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.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “Mondo”
Rare Disease analysis in Mondo
<p>To answer the question of 'How many rare diseases are there?' we analyzed terms in Mondo to get a total count of Rare Diseases as defined in Mondo Disease Ontology (Mondo).</p> <p> </p> <p>Methods</p> <p>This analysis was performed on the <a href="http://purl.obolibrary.org/obo/mondo/releases/2019-09-30/mondo.json">Mondo 2019-09-30 release</a>.</p> <p><strong>1. Get all 'Disease' terms from Mondo</strong></p> <p>First we get all the terms in Mondo that are a descendants of <code>MONDO:0000001 'Disease'</code>.</p> <p>There are <code>21633</code> Mondo disease terms.</p> <p><strong>2. Filter terms that are descendants of 'disease susceptibility'</strong></p> <p>We then filter out terms that are descendants of <code>MONDO:0042489 'disease susceptibility'</code>, to avoid counting ambiguous terms that are related to disease susceptibility and not the actual disease itself.</p> <p>This gives us a list of <code>21563</code> Mondo rare disease terms.</p> <p><strong>3. Identify terms that are 'rare'</strong></p> <p>Any disease term in Mondo is considered rare if the term, or its ancestor, has modifier <code>MONDO:0021136 'Rare'</code> in the ontology.</p> <p>There are <code>12914</code> Mondo rare disease terms.</p> <p><strong>4. Consider terms in 'gard_rare' subset</strong></p> <p>There are <code>3176</code> Mondo disease terms that are in <code>gard_rare</code> subset which contains Mondo terms that are yet to be treated as 'rare'.</p> <p>We add these terms to our set of Mondo rare disease terms.</p> <p>This increases the Mondo rare disease term count to <code>13866</code>.</p> <p>But for this analysis, we are interested in terms that are both rare and are leaf nodes in the ontology.</p> <p>After considering only leaf nodes, we get <code>10394</code> as the final count of Mondo rare disease terms.</p> <p> </p> <p>Results</p> <p>all-mondo-disease-terms.tsv: As part of our analysis, we generated a TSV containing 21633 Mondo disease terms, each with annotations that signifies whether the term is a rare disease term and whether that term is a leaf node in the ontology.</p>
Altro Mondo
Impossible architecture inspirated by M.C. Escher. Source: Objaverse 1.0 / Sketchfab
Data from: The Caenorhabditis elegans Myc-Mondo/Mad complexes integrate diverse longevity signals
The Myc family of transcription factors regulates a variety of biological processes, including the cell cycle, growth, proliferation, metabolism, and apoptosis. In Caenorhabditis elegans, the "Myc interaction network" consists of two opposing heterodimeric complexes with antagonistic functions in transcriptional control: the Myc-Mondo:Mlx transcriptional activation complex and the Mad:Max transcriptional repression complex. In C. elegans, Mondo, Mlx, Mad, and Max are encoded by mml-1, mxl-2, mdl-1, and mxl-1, respectively. Here we show a similar antagonistic role for the C. elegans Myc-Mondo and Mad complexes in longevity control. Loss of mml-1 or mxl-2 shortens C. elegans lifespan. In contrast, loss of mdl-1 or mxl-1 increases longevity, dependent upon MML-1:MXL-2. The MML-1:MXL-2 and MDL-1:MXL-1 complexes function in both the insulin signaling and dietary restriction pathways. Furthermore, decreased insulin-like/IGF-1 signaling (ILS) or conditions of dietary restriction increase the accumulation of MML-1, consistent with the notion that the Myc family members function as sensors of metabolic status. Additionally, we find that Myc family members are regulated by distinct mechanisms, which would allow for integrated control of gene expression from diverse signals of metabolic status. We compared putative target genes based on ChIP-sequencing data in the modENCODE project and found significant overlap in genomic DNA binding between the major effectors of ILS (DAF-16/FoxO), DR (PHA-4/FoxA), and Myc family (MDL-1/Mad/Mxd) at common target genes, which suggests that diverse signals of metabolic status converge on overlapping transcriptional programs that influence aging. Consistent with this, there is over-enrichment at these common targets for genes that function in lifespan, stress response, and carbohydrate metabolism. Additionally, we find that Myc family members are also involved in stress response and the maintenance of protein homeostasis. Collectively, these findings indicate that Myc family members integrate diverse signals of metabolic status, to coordinate overlapping metabolic and cytoprotective transcriptional programs that determine the progression of aging.
Data from: The Caenorhabditis elegans Myc-Mondo/Mad complexes integrate diverse longevity signals
Open the record for dataset details and reuse information.
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.