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1,274 results for “Disease Model”
Integrated stress response inhibition prolongs the lifespan of a Pelizaeus-Merzbacher disease mouse model by increasing oligodendrocyte survival.
GEO Series GSE277705. Mus musculus. 57 samples. Type: Expression profiling by high throughput sequencing.
RNA-Sequencing from ventral mid brain and striatum of paraquat, pyridaben and paraquat+maneb mice models of Parkinson's disease.
GEO Series GSE36232. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Connexin 30 deficiency ameliorates the disease progression of amyotrophic lateral sclerosis model mice by suppressing glial inflammation.
GEO Series GSE213844. Mus musculus. 3 samples. Type: Expression profiling by array.
Integrated Gut/Liver-on-a-Chip platform as in vitro human model of non-alcoholic fatty liver disease
GEO Series GSE152091. Homo sapiens. 23 samples. Type: Expression profiling by high throughput sequencing.
Blood-brain barrier dysfunction in response to Alzheimer's disease mutations and aged serum in a tissue-engineered microvascular model
GEO Series GSE272179. Homo sapiens. 54 samples. Type: Expression profiling by high throughput sequencing.
Use of mice defective in interferon signaling to distinguish between primary and secondary pathological pathways in a mouse model of neuronal forms of Gaucher disease
GEO Series GSE150266. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
Rat models for Portosinusoidal Vascular Disease
GEO Series GSE229380. Rattus norvegicus. 23 samples. Type: Expression profiling by high throughput sequencing.
Gene expression response in mouse model of inflammatory bowel disease to ionizing radiation
GEO Series GSE114142. Mus musculus. 20 samples. Type: Expression profiling by array.
Data from: Big data analysis of genes associated with neuropsychiatric disorders in an Alzheimer's disease animal model
Alzheimer's disease is a neurodegenerative disease characterized by the impairment of cognitive function and loss of memory, affecting millions of individuals worldwide. With the dramatic increase in the prevalence of Alzheimer's disease, it is expected to impose extensive public health and economic burden. However, this burden is particularly heavy on the caregivers of Alzheimer's disease patients eliciting neuropsychiatric symptoms that include mood swings, hallucinations, and depression. Interestingly, these neuropsychiatric symptoms are shared across symptoms of bipolar disorder, schizophrenia, and major depression disorder. Despite the similarities in symptomatology, comorbidities of Alzheimer's disease and these neuropsychiatric disorders have not been studied in the Alzheimer's disease model. Here, we explore the comprehensive changes in gene expression of genes that are associated with bipolar disorder, schizophrenia, and major depression disorder through the microarray of an Alzheimer's disease animal model, the forebrain specific PSEN double knockout mouse. To analyze the genes related with these three neuropsychiatric disorders within the scope of our microarray data, we used selected 1207 of a total of 45,037 genes that satisfied our selection criteria. These genes were selected on the basis of 14 Gene Ontology terms significantly relevant with the three disorders which were identified by previous research conducted by the Psychiatric Genomics Consortium. Our study revealed that the forebrain specific deletion of Alzheimer's disease genes can significantly alter neuropsychiatric disorder associated genes. Most importantly, most of these significantly altered genes were found to be involved with schizophrenia. Taken together, we suggest that the synaptic dysfunction by mutation of Alzheimer's disease genes can lead to the manifestation of not only memory loss and impairments in cognition, but also neuropsychiatric symptoms.
Data from: A methylation-to-expression feature model for generating accurate prognostic risk scores and identifying disease targets in clear cell kidney cancer
Many researchers now have available multiple high-dimensional molecular and clinical datasets when studying a disease. As we enter this multi-omic era of data analysis, new approaches that combine different levels of data (e.g. at the genomic and epigenomic levels) are required to fully capitalize on this opportunity. In this work, we outline a new approach to multi-omic data integration, which combines molecular and clinical predictors as part of a single analysis to create a prognostic risk score for clear cell renal cell carcinoma. The approach integrates data in multiple ways and yet creates models that are relatively straightforward to interpret and with a high level of performance. Furthermore, the proposed process of data integration itself captures relationships in the data that represent highly disease-relevant functions.
Figure 4 from: Tachkov K, Mitov K, Savova A (2019) Predicting the outcomes and costs for a cohort of 426 patients with Chronic Obstructive Pulmonary Disease (COPD) in Bulgaria through a Markov model. Pharmacia 66(2): 53-57. https://doi.org/10.3897/pharmacia.66.e35162
Figure 4 Tornado diagram for LYS
Figure 2 from: Tachkov K, Mitov K, Savova A (2019) Predicting the outcomes and costs for a cohort of 426 patients with Chronic Obstructive Pulmonary Disease (COPD) in Bulgaria through a Markov model. Pharmacia 66(2): 53-57. https://doi.org/10.3897/pharmacia.66.e35162
Figure 2 CEAC of all data points
Figure 1 from: Tachkov K, Mitov K, Savova A (2019) Predicting the outcomes and costs for a cohort of 426 patients with Chronic Obstructive Pulmonary Disease (COPD) in Bulgaria through a Markov model. Pharmacia 66(2): 53-57. https://doi.org/10.3897/pharmacia.66.e35162
Figure 1 ICER points and dispersion cloud of Monte-Carlo simulation
Figure 3 from: Tachkov K, Mitov K, Savova A (2019) Predicting the outcomes and costs for a cohort of 426 patients with Chronic Obstructive Pulmonary Disease (COPD) in Bulgaria through a Markov model. Pharmacia 66(2): 53-57. https://doi.org/10.3897/pharmacia.66.e35162
Figure 3 Tornado diagram for QALYs
Bulk RNA-seq count matrices from manuscript: "Therapeutic efficacy of intracerebral hematopoietic stem cell gene therapy in an Alzheimer's disease mouse model"
<p>Gene expression profile of microglia-like cells in the central nervous system (CNS) after transplantation of hematopoietic stem/progenitor cells (HSPC). </p> <p>Different cell subsets and delivery routes are tested to induce a robust and exclusive engraftment of HSPCs and their progeny in the CNS of mice transplant recipients.</p>
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk (sequence model release)
<p>(This is the updated version that has been converted a standard pytorch model format)</p> <p>This is the deep learning sequence model used in </p> <p>Jian Zhou, Chandra L. Theesfeld, Kevin Yao, Kathleen M. Chen, Aaron K. Wong, and Olga G. Troyanskaya, Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk, Nature Genetics, 2018.</p> <p>Note the full software is available from https://github.com/FunctionLab/ExPecto and this release is created for the convenience of use and under the same non-commercial license. The model weights can be loaded with pytorch load_state_dict function (for an example please find <a href="https://github.com/FunctionLab/ExPecto/blob/master/chromatin.py">https://github.com/FunctionLab/ExPecto/blob/master/chromatin.py</a>). We also provide a web server for browsing mutations with strong predicted effects at https://hb.flatironinstitute.org/expecto/, which are currently limited to mutations within 1kb to TSS or are 1000 Genomes variants.</p> <p>Trivia: we code-named our models with whale names. This model has an unofficial codename DeepSEA "Beluga".</p>
Data from: Discovery of potential urine-accessible metabolite biomarkers associated with muscle disease and corticosteroid response in the mdx mouse model for Duchenne
Urine is increasingly being considered as a source of biomarker development in Duchenne Muscular Dystrophy (DMD), a severe, life-limiting disorder that affects approximately 1 in 4500 boys. In this study, we considered the mdx mice—a murine model of DMD—to discover biomarkers of disease, as well as pharmacodynamic biomarkers responsive to prednisolone, a corticosteroid commonly used to treat DMD. Longitudinal urine samples were analyzed from male age-matched mdx and wild-type mice randomized to prednisolone or vehicle control via liquid chromatography tandem mass spectrometry. A large number of metabolites (869 out of 6,334) were found to be significantly different between mdx and wild-type mice at baseline (Bonferroni-adjusted p-value < 0.05), thus being associated with disease status. These included a metabolite with m/z = 357 and creatine, which were also reported in a previous human study looking at serum. Novel observations in this study included peaks identified as biliverdin and hypusine. These four metabolites were significantly higher at baseline in the urine of mdx mice compared to wild-type, and significantly changed their levels over time after baseline. Creatine and biliverdin levels were also different between treated and control groups, but for creatine this may have been driven by an imbalance at baseline. In conclusion, our study reports a number of biomarkers, both known and novel, which may be related to either the mechanisms of muscle injury in DMD or prednisolone treatment.
Coumarin–Chalcone Hybrid LM-021 and Indole Derivative NC009-1 Targeting Inflammation and Oxidative Stress in Par-kinson's Disease Cell Models
<p>Figure S1: Wild type and A53T SNCA-GFP BE(2)-M17 cells; Figure S2: α-Synuclein aggregation and neurite outgrowth analyses on wild type and A53T SNCA-GFP BE(2)-M17 cells; Figure S3: Neuroprotective effects of LM-021 and NC009-1 on A53T-11 SNCA-GFP BE(2)-M17 cells; Figure S4: α-Synuclein aggregation reduction and neurite outgrowth promotion of LM-021 and NC009-1 on A53T-11 SNCA-GFP BE(2)-M17 cells.</p>
a Foundational Model for Cardiovascular Disease Diagnosis and Prediction
ClinicalTrials.gov study NCT06591923. IPD Sharing: NO. Countries: 1. Publications: 0.
Modelling in the Quantitative Analysis of Brain PET Scans in Patients With Alzheimer's Disease
ClinicalTrials.gov study NCT04718207. IPD Sharing: NO. Countries: 1. Publications: 0.
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.