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Dataset results
59 results for “sparse data”
Data from: A low-threshold potassium current enhances sparseness and reliability in a model of avian auditory cortex
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Data from: Mapping beta diversity from space: Sparse Generalized Dissimilarity Modelling (SGDM) for analysing high-dimensional data
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Data from: Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices
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Data sets used in the manuscript titled "Ecosystem-level energy and water budgets are resilient to canopy mortality in sparse semi-arid biomes"
<p><span>This data set reports water and energy fluxes, soil water content and sap fluxes measured at two adjacent pinon-juniper woodlands in central New Mexico from January 2009 to December 2016. This data set was used for the analysis in the manuscript titled "Ecosystem-level energy and water budgets are resilient to canopy mortality in sparse semi-arid biomes" submitted to JGR-Biogeosciences. </span></p>
Heusinkveld_et_al_Complementing_sparse_vascular_imaging data_JAPPL
<p>Source Data belonging to the Manuscript entitled:</p> <p>Complementing sparse vascular imaging data by physiological adaptation rules</p>
Data from: Linking genetic merit to sparse behavioral data: does behavior explain genetic variation for maternal care in Soay sheep?
Wild quantitative genetic studies have focused on a subset of traits (largely morphological and life-history), with others, such as behaviors, receiving much less attention. This is because it is challenging to obtain sufficient data, particularly for behaviors involving interactions between individuals. Here, we explore an indirect approach for pilot investigations of the role of genetic differences in generating variation in parental care. Variation in parental genetic effects for offspring performance is expected to arise from among-parent genetic variation in parental care. Therefore, we used the animal model to predict maternal breeding values for lamb growth and used these predictions to select females for field observation, where maternal and lamb behaviors were recorded. Higher predicted maternal breeding value for lamb growth was associated with greater suckling success, but not with any other measures of suckling behavior. Though our work cannot explicitly estimate the genetic basis of the specific traits involved, it does provide a strategy for hypothesis generation and refinement, that we hope could be used to justify data collection costs needed for confirmatory studies. Here results suggest that behavioral genetic variation is involved in generating maternal genetic effects on lamb growth in Soay sheep. Though important caveats and cautions apply, our approach may extend the ability to initiate more genetic investigations of difficult-to-study behaviours and social interactions in natural populations.
Data from: Mutation rules and the evolution of sparseness and modularity in biological systems
Biological systems exhibit two structural features on many levels of organization: sparseness, in which only a small fraction of possible interactions between components actually occur; and modularity – the near decomposability of the system into modules with distinct functionality. Recent work suggests that modularity can evolve in a variety of circumstances, including goals that vary in time such that they share the same subgoals (modularly varying goals), or when connections are costly. Here, we studied the origin of modularity and sparseness focusing on the nature of the mutation process, rather than on connection cost or variations in the goal. We use simulations of evolution with different mutation rules. We found that commonly used sum-rule mutations, in which interactions are mutated by adding random numbers, do not lead to modularity or sparseness except for in special situations. In contrast, product-rule mutations in which interactions are mutated by multiplying by random numbers – a better model for the effects of biological mutations – led to sparseness naturally. When the goals of evolution are modular, in the sense that specific groups of inputs affect specific groups of outputs, product-rule mutations also lead to modular structure; sum-rule mutations do not. Product-rule mutations generate sparseness and modularity because they tend to reduce interactions, and to keep small interaction terms small.
Data from: Direction matching for sparse movement data sets: determining interaction rules in social groups
It is generally assumed that high-resolution movement data are needed to extract meaningful decision-making patterns of animals on the move. Here we propose a modified version of force matching (referred to here as direction matching), whereby sparse movement data (i.e., collected over minutes instead of seconds) can be used to test hypothesized forces acting on a focal animal based on their ability to explain observed movement. We first test the direction matching approach using simulated data from an agent-based model, and then go on to apply it to a sparse movement data set collected on a troop of baboons in the DeHoop Nature Reserve, South Africa. We use the baboon data set to test the hypothesis that an individual's motion is influenced by the group as a whole or, alternatively, whether it is influenced by the location of specific individuals within the group. Our data provide support for both hypotheses, with stronger support for the latter. The focal animal showed consistent patterns of movement toward particular individuals when distance from these individuals increased beyond 5.6 m. Although the focal animal was also sensitive to the group movement on those occasions when the group as a whole was highly clustered, these conditions of isolation occurred infrequently. We suggest that specific social interactions may thus drive overall group cohesion. The results of the direction matching approach suggest that relatively sparse data, with low technical and economic costs, can be used to test between hypotheses on the factors driving movement decisions.
Data from: Building the avian tree of life using a large-scale, sparse supermatrix
Birds are the most diverse tetrapod class, with about 10,000 extant species that represent a remarkable evolutionary radiation in which most taxa arose during a short period of time. There has been a tremendous increase in the amount of molecular data available from birds, and more than two-thirds of these species have some sequence data available. Here we assembled these available sequence data from birds to estimate a large-scale avian phylogeny. We performed an unconstrained maximum likelihood analysis of a sparse supermatrix comprising 22 nuclear loci and seven mitochondrial regions from 6714 species. We inferred a phylogeny with a backbone remarkably similar to that obtained by detailed analyses of multigene datasets, yet with the addition of thousands of more taxa. All orders were monophyletic with generally high support. While most families and genera were well supported, a number of them, especially within the oscine passerines, had little or no support. This likely reflects problems with the circumscription of these genera and families. Our results indicate that the amount of sequence data currently available is sufficient to produce a robust estimate of the avian tree of life using current methods of inference. The availability of a tree that is unconstrained by prior information, with branch lengths that have a direct connection to the underlying data, should be useful for comparative methods, taxonomic revisions, and prioritizing taxa that should be targeted for additional data collection.
Data from: Reliable species distributions are obtainable with sparse, patchy and biased data by leveraging over species and data types
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Data from: Linking genetic merit to sparse behavioral data: does behavior explain genetic variation for maternal care in Soay sheep?
Open the record for dataset details and reuse information.
Data from: Mutation rules and the evolution of sparseness and modularity in biological systems
Open the record for dataset details and reuse information.
Data sets used in the manuscript titled "Ecosystem-level energy and water budgets are resilient to canopy mortality in sparse semi-arid biomes"
Open the record for dataset details and reuse information.
Data from: Direction matching for sparse movement data sets: determining interaction rules in social groups
Open the record for dataset details and reuse information.
Data from: Building the avian tree of life using a large-scale, sparse supermatrix
Open the record for dataset details and reuse information.
Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data
GEO Series GSE144623. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
Gene expression data from hCdc73 knock-down HEK293 cells under confluent and sparse condition.
GEO Series GSE61601. Homo sapiens. 4 samples. Type: Expression profiling by array.
Sparse wavelengths data in mid-infrared spectroscopy: Modelling approaches and channel sampling
<p>Milk and fungi dataset (already split in calibration and test set) in .mat format + MATLAB workspaces for i) variable selection (for milk and fungi); ii) PLSR on broadband spectra (for milk and fungi) iii) PLSR on single wavelengths (for milk and fungi); iv) PLSR on tuned wavelengths (for milk and fungi); v) PLSR test for fungi on milk selected wavelengths (FM_).</p>
3’ RNA-seq of whole organisms is superior to standard in cases of sparse data but inferior with respect to identified functions
GEO Series GSE214481. Danio rerio. 6 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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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.