Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
91
datasets available to search
ShareScore release 0.9.0
Dataset results
91 results for “compound screen”
A phenotypic screening platform utilising human spermatozoa identifies compounds with contraceptive activity
Open the record for dataset details and reuse information.
Screening of 6000 compounds for uncoupling activity: input parameters, the predicted uncoupling activity, as well as the results in respect to structural alerts
Open the record for dataset details and reuse information.
Screening the Sigma LOPAC®1280 library of compounds for protective effects against cisplatin-induced oto- and nephrotoxicity
Open the record for dataset details and reuse information.
Data from: High-throughput screening of inorganic compounds for dielectric and optical properties to enable the discovery of novel materials
Dielectrics are an important class of materials that are ubiquitous in modern electronic applications. Even though their properties are important for the performance of devices, the number of compounds with known dielectric constant is on the order of a few hundred. Here, we use Density Functional Perturbation Theory as a way to screen for the dielectric constant and refractive index of materials in a fast and computationally efficient way. Our results form the largest database to date, containing the full dielectric tensor for 1,056 compounds. Details regarding the computational methodology and technical validation are presented along with the format of our publicly available data. In addition, we integrate our dataset with the Materials Project allowing users easy access to material properties. Finally, we explain how our dataset and calculation methodology can be used in the search for novel dielectric compounds.
Unveiling CNS Cell Morphology with Deep Learning: A Gateway to Anti-Inflammatory Compound Screening
<p>Understanding the connection between cellular structure and observable traits is vital for comprehending cell behavior, especially in neuropathological conditions. Current limitations exist in applying advanced image analysis, like deep learning, to central nervous system cells due to challenges such as the need for extensive labeled data, difficulty in detecting subtle changes, and the presence of batch effects. The study focuses on overcoming these issues in the context of neuroinflammation, utilizing a deep learning approach to effectively analyze morphological changes in neuronal and microglial cells. This innovative method aids in studying neuroinflammation, facilitating the screening of potential therapeutic compounds and bridging gaps in neuropathological research and pharmaceutical development.</p>
In Silico Screening of Coffee Plant Natural Products as Lead Compounds for Stroke Remedy (Supplementary material)
<p>Data set for ICSE 2023 conference proceeding</p>
Fig. 1 in Screening of in vitro and in silico α-amylase, α-glucosidase, and lipase inhibitory activity of oxyprenylated natural compounds and semisynthetic derivatives
Fig. 1. Chemical structures of the 23 analysed pure natural and semisynthetic compounds.
Fig. 1 in Catecholic alkaloid sulfonates and aromatic nitro compounds from Portulaca oleracea and screening of their anti-inflammatory and anti-microbial activities
Fig. 1. Chemical structures of compounds 1–22 isolated from P. oleracea.
Fig. 3 in Catecholic alkaloid sulfonates and aromatic nitro compounds from Portulaca oleracea and screening of their anti-inflammatory and anti-microbial activities
Fig. 3. Crystal structure of compound 2 monohydrate.
Fig. 2 in Catecholic alkaloid sulfonates and aromatic nitro compounds from Portulaca oleracea and screening of their anti-inflammatory and anti-microbial activities
Fig. 2. Key HMBC (H→C) correlations of compounds 1, 3–6, 10, 16, and 17.
Data from: Forward chemical genetic screens in Arabidopsis identify genes that influence sensitivity to the phytotoxic compound sulfamethoxazole
Open the record for dataset details and reuse information.
Data from: High-throughput screening of inorganic compounds for dielectric and optical properties to enable the discovery of novel materials
Open the record for dataset details and reuse information.
High throughput phenotypic screen and transcriptional analysis identify new compounds, targets and pathways for macrophage reprogramming I
GEO Series GSE144989. Homo sapiens. 11 samples. Type: Expression profiling by high throughput sequencing.
High-Throughput Screening for Myelination Promoting Compounds Using Human Stem Cell-derived Oligodendrocyte Progenitor Cells Identifies Novel Targets
GEO Series GSE223599. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
Tumor immunological phenotype signature-based high-throughput screening for the discovery of combination immunotherapy compounds
GEO Series GSE160071. Homo sapiens; Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
Screening bioactive food compounds in honey bees suggests curcumin blocks alcohol-induced damage to longevity and DNA methylation
GEO Series GSE169362. Apis mellifera. 13 samples. Type: Methylation profiling by high throughput sequencing.
A multiplexed, single-cell sequencing screen identifies compounds that increase neurogenic reprogramming of mammalian Muller glia.
GEO Series GSE239731. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
A Dermis-on-a-Chip Model for Compound Screening
GEO Series GSE300701. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
A chemical screen identifies compounds limiting the toxicity of C9ORF72 dipeptide repeats [drug treatment]
GEO Series GSE116392. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Identification of selective inhibitors for diffuse-type gastric cancer cells by screening of annotated compounds in E-cadherin/p53 double conditional knockout mice
GEO Series GSE102297. Mus musculus. 8 samples. Type: Expression 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.