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multi omics data  (Omics Data Automation)

 
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    Omics Data Automation multi omics data
    Multi Omics Data, supplied by Omics Data Automation, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/multi+omics+data+set/data+multi+omics/pmc12530062-86-34-62
    Average 86 stars, based on 1 article reviews
    multi omics data - by Bioz Stars, 2026-11
    86/100 stars

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    Related Articles

    Biomarker Discovery:

    Article Title: Utilizing Machine Learning to Predict Lung Cancer Severity: Integrating Patient Insights for Improved Clinical Outcomes
    Article Snippet: .. Importance of Multi-Omics Data The significant improvement in model performance through the integration of multi-omics data highlights the necessity of a holistic approach to data collection. ..

    Article Title: Utilizing Machine Learning to Predict Lung Cancer Severity: Integrating Patient Insights for Improved Clinical Outcomes
    Article Snippet: .. Integration of Multi-Omics Data The impact of integrating multi-omics data on predictive performance will be analyzed by comparing models trained on single-omics data versus those using multi-omics inputs. ..

    Article Title: MultiSP deciphers tissue structure and multicellular communication from spatial multi-omics data.
    Article Snippet: .. Highlights • MultiSP deciphers complex tissue structures from spatial multi-omics data • Flexible integration of any number of omics modalities • MultiSP restores noisy and sparse spatial omics data • Inference of spatially multimodal cell-cell communication Authors Chenfeng Mo, Xiufen Zou, Suoqin Jin Correspondence sqjin@whu.edu.cn In brief Mo et al. present MultiSP, an efficient deep learning framework for integrative analysis of spatial multi-omics data. ..

    Article Title: EMixed: Probabilistic Multi-Omics Cellular Deconvolution of Bulk Omics Data
    Article Snippet: .. Multi-omics data have several characteristics that make them useful for this purpose: 1) the multi-omics data from a tissue sample share the same true cell composition; 2) the estimated cell type fractions across observed multi-omics data from the same tissue region of an individual are similar, while affected by sampling and technical variability across omics data; 3) strong markers are shared across omics data ( ). ..

    Article Title: Generative deep learning in bioinformatics: a microservices-driven paradigm for big data environment
    Article Snippet: .. – TCGA (Omics Data): Multi-omics data (gene expression, mutation calls, and copy number variation) were preprocessed separately. ..

    Article Title: Enhancing Cancer Treatment: Integrating Pharmacometrics and Personalized Medicine in Oncology
    Article Snippet: .. These challenges span scientific, technological, ethical, and clinical domains, requiring strategic solutions to optimize their impact in cancer treatment. a) Complexity of Multi-Omics Data Integration • Cancer is highly heterogeneous, making it difficult to integrate multi-omics data, including genomic, proteomic, metabolomic, and transcriptomic information, into predictive models (Malone et al., 2020). ..

    Article Title: Design of an integrated model using U-Net, DeepSurv, and cross-attention for lung cancer classification and survival prediction
    Article Snippet: .. , Deep Learning with Multi-Omics Data , Multi-omics data improves lung cancer classification , High accuracy for subtype prediction , Limited data availability for rare subtypes. .. , Fully Automated Screening System , End-to-end automation of lung cancer screening , High accuracy with automated segmentation , Generalization issues for unseen imaging modalities.

    Article Title: Subtypes estimation in single-cell multi-omics data via S-multi-SNE.
    Article Snippet: .. We further explored whether multi-omics data can improve the visualisations obtained from single-omics data. ..

    Sampling:

    Article Title: EMixed: Probabilistic Multi-Omics Cellular Deconvolution of Bulk Omics Data
    Article Snippet: .. Multi-omics data have several characteristics that make them useful for this purpose: 1) the multi-omics data from a tissue sample share the same true cell composition; 2) the estimated cell type fractions across observed multi-omics data from the same tissue region of an individual are similar, while affected by sampling and technical variability across omics data; 3) strong markers are shared across omics data ( ). ..

    Gene Expression:

    Article Title: Generative deep learning in bioinformatics: a microservices-driven paradigm for big data environment
    Article Snippet: .. – TCGA (Omics Data): Multi-omics data (gene expression, mutation calls, and copy number variation) were preprocessed separately. ..

    Mutagenesis:

    Article Title: Generative deep learning in bioinformatics: a microservices-driven paradigm for big data environment
    Article Snippet: .. – TCGA (Omics Data): Multi-omics data (gene expression, mutation calls, and copy number variation) were preprocessed separately. ..



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    multi omics data set  (Omics Data Automation)
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    Omics Data Automation multi omics data set
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    Omics Data Automation multi-omics data sets
    Comprehensive overview of alterations in energy metabolism and lipid-handling pathways in patients with hypertrophic cardiomyopathy (HCM) vs nonfailing (NF) donors integrating metabolomics, <t>lipidomics,</t> and proteomics data. Metabolomic, lipidomic, and proteomic data were integrated to provide an overview of changes in major energy metabolism and lipid-handling pathways. Metabolites and lipids are indicated by objects with a dark fill and white text; proteins are indicated by objects with a light fill and black text. Blue, orange, and gray indicate lower, higher, and unchanged abundances in HCM vs NF donors, respectively. Created with BioRender.com .
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    quality data data set multi omics data sets data set correlation statistics references 53 63  (Omics Data Automation)
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    Omics Data Automation quality data data set multi omics data sets data set correlation statistics references 53 63
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    combined ad-metabolic multi-omics data set  (Omics Data Automation)
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    multi-omics data set  (Omics Data Automation)
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    Image Search Results


    Comprehensive overview of alterations in energy metabolism and lipid-handling pathways in patients with hypertrophic cardiomyopathy (HCM) vs nonfailing (NF) donors integrating metabolomics, lipidomics, and proteomics data. Metabolomic, lipidomic, and proteomic data were integrated to provide an overview of changes in major energy metabolism and lipid-handling pathways. Metabolites and lipids are indicated by objects with a dark fill and white text; proteins are indicated by objects with a light fill and black text. Blue, orange, and gray indicate lower, higher, and unchanged abundances in HCM vs NF donors, respectively. Created with BioRender.com .

    Journal: Circulation. Genomic and Precision Medicine

    Article Title: Integrating Clinical Phenotype With Multiomics Analyses of Human Cardiac Tissue Unveils Divergent Metabolic Remodeling in Genotype-Positive and Genotype-Negative Patients With Hypertrophic Cardiomyopathy

    doi: 10.1161/CIRCGEN.123.004369

    Figure Lengend Snippet: Comprehensive overview of alterations in energy metabolism and lipid-handling pathways in patients with hypertrophic cardiomyopathy (HCM) vs nonfailing (NF) donors integrating metabolomics, lipidomics, and proteomics data. Metabolomic, lipidomic, and proteomic data were integrated to provide an overview of changes in major energy metabolism and lipid-handling pathways. Metabolites and lipids are indicated by objects with a dark fill and white text; proteins are indicated by objects with a light fill and black text. Blue, orange, and gray indicate lower, higher, and unchanged abundances in HCM vs NF donors, respectively. Created with BioRender.com .

    Article Snippet: Processed metabolomics, lipidomics, and proteomics data are furthermore available as a Supplemental Material ( Multi-Omics Data Sets ).

    Techniques:

    Limited agreement among studies into metabolomic and lipidomic changes in tissue of patients with hypertrophic cardiomyopathy (HCM) compared with nonfailing (NF) donor tissue. A , Pie chart visualizing agreement in metabolite findings in HCM vs NF donor cardiac tissue samples; 114 metabolites were detected in at least 2 studies. Of these metabolites, 92 displayed inconsistent outcomes in HCM vs NF donor tissue. B , Table displaying consistency in lipidomic findings in HCM vs NF donor tissue. Blue and orange indicate consistently lowered and elevated levels, respectively, in HCM vs NF donors. *Derived from both metabolomics and lipidomics.

    Journal: Circulation. Genomic and Precision Medicine

    Article Title: Integrating Clinical Phenotype With Multiomics Analyses of Human Cardiac Tissue Unveils Divergent Metabolic Remodeling in Genotype-Positive and Genotype-Negative Patients With Hypertrophic Cardiomyopathy

    doi: 10.1161/CIRCGEN.123.004369

    Figure Lengend Snippet: Limited agreement among studies into metabolomic and lipidomic changes in tissue of patients with hypertrophic cardiomyopathy (HCM) compared with nonfailing (NF) donor tissue. A , Pie chart visualizing agreement in metabolite findings in HCM vs NF donor cardiac tissue samples; 114 metabolites were detected in at least 2 studies. Of these metabolites, 92 displayed inconsistent outcomes in HCM vs NF donor tissue. B , Table displaying consistency in lipidomic findings in HCM vs NF donor tissue. Blue and orange indicate consistently lowered and elevated levels, respectively, in HCM vs NF donors. *Derived from both metabolomics and lipidomics.

    Article Snippet: Processed metabolomics, lipidomics, and proteomics data are furthermore available as a Supplemental Material ( Multi-Omics Data Sets ).

    Techniques: Derivative Assay

    Seventeen predicted lipid species in the AD multi‐omics data sets with a VIP score >1 in the ABCA7‐KO cortical lipidome

    Journal: Journal of Neurochemistry

    Article Title: Pathway‐based integration of multi‐omics data reveals lipidomics alterations validated in an Alzheimer's disease mouse model and risk loci carriers

    doi: 10.1111/jnc.15719

    Figure Lengend Snippet: Seventeen predicted lipid species in the AD multi‐omics data sets with a VIP score >1 in the ABCA7‐KO cortical lipidome

    Article Snippet: Conditional cell‐type enrichment was performed on a combined AD‐metabolic multi‐omics data set to investigate enrichment relationships.

    Techniques: Biomarker Discovery