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165
datasets available to search
ShareScore release 0.9.0
Dataset results
165 results for “conversational data”
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_HT29_batchB
GEO Series GSE250623. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_HepG2_batchE
GEO Series GSE248974. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_HT29_batchA
GEO Series GSE250621. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_A549_batchD
GEO Series GSE252817. Homo sapiens. 59 samples. Type: Expression profiling by high throughput sequencing.
Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data
GEO Series GSE229504. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_A549_batchA
GEO Series GSE252814. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_SW1783_batchC
GEO Series GSE254453. Homo sapiens. 59 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_SW1783_batchB
GEO Series GSE254452. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_HT29_batchE
GEO Series GSE250626. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_SW1783_batchE
GEO Series GSE254457. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_SW1783_batchA
GEO Series GSE254450. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_SW1783_batchD
GEO Series GSE254455. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Effect of performing SLAM-seq chemistry in methanol fixed cells versus standard tube processing on quantification bias in nucleotide conversion RNA-seq data
GEO Series GSE253370. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data
GEO Series GSE229506. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_HepG2_batchD
GEO Series GSE248973. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Digital transformation of herbal medicine: Conversion to biological entity data using digestive herbal medicine-induced transcriptome sequencing_second_HepG2_batchB
GEO Series GSE248970. Homo sapiens. 60 samples. Type: Expression profiling by high throughput sequencing.
Data from: The intake pattern and feed preference of layer hens selected for high or low feed conversion ratio
Feed accounts for the greatest proportion of laying hen egg production costs and there is substantial variation in feed to egg conversion (FCR) efficiency between individual hens. Despite this understanding, there is a paucity of information regarding layer hen feeding behaviour, diet selection and its impact on feed efficiency. It was hypothesised that variation in feed to egg conversion efficiency between hens may be influenced by feeding behaviour. For this experiment, two 35- bird groups of ISA Brown layers were selected from 450 individually caged hens at 25-30 weeks of age for either low feed conversion ratio FCR < 1.8 ± 0.02 (high feed efficiency (HFE))) or high FCR >2.1 ± 0.02 (low feed efficiency (LFE)). For each of these 70 hens, intake of an ad-libitum mash diet at 2-minute time intervals, 24 h a day, for 7 days was determined alongside behavioural assessment and estimation of the selection of components of thethis mash. The group selected for HFE had a lower feed intake, similar egg mass and associated lower FCR when compared with the LFE group. Whilst feed intake patterns were similar between HFE and LFE hens, there was a distinct intake pattern for all layer hens with intake rate increasing from 0300 to 1700 h with a sharp decline to 22002100 h. High feed efficiencyFE hens selected a diet with 25% more ash and 4% less gross energy than LFE hens. The LFE hens also spent more time eating with more walking events, but less time spent resting, drinking, preening and cage pecking events as compared with HFE hens. In summary, there was no contrasting diurnal pattern of feed consumption behaviour between the groups ranked on feed efficiency, howeverIn summary, high feed efficiency hens consumed less feed and selected a diet with greater ash content and lower gross energy as compared with LFE hens. Our work is now focused on individual hen diet selection from mash diets with an aim of formulating precision, targeted diets for greater feed efficiency.
Data from: Contrasting evolutionary histories of MHC class I and class II loci in grouse - effects of selection and gene conversion
Genes of the major histocompatibility complex (MHC) encode receptor molecules that are responsible for recognition of intra- and extra-cellular pathogens (class I and class II genes, respectively) in vertebrates. Given the different roles of class I and II MHC genes, one might expect the strength of selection to differ between these two classes. Different selective pressures may also promote different rates of gene conversion at each class. Despite these predictions, surprisingly few studies have looked at differences between class I and II genes in terms of both selection and gene conversion. Here, we investigated the molecular evolution of MHC class I and II genes in five closely related species of prairie grouse (Centrocercus and Tympanuchus) that possess one class I and two class II loci. We found striking differences in the strength of balancing selection acting on MHC class I versus class II genes. More than half of the putative antigen-binding sites (ABS) of class II were under positive or episodic diversifying selection, compared with only 10% at class I. We also found that gene conversion played a stronger role in shaping the evolution of MHC class II than class I. Overall, the combination of strong positive (balancing) selection and frequent gene conversion has maintained higher diversity of MHC class II than class I in prairie grouse. This is one of the first studies clearly demonstrating that macroevolutionary mechanisms can act differently on genes involved in the immune response against intra- and extra-cellular pathogens.
Evaluating the Acceptability, Feasibility and Usability of Various Conversational Data Collection Software
ClinicalTrials.gov study NCT07336537. IPD Sharing: YES. Countries: 1. Publications: 0.
Prognosis prediction model for Alzheimer’s disease conversion from mild cognitive impairment by integrative analysis of multi-omics data
GEO Series GSE150693. Homo sapiens. 197 samples. Type: Non-coding RNA profiling by array.
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.