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920 results for “Functional analysis”
Fig. 1 in Eukaryotic Microbial Communities Associated with Rock-dwelling Foliose Lichens: A Functional Morphological and Microecological Analysis
Fig. 1. Photograph of a portion of a Flavoparmelia thallus showing an example of a radially oriented lobe with three segments sampled in analyzing the microbial communities: A – inner, B – middle, and C – outer. Scale bar: 5 mm.
EEG functional connectivity analysis for the study of the brain maturation in the first year of life
<p>This dataset is related to 146 typically developing infants who underwent baseline electrophysiological (EEG) data recording at 6 (T6) and 12 (T12) months of age. The recordings were made using a dense-array EGI system (Geodesic EEG System (GES) 300 or 400, Electric Geodesic, In., Eugene, Oregon, USA) equipped with 60/64-electrode or 128-electrode caps (HydroCel Geodesic Sensor net).<br>Whole-brain functional connectivity (FC) metrics were extracted, for multiple frequency bands with the aim to evaluate brain maturation in the first year of life in terms of EEG functional connectivity. In addition, Bayley test was administered at 24 months of age to explore possible relation between brain network connectivity and cognitive functions.</p> <p>The dataset includes subjects’ sociodemographic and individual factors (such as age, sex, socioeconomic status, gestational week and birth weight); functional connectivity metrics (such as the magnitude-squared coherence index, phase lag index (PLI), and parameters characterizing the minimum spanning tree built from the PLI index) computed in the delta (2-4 Hz), theta (4-6 Hz), low-alpha (6-9-Hz), high-alpha (9-13 Hz), beta (13-30 Hz) and gamma (30-45 Hz) frequency bands; and the Bayley test raw scores, assessed at 24 months of age. </p> <p>In particular, each row in the database corresponds to a subject and each column to a different variable.<br>Column A, Subject code;<br>Column B, Time point: 1 = data related to the EEG recording performed at six months of age; 2 = data related to the EEG recording performed at twelve months of age;<br>Column C, Sex: 0= males; 1=females;<br>Column D, Age (expressed in days) at T6;<br>Column E, Age (expressed in days) at T12;<br>Column F, Family socio-economic status;<br>Column G, Gestational age expressed in weeks;<br>Column H, Birth weight expressed in grams;<br>Column I and J, Bayley Cognitive Composite Score and Griffiths developmental quotient both assessed at 6 months of age;<br>Column K and L, Number of electrodes of the used electrode-caps for T6 and T12, respectively;<br>Columns from M to BM, FC metrics for all frequency bands;<br>Columns from BO to BQ, raw cognitive, receptive and expressive Bayley test scores assessed at 24 months of age;<br>Column BR, Composite language metric derived from the expressive and receptive Bayley scores.</p> <p> </p> <p>If you use this dataset please cite the following manucript: Falivene, A.; Cantiani, C.; Dondena, C.; Riboldi, E.M.; Riva, V.; Piazza, C. EEG Functional Connectivity Analysis for the Study of the Brain Maturation in the First Year of Life. Sensors 2024, 24, 4979. All details about subjects, data acquisition and signal processing pipeline are described in the manuscript.</p>
Fig. 6 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 6. Four examples of the tissue expression profiling of unknown distinct unigenes (>500 bp) expressed highly in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis. Relative expression levels were determined as described in Fig. 5.
Fig. 4 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 4. Kyoto encyclopedia of gene and genomes (KEGG) analysis of unigenes expressed highly in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis. Each category contains more than 1 unigene sequences.
Fig. 2 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 2. Clusters of orthologous groups (COG) functional classification of unigenes expressed highly and specifically in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis.
Fig. 1 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 1. Statistics of sequences expressed specifically in each analyzed tissue of Bactrocera dorsalis.
Fig. 5 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 5. Six examples of the tissue expression profiling of predicted distinct unigenes (>500 bp) expressed highly in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis. Relative expression levels were determined by qRT-PCR in head (HE), thorax (TH), abdomen (AB), midgut (MG), fat body (FB), Malpighian tubules (MT), testes (TE), and male accessory glands and ejaculatory duct (MAG) samples from B. dorsalis males. Relative expression levels were calculated based on the value in head, which was ascribed an arbitrary value of 1. Different letters above the bars indicate significant differences based on Tukey's test (P ≤ 0.05).
Fig. 3 in Comparative transcriptome analysis of three Bactrocera dorsalis (Diptera: Tephritidae) organs to identify functional genes in the male accessory glands and ejaculatory duct
Fig. 3. Gene ontology (GO) classification of unigenes expressed highly in male accessory glands and ejaculatory duct tissue of Bactrocera dorsalis.
Example Datasets for Functional Enrichment Analysis
<p>This dataset contains a set of example data for a functional enrichment tutorial.</p>
Language Function Analysis 2011 Corpus (LFA-11)
<p>The Language Function Analysis 2011 Corpus (LFA-11) is a German text corpus of promotional text, reviews and blog posts on music and smartphones. The texts were manually classified with respect to their topic relevance, language function, and sentiment polarity.</p> <p>The purpose of the corpus is to provide textual data for the development and evaluation of approaches to language function analysis and sentiment analysis. Therefore, each text is classified by language function (personal, commercial, or informational) as well as by sentiment (positive, negative, neutral).</p> <p>The corpus consists of two separated collections, which contain the texts about <em>music</em> and <em>smartphones</em> respectively. The music collection consists of 2,713 promotional texts and reviews from both users and professionals. The smartphone collection contains 2,093 blog posts on smartphones from the <a href="http://spinn3r.com/">Spinn3r corpus</a>.</p>
Quantitative results of the analysis of human bioengineered tissues corresponding to the work "Generation of tissue-like models of human bilayered tissues functionalized with olive oil components"
<p>This file contains the raw dataset generated in the work entitled "GENERATION OF NOVEL TISSUE-LIKE MODELS OF HUMAN BILAYERED TISSUES FUNCTIONALIZED WITH BIOACTIVE COMPONENTS OBTAINED FROM OLIVE OIL". These results correspond to the quantification of the histological results obtained in this work.</p>
The dataset of article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis"
<p>This is a file as dataset of the article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis".</p> <p>It includes fMRI brain imaging data of subjects included in the case group (ESRD group) and healthy control group (HC group).</p>
Synchrotron Radiation Pair Distribution Function Analysis of gels in cements
<p>Raw data for: Synchrotron Radiation Pair Distribution Function Analysis of Gels in Cements. doi: https://doi.org/10.3390/cryst7100317</p> <p> </p> <p>The analysis of atomic ordering in a nanocrystalline phase with small particle size, below »5 nm, is intrinsically complicated because of the lack of long range order. Furthermore, the presence of additional crystalline phase(s) may exacerbate the problem as it is the case in cement pastes. Here we use synchrotron pair distribution function (PDF) chiefly to characterize the local atomic order of the nanocrystalline phases, gels, in cement pastes. We have used a multi r-range analysis approach, where the ~4-7 nm r-range allows determining the crystalline phase contents; the ~1-2.5 nm r-range is used to characterize the atomic ordering in the nanocrystalline component; and the ~0.2-1.0 nm r-range give insights about additional amorphous components. Specifically, we have prepared four alite pastes, with variable water contents, and the analyses showed that a defective tobermorite, Ca<sub>11</sub>Si<sub>9</sub>O<sub>28</sub>(OH)<sub>2</sub><sup>.</sup>8.5H<sub>2</sub>O, gave the best fits. Furthermore, the PDF analyses suggest that the calcium silicate hydrate gel is composed of this tobermorite and amorphous calcium hydroxide. Finally, this approach has been used to study alternative cements. The hydration of monocalcium aluminate and ye'elimite pastes yield aluminum hydroxide gels. PDF analyses show that these gels are constituted by nanocrystalline gibbsite and the particle size can be as small as 2.5 nm.</p>
Annotation-based Modeling of Non-functional Requirements and Analysis Results in Domain-driven Design
<p>This repo contains all supplementary data sets that we have created and used throughout this thesis. In particular, it contains<br> - expert interview material (elicitation): consent form and question catalogue for requirements elicitation<br> - expert interview material (evaluation): consent form and task description for expert evaluation<br> - Diagrams related to our modeling concept and Dqualizer<br> - Screenshots of the Domain Story Modeler with our Modeling Concept</p>
Dynamic analysis of pathogenesis and a suppression function of TREM2-dependent macrophages in skin fibrosis
<p>Systemic sclerosis (SSc) is a chronic and incurable autoimmune disease with high mortality rates, and fibrosis is the distinguishing hallmark in the pathogenesis. Identification of the precise, time dependent composition of stromal and immune cells may provide clues for the establishment of new biomarkers and therapeutic approaches targeting SSc fibrosis. Here, the temporal dynamics of pathological process in a mouse model of skin fibrosis is investigated using single-cell RNA-sequencing (scRNA-seq). we collected skin single cell suspensions for transcriptome profiling by scRNA-seq from four time points after BLM-treatment (day 3, 7, 14, and 28) and untreated control skin (day 0) with on average three replicate mice per time point, and repeated once at each time point.{mouse_SSc_scRNAseq_day0_sample1_B1_1, mouse_SSc_scRNAseq_day3_sample1_B2_1, mouse_SSc_scRNAseq_day3_sample2_B2_2, mouse_SSc_scRNAseq_day7_sample1_B3_1, mouse_SSc_scRNAseq_day7_sample2_B3_2, mouse_SSc_scRNAseq_day14_sample1_B4_1, mouse_SSc_scRNAseq_day14_sample2_B4_2, mouse_SSc_scRNAseq_day28_sample1_B5_1, mouse_SSc_scRNAseq_day28_sample2_B5_2}</p>
Quality-aware Analysis and Optimisation of Virtual Network Function
<p># SPLC'22 Quality-aware Analysis and Optimisation of Virtual Network Functions</p><p> </p><p>DATA: Quality-aware Analysis and Optimisation of Virtual Network Functions</p><p> </p><p>This repository contains the models, operations and results empirically used in [Quality-aware Analysis and Optimisation of Virtual Network Functions](https://doi.org/10.1145/3546932.3547007) at SPLC 2022.</p><p>Due to copyright issues, it does not contain the tools (i.e., automated reasoners), although their official sites are provided.</p><p> </p><p>It is licensed under the [MIT license](https://github.com/danieljmg/SPLC22/blob/main/LICENSE).</p><p> </p><p> </p><p>## SPLC'22 Models, Categorical Operations and Datasets</p><p> </p><p>This data-set contains:</p><p> </p><p>1. The 5 SPL categories in CQL alongside the 11 tested operations.</p><p>2. The 5 SPL Clafer models.</p><p>3. The 5 SPL XMLs (for the AAFM Python Framework).</p><p>4. The 5 SPL XMLs (for SATIBEA).</p><p>5. The previous models are enriched with quality attributes measurements at feature and configuration levels.</p><p>6. A Microsoft Excel file with the scalability results obtained.</p><p> </p><p> </p><p>## Automated Reasoners</p><p> </p><p>- CQL IDE: https://github.com/CategoricalData/CQL</p><p>- Clafermoo: http://t3-necsis.cs.uwaterloo.ca:8092/</p><p>- AAFM Python Framework: https://pypi.org/project/famapy/</p><p>- SATIBEA: https://github.com/jmguo/SMTIBEA</p><p> </p><p> </p><p>## Requirements</p><p> </p><p>The data-set has been generated using Java JDK 18.0.2 for CQL IDE, Clafermoo, and SATIBEA, and Python 3.9.13 x86_64 for AAFM Python Framework.</p><p> </p><p>## Authors</p><p> </p><p>1. **[Daniel-Jesus Munoz](https://github.com/danieljmg)**: [ITIS Software](https://www.uma.es/institutos-uma/info/118460/instituto-de-tecnologias-e-ingenieria-del-software/), [CAOSD](http://caosd.lcc.uma.es/), Dpt. LCC, Universidad de Málaga, Andalucía Tech, Spain</p><p>2. **Mónica Pinto**: [ITIS Software](https://www.uma.es/institutos-uma/info/118460/instituto-de-tecnologias-e-ingenieria-del-software/), [CAOSD](http://caosd.lcc.uma.es/), Dpt. LCC, Universidad de Málaga, Andalucía Tech, Spain</p><p>3. **Lidia Fuentes**: [ITIS Software](https://www.uma.es/institutos-uma/info/118460/instituto-de-tecnologias-e-ingenieria-del-software/), [CAOSD](http://caosd.lcc.uma.es/), Dpt. LCC, Universidad de Málaga, Andalucía Tech, Spain</p>
Cross-species analysis identifies mitochondrial dysregulation as a functional consequence of the schizophrenia-associated 3q29 deletion
Open the record for dataset details and reuse information.
Data from: Provenance variation in functional traits of European forest trees: Meta-analysis reveals effects of taxa and age despite critical research gaps
Open the record for dataset details and reuse information.
Refining impact assessment in undergraduate STEM education: Differential item functioning analysis of field-based learning interventions
Open the record for dataset details and reuse information.
Input data for the analysis of changes in functional structures of Japanese tree species by species loss simulation
<p>The dataset was used in Kusumoto, Shiono & Kubota (2020). It includes functional structure indices (community means, functional richness, and Rao's quadratic entropy) for 514 Japanese timber and non-timber tree species at 10-km grid cell level. The community means were based on specific leaf area and leaf nitrogen content, respectively. Functional richness and Rao's Q were based on wood density and tree height. There functional metrics were calculated for the observed species assemblages and simulated assemblages at 10-km grid cell level. The simulated assemblages were computed by removing species in each grid cell at 5 levels of species loss (10%, 20%, 30%, 40% and 50%) with two scenarios: random loss and ordered loss depending on species successional niche score (i.e. later successinal species are preferentially lost). See "README" sheet for detailed explanations of the contents.</p> <p>Kusumoto, Shiono & Kubota (2020) Ethnobotany-informed trait ecology: measuring vulnerability of timber provisioning services across forest biomes in Japan. Biodiversity and Conservation. DOI: 10.1007/s10531-020-01974-y</p>
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.