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1,481 results for “data processing”
Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild
The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed inference when addressing evolutionary questions. Hierarchical modelling (HM) has been proposed as a generic statistical framework to deal with complexity in ecological data and account for uncertainty. However, to date, HM has seldom been used to investigate evolutionary mechanisms possibly underlying observed patterns. Here, we contend the HM approach offers a relevant approach for the study of eco-evolutionary processes in the wild by confronting formal theories to empirical data through proper statistical inference. Studying eco-evolutionary processes requires considering the complete and often complex life histories of organisms. We show how this can be achieved by combining sequentially all life histories components and all available sources of information through HM. We demonstrate how eco-evolutionary processes may be poorly inferred or even missed without using the full potential of HM. As a case study, we use the Atlantic salmon and data on wild marked juveniles. We assess a reaction norm for migration and two potential trade-offs for survival. Overall, HM has a great potential to address evolutionary questions and investigate important processes that could not previously be assessed in laboratory or short time-scale studies.
Data from: State-dependent judgement bias in Drosophila: evidence for evolutionarily primitive affective processes
Affective states influence decision-making under ambiguity in humans and other animals. Individuals in a negative state tend to interpret ambiguous cues more negatively than individuals in a positive state. We demonstrate that the fruit fly, Drosophila melanogaster, also exhibits state-dependent changes in cue interpretation. Drosophila were trained on a Go/Go task to approach a positive (P) odour associated with a sugar reward and actively avoid a negative (N) odour associated with shock. Trained flies were then either shaken to induce a purported negative state or left undisturbed (control), and given a choice between: air or P; air or N; air or ambiguous odour (1:1 blend of P:N). Shaken flies were significantly less likely to approach the ambiguous odour than control flies. This 'judgement bias' may be mediated by changes in neural activity that reflect evolutionarily primitive affective states. We cannot say whether such states are consciously experienced, but utilisation of this model organism's versatile experimental tool kit may facilitate elucidation of their neural and genetic basis.
Data from: Rapid diversification of sperm precedence traits and processes among three sibling Drosophila species
Postcopulatory sexual selection is credited with driving rapid evolutionary diversification of reproductive traits and the formation of reproductive isolating barriers between species. This judgment, however, has largely been inferred rather than demonstrated due to general lack of knowledge about processes and traits underlying variation in competitive fertilization success. Here, we resolved processes determining sperm fate in twice-mated females, using transgenic Drosophila simulans and D. mauritiana populations with fluorescently-labeled sperm heads. Comparisons among these two species and D. melanogaster revealed a shared motif in the mechanisms of sperm precedence, with postcopulatory sexual selection potentially occurring during any of the three discrete stages: (1) insemination, (2) sperm storage, and (3) sperm use for fertilization, and involving four distinct phenomena: (1) sperm transfer, (2) sperm displacement, (3) sperm ejection, and (4) sperm selection for fertilizations. Yet, underlying the qualitative similarities were significant quantitative differences in nearly every relevant character and process. We evaluate these species differences in light of concurrent investigations of within-population variation in competitive fertilization success and postmating/prezygotic reproductive isolation in hybrid matings between species to forge an understanding of the relationship between microevolutionary processes and macroevolutionary patterns as pertains to postcopulatory sexual selection in this group.
Data from: Resource composition mediates the effects of intraspecific variability in nutrient recycling on ecosystem processes
Despite the growing evidence for individual variation in trophic niche within populations, its potential indirect effects on ecosystem processes remains poorly understood. In particular, few studies have investigated how intraspecific trophic variability can modulate the effects of consumers on ecosystems through potential changes in nutrient excretion rates. Here, we first quantified the level of intraspecific trophic variability in 11 wild populations of the omnivorous fish Lepomis gibbosus. Outputs from stomach content and stable isotope analyses revealed that the degree of trophic specialization and trophic positions were highly variable between and within these wild populations. There was intrapopulation variation in trophic position of more than one trophic level, suggesting that individuals consumed a range of plant and animal resources. We then experimentally manipulated intraspecific trophic variability to assess how it can modulate consumer-mediated nutrient effects on relevant processes of ecosystem functioning. Specifically, three food sources varying in nutrient quality (e.g. plant material, macro-invertebrate and fish meat) were used individually or in combination to simulate seven diet treatment. Results indicated that intraspecific variability in growth and nitrogen excretion rates were more related to the composition of the diet rather than the degree of specialization, and increased with the trophic position of the diet consumed. We subsequently used microcosms and showed that critical ecosystem functions, such as primary production and community respiration, were affected by the variability in excretory products, and this effect was biomass-dependent. These results highlight the importance of considering variation within species to better assess the effects of individuals on ecosystems and, more specifically, the effects of consumer-mediated nutrient recycling because the body size and the trophic ecology of individuals are affected by a large spectrum of natural and human-induced environmental changes.
Data from: Patterns and processes in complex landscapes: testing alternative biogeographic hypotheses through integrated analysis of phylogeography and community ecology in Hawai'i
The Island of Hawai'i is a dynamic assemblage of five volcanoes with wet forest habitat currently existing in four distinct natural regions that vary in area, age, and geographic isolation. In this complex landscape, alternative assumptions of the relative importance of specific habitat characteristics on evolutionary and ecological processes predict strikingly different general patterns of local diversity and regional similarity. In this study we compare alternative a priori hypotheses against observed patterns within two distinct biological systems and scales: community composition of wet forest vascular plant species and mitochondrial and nuclear genes of Drosophila sproati, a wet forest restricted endemic. All observed patterns display strong and similar regional structuring, with the greatest local diversity found in Kohala and the windward side of Mauna Loa, the least in Ka'ū and Kona, and a distinctive pattern of regional similarity that likely reflects the historical development of this habitat on the island. These observations largely corroborate a biogeographic model that integrates multiple lines of evidence, including climatic reconstruction, over those relying on single measures, such as current habitat configuration or substrate age. This method of testing alternative hypotheses across biological systems and scales is an innovative approach for understanding complex landscapes and should prove valuable in diverse biogeographic systems.
Data from: Neutral genetic processes influence MHC evolution in threatened gopher tortoises (Gopherus polyphemus)
Levels of adaptive genetic variation influence how species deal with environmental and ecological change, but these levels are frequently inferred using neutral genetic markers. Major histocompatibility complex (MHC) genes play a key role in the adaptive branch of the immune system and have been used extensively to estimate levels of adaptive genetic variation. Parts of the peptide binding region, sites where MHC molecules directly interact with pathogen and self-proteins, were sequenced from a MHC class I (95/441 tortoises) and class II (245/441 tortoises) gene in threatened and non-threatened populations of gopher tortoises (Gopherus polyphemus), and adaptive genetic variation at MHC genes was compared to neutral genetic variation derived from 10 microsatellite loci (441 tortoises). Genetic diversity at the MHC class II locus and microsatellites was greater in populations in the non-threatened portion of the gopher tortoise's range (MHC class II difference in mean A = 8.11, AR = 0.79, HO = 0.51, and HE = 0.16; microsatellite difference in mean A = 1.05 and AR = 0.47). Only MHC class II sequences showed evidence of positive selection (dN/dS > 1, Z = 1.81, P = 0.04). Historical gene flow as estimated with Migrate-N was greater than recent migration estimated with BayesAss, suggesting that populations were better connected in the past when habitat was less fragmented. MHC genetic differentiation was correlated with microsatellite differentiation (Mantel r = 0.431, P = 0.001) suggesting neutral genetic processes are influencing MHC evolution, and advantageous MHC alleles could be lost due to genetic drift.
Data from: Differential neural processing during motor imagery of daily activities in chronic low back pain patients
Chronic low back pain (chronic LBP) is both debilitating for patients but also a major burden on the health care system. Previous studies reported various maladaptive structural and functional changes among chronic LBP patients on spine- and supraspinal levels including behavioral alterations. However, evidence for cortical reorganization in the sensorimotor system of chronic LBP patients is scarce. Motor Imagery (MI) is suitable for investigating the cortical sensorimotor network as it serves as a proxy for motor execution. Our aim was to investigate differential MI-driven cortical processing in chronic LBP compared to healthy controls (HC) by means of functional magnetic resonance imaging (fMRI). Twenty-nine subjects (15 chronic LBP patients, 14 HC) were included in the current study. MI stimuli consisted of randomly presented video clips showing every-day activities involving different whole-body movements as well as walking on even ground and walking downstairs and upstairs. Guided by the video clips, subjects had to perform MI of these activities, subsequently rating the vividness of their MI performance. Brain activity analysis revealed that chronic LBP patients exhibited significantly reduced activity compared to HC subjects in MI-related brain regions, namely the left supplementary motor area and right superior temporal sulcus. Furthermore, psycho-physiological-interaction analysis yielded significantly enhanced functional connectivity (FC) between various MI-associated brain regions in chronic LBP patients indicating diffuse and non-specific changes in FC. Current results demonstrate initial findings about differences in MI-driven cortical processing in chronic LBP pointing towards reorganization processes in the sensorimotor network.
Pre-processed B-cell receptor amplicon sequencing data from SRR1842411
<p>An example dataset containing B-cell receptor (BCR) gene sequences. This dataset is intended to be used for testing software tools developed to annotate (i.e. map Variable, Diversity and Joining segments) and perform clonal analysis of BCR sequencing data.</p> <p><strong>Sequencing:</strong></p> <p>Libraries prepared using 5'RACE from PBMCs of a healthy donor. Input molecules were tagged with unique molecular identifiers (UMIs). Sequencing was ran on MiSeq , 300+300bp reads.</p> <p><strong>Contents:</strong></p> <p>The dataset contains both raw sequencing reads and high-quality consensus sequences assembled using unique molecular tagging (UMI) approach. Consensus assembly corrects for sequencing errors and eliminates sequencing artifacts.</p> <ul> <li>age_ig_s7_R1.fastq.gz and age_ig_s7_R2.fastq.gz contain raw reads</li> <li>age_ig_s7_R1.t10.cf.fastq.gz and age_ig_s7_R2.t10.cf.fastq.gz contain consensus sequences</li> </ul> <p>All files contain an UMI tag sequence in their header, in form UMI:NNNN:QQQQ where N is the base character and Q is the quality character (for assembled consensuses the total number of reads is given instead of Q string).</p> <p>Note that consensus sequences were assembled using only raw sequences that correspond to UMI tags supported by at least 10 sequencing reads. That means that consensus sequence files contain a subset of all UMI tags found in raw sequences. Thus, if one wants to assess software performance on raw sequencing reads using assembled consensus sequences as a high-quality data standard, raw sequencing reads should be filtered to contain only those UMI tags that are present in consensus sequence file.</p> <p><strong>Citations:</strong></p> <p>The whole dataset was used to benchmark MiXCR software and was originally referenced in Bolotin DA, et al. MiXCR: software for comprehensive adaptive immunity profiling Nature methods 12(5):380-381, 2015.</p> <p>Data pre-processing was carried out using MIGEC software, Shugay M et al. Towards error-free profiling of immune repertoires. Nature Methods 11(6):653-655, 2014.</p> <p><strong>Contributors:</strong></p> <p>The dataset was generated in Prof. Chudakov lab (Adaptive Immunity Group in Masaryk University, Brno and Genomics of Adaptive Immunity Lab in Institute of Bioorganic Chemistry, Moscow). Sample preparation and sequencing was performed by Dr. Olga Britanova and Dr. Maria Turchaninova. Raw sequencing reads were pre-processed and uploaded by Dr. Mikhail Shugay.</p>
Data_processing_v.4alcrlp
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Sequence data processing R script
<p>R script used for processing the 16S Illumina paired end read data using the DADA2 pipeline.</p><p> </p>
DATA PROCESSING BASCULAS
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Observed data and processed data
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Data for "The increase in prevalence of natural products through the drug discovery process"
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Processed CODEX multiplexed imaging data of cellular microenvironment around T cell stimulating hydrogels
<p>Our research used CODEX (Co-Detection by Indexing) multiplexed imaging to gain insights into the cellular microenvironment surrounding T cell stimulating hydrogels. These hydrogels were engineered with signals that could locally expand antigen-specific T cells for use in tumor immunotherapy. CODEX imaging involves an iterative process of annealing and stripping fluorophore-labeled oligonucleotide barcodes, complementing the barcodes attached to over 40 antibodies used for tissue staining. Subsequently, images underwent standard CODEX image processing (tile stitching, drift compensation, cycle concatenation, background subtraction, deconvolution, and determination of best focal plane), single cell segmentation, and column marker z-normalization by tissue.</p> <p>Our datasets comprise individual cells as rows, each characterized by 40+ antibody fluorescence values quantified from various markers evaluated for each study. These markers correspond to the antibodies targeting specific proteins within the tissue, quantified at the single-cell level. The values represent per-cell/area-averaged fluorescent intensities, z-normalized along each column. Each cell is mapped with its cell type, defined by x and y coordinates representing pixel locations in the original image. </p> <p>We then used this data to investigate how different proportions of the cell types change over time in response to the stimulating hydrogel injection with antigen-specific T cells. These data could be used to understand the cellular interactions, composition, and structure of T cell stimulating biomaterials for antigen-specific immunotherapy and with adoptive T cell transfer. These datasets offer valuable insights for researchers interested in engineering T cell stimulating microenvironments, immune responses, and therapeutic interventions such as T cell therapies.</p> <p>We investigate the dynamic interplay between immune responses, antigen-specific T cell interactions, and hydrogel environment in a murine melanoma model. We injected antigen-specific T cells with microparticle T cell stimulating hydrogels into mice subcutaneously. Injection sites were take out at different time points day=0 (just after injection), day=3, and day=9 (n=3-6 per time point). Our 51-plex CODEX antibody panel characterizes immune cell types, T cell phenotypes, and stromal cell types, resulting in a rich dataset of 241,685 cells across 51 marker channels.</p>
EO4EU-UC6-Processed-Data
<p>Processed data of ERA5 land for EO4EU UC5 use case.</p>
Mouse Stereo-seq - processed data
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MySQL dump for finding optimal parameters for data augmentation techniques in publication "Leveraging Data Augmentation for Process Information Extraction"
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Processed mass spectrometry data - systematic identification of allosteric effectors in Escherichia coli metabolism
<p>MATLAB files of processed mass spectrometry data, i.e. full data table after peak picking, annotation and quantification. Additionally, for each of the tested enzymes, the relevant ion traces of substrates and products are extracted, sorted by timepoint and replicate and saved in separate tables.</p>
Supplementary data to: Unravelling driving conditions of rock and ice avalanches and resulting cascading processes in High Mountain Asia
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data for "Importance of Strains in Kinetic Energy Conversion for Submesoscale Processes from an Anisotropic Perspective "
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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.