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ShareScore release 0.9.0
Dataset results
18 results for “Integrative Genome Modeling”
Data from: Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
<p>Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ash (<em>Fraxinus pennsylvanica</em>) using 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross-validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic-genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially-explicit model. Approximate Bayesian Computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross-validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data.</p>
Data from: Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
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DeepAnnotation: A novel interpretable deep learning-based genomic selection model that integrates comprehensive functional annotations
<p>1. Update package, example dataset, and demo code of DeepAnnotation</p> <p>2. Update the transformed genotype data, the phenotype data, the comprehensive functional annotation data for Duroc prepared by RNAfold, DeepSEA, easyMF models, and the four types of input data for training DeepAnnotation model</p> <p>3. Add the conserved functional annotation</p> <p> </p>
Integration of whole genome sequencing analysis with unique patient-derived models reveals clinically relevant drug targets in TFCP2 fusion-defined intraosseous rhabdomyosarcoma
GEO Series GSE287694. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
Integrative model of genomic factors for determining binding site selection by estrogen receptor alpha in MCF-7 cancer cells
GEO Series GSE23701. Homo sapiens. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Integrative model of genomic factors for determining binding site selection by estrogen receptor alpha in MCF-7 cancer cells
GEO Series GSE26831. Homo sapiens. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Integrative genomic analysis of gemcitabine resistance in pancreatic cancer by patient-derived xenograft models
GEO Series GSE165764. Homo sapiens. 56 samples. Type: Methylation profiling by genome tiling array.
Integrating Extracellular Flux Measurements and Genome-Scale Modeling Reveals Novel Differences between Brown and White Adipocytes
GEO Series GSE100003. Homo sapiens. 6 samples. Type: Expression profiling by array.
Integrative Analysis of Tamoxifen-resistant Cell Line Models Based on Sequencing Genomes, Transcriptomes and Epigenomes
GEO Series GSE55383. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing; Methylation profiling by high throughput sequencing; Genome variation profiling by array.
Integrative genomic strategies applied to a lymphoblast cell line model reveal specific transcriptomic signatures associated with clozapine response [expression]
GEO Series GSE158819. Homo sapiens. 28 samples. Type: Expression profiling by array.
Full-length dystrophin restoration via targeted genomic integration by AAV-CRISPR in a humanized mouse model of Duchenne muscular dystrophy
GEO Series GSE173224. Mus musculus. 186 samples. Type: Other.
Integrative Analysis of Tamoxifen-resistant Cell Line Models Based on Sequencing Genomes, Transcriptomes and Epigenomes [seq]
GEO Series GSE55343. Homo sapiens. 26 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing; Methylation profiling by high throughput sequencing.
Integrating multi-omics data with genome scale metabolic modeling for the analysis of Pseudomonas aeruginosa persister cells
GEO Series GSE185914. Pseudomonas aeruginosa. 45 samples. Type: Expression profiling by high throughput sequencing.
Genome models integrating chromatin contacts and nuclear lamin-genome interactions reveal implications of laminopathy-causing lamin mutations on genome architecture
GEO Series GSE81671. Homo sapiens. 25 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Integrative Analysis of Tamoxifen-resistant Cell Line Models Based on Sequencing Genomes, Transcriptomes and Epigenomes [aCGH]
GEO Series GSE55380. Homo sapiens. 4 samples. Type: Genome variation profiling by array.
Integrative genomic strategies applied to a lymphoblast cell line model reveal specific transcriptomic signatures associated with clozapine response [methylation]
GEO Series GSE158716. Homo sapiens. 92 samples. Type: Methylation profiling by array.
Integrated Genomic Analysis of a Stem Cell Model of Overgrowth Syndrome with Intellectual Disability (WGBS)
GEO Series GSE116420. Mus musculus. 13 samples. Type: Methylation profiling by high throughput sequencing.
Integrative genomic strategies applied to a lymphoblast cell line model reveal specific transcriptomic signatures associated with clozapine response
GEO Series GSE158821. Homo sapiens. 120 samples. Type: Expression profiling by array; Methylation 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.