationships and interpretations of species limits have required widespread scientific name changes. Taxonomic instability, colloquially "splits, lumps, and shuffles," presents logistical challenges to large-scale biodiversity research because (1) the same species or sets of populations may be listed under different names in different data sources, or (2) the same name may apply to different sets of populations representing different taxonomic concepts. Consequently, distributional and trait data are often difficult to link directly to primary DNA sequence data without extensive and time-consuming curation. Here, we present RANT: Reconciliation of Avian NCBI Taxonomy. RANT applies taxonomic reconciliation to standardize avian taxon names in use in NCBI GenBank, a primary source of genetic data, to a widely used and regularly updated avian taxonomy: eBird/Clements. Of 14,341 avian species/subspecies names in GenBank, 11,031 directly matched an eBird/Clements; these link to more than 6 million nucleotide sequences. For the remaining unmatched avian names in GenBank, we used Avibase's system of taxonomic concepts, taxonomic descriptions in Cornell's Birds of the World, and DNA sequence metadata to identify corresponding eBird/Clements names. Reconciled names linked to more than 600,000 nucleotide sequences, ~9% of all avian sequences on GenBank. Nearly 10% of eBird/Clements names had nucleotide sequences listed under 2 or more GenBank names. Our taxonomic reconciliation is a first step towards rigorous and open-source curation of avian GenBank sequences and is available at GitHub, where it can be updated to correspond to future annual eBird/Clements taxonomic updates.
Updating splits, lumps, and shuffles: Reconciling GenBank names with standardized avian taxonomies
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Accelerated genome shuffling associated with rapid evolution of sexual conflicts in seed beetles
<p><strong><span>Accelerated genome shuffling associated with rapid evolution of sexual conflicts in seed beetles</span></strong></p>
Data from: Investigating the causes and consequences of symbiont shuffling in a multi-partner reef coral symbiosis under environmental change
Dynamic symbioses may critically mediate impacts of climate change on diverse organisms, with repercussions for ecosystem persistence in some cases. On coral reefs, increases in heat-tolerant symbionts after thermal bleaching can reduce coral susceptibility to future stress. However, the relevance of this adaptive response is equivocal owing to conflicting reports of symbiont stability and change. We help reconcile this conflict by showing that change in symbiont community composition (symbiont shuffling) in Orbicella faveolata depends on the disturbance severity and recovery environment. The proportion of heat-tolerant symbionts dramatically increased following severe experimental bleaching, especially in a warmer recovery environment, but tended to decrease if bleaching was less severe. These patterns can be explained by variation in symbiont performance in the changing microenvironments created by differentially bleached host tissues. Furthermore, higher proportions of heat-tolerant symbionts linearly increased bleaching resistance but reduced photochemical efficiency, suggesting that any change in community structure oppositely impacts performance and stress tolerance. Therefore, even minor symbiont shuffling can adaptively benefit corals, although fitness effects of resulting trade-offs are difficult to predict. This work helps elucidate causes and consequences of dynamism in symbiosis, which is critical to predicting responses of multi-partner symbioses such as O. faveolata to environmental change.
Data from: Evolutionary novelty in a butterfly wing pattern through enhancer shuffling
An important goal in evolutionary biology is to understand the genetic changes underlying novel morphological structures. We investigated the origins of a complex wing pattern found among Amazonian Heliconius butterflies. Genome sequence data from 142 individuals across 17 species identified narrow regions associated with two distinct red colour pattern elements, dennis and ray. We hypothesise that these modules in non-coding sequence represent distinct cis-regulatory loci that control expression of the transcription factor optix, which in turn controls red pattern variation across Heliconius. Phylogenetic analysis of the two elements demonstrated that they have distinct evolutionary histories and that novel adaptive morphological variation was created by shuffling these cis-regulatory modules through recombination between divergent lineages. In addition, recombination of modules into different combinations within species further contributes to diversity. Analysis of the timing of diversification in these two regions supports the hypothesis of introgression moving regulatory modules between species, rather than shared ancestral variation. The dennis phenotype introgressed into Heliconius melpomene at about the same time that ray originated in this group, while ray introgressed back into H. elevatus much more recently. We show that shuffling of existing enhancer elements both within and between species provides a mechanism for rapid diversification and generation of novel morphological combinations during adaptive radiation.
Data from: Permutation tests for phylogenetic comparative analyses of high-dimensional shape data: what you shuffle matters
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Data from: A new method to localize and test the significance of incongruence: detecting domain shuffling in the nuclear receptor superfamily
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Data from: Investigating the causes and consequences of symbiont shuffling in a multi-partner reef coral symbiosis under environmental change
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Data from: Evolutionary novelty in a butterfly wing pattern through enhancer shuffling
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Histone H3 K56 acetylation in wild-type histone shuffle strain (YBL574)
GEO Series GSE37039. Saccharomyces cerevisiae. 12 samples. Type: Genome binding/occupancy profiling by array.
Hi-C guided assemblies reveal conserved regulatory topologies on X and autosomes despite extensive genome shuffling [HiC]
GEO Series GSE120751. Drosophila virilis; Drosophila melanogaster; Drosophila busckii. 5 samples. Type: Other; Third-party reanalysis.
Mobilization of Pack-CACTA transposons in Arabidopsis suggests the mechanism of gene shuffling
GEO Series GSE120571. Arabidopsis thaliana. 70 samples. Type: Genome variation profiling by high throughput sequencing.
Hi-C guided assemblies reveal conserved regulatory topologies on X and autosomes despite extensive genome shuffling
GEO Series GSE120752. Drosophila melanogaster; Drosophila virilis; Drosophila busckii. 17 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
speedingCARs: accelerating the engineering of CAR T cells by signaling domain shuffling and single-cell sequencing
GEO Series GSE214231. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
Hi-C guided assemblies reveal conserved regulatory topologies on X and autosomes despite extensive genome shuffling [ChIP-seq]
GEO Series GSE120750. Drosophila virilis; Drosophila busckii. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Shuffling the yeast genome using CRISPR/Cas9-generated DSBs that target the transposable Ty1 elements
GEO Series GSE205199. Saccharomyces cerevisiae. 18 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
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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)
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.