Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
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Title
Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
Authors
Keywords
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Journal
NATURE BIOTECHNOLOGY
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-01-03
DOI
10.1038/s41587-022-01520-x
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Note: Only part of the references are listed.- A Python library for probabilistic analysis of single-cell omics data
- (2022) Adam Gayoso et al. NATURE BIOTECHNOLOGY
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- (2022) Cristina Leal Rodríguez et al. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY
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- (2022) April R. Kriebel et al. Nature Communications
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- (2022) Rosa Lundbye Allesøe et al. Science Advances
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- (2021) Jakob Nybo Nissen et al. NATURE BIOTECHNOLOGY
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- (2021) Burak Yelmen et al. PLoS Genetics
- Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions
- (2021) Grace Hui Ting Yeo et al. Nature Communications
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- (2021) Sofia K. Forslund et al. NATURE
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- (2021) Jonathan Frazer et al. NATURE
- Role of Phagocytosis in the Pro-Inflammatory Response in LDL-Induced Foam Cell Formation; a Transcriptome Analysis
- (2020) Alexander N. Orekhov et al. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
- SciPy 1.0: fundamental algorithms for scientific computing in Python
- (2020) Pauli Virtanen et al. NATURE METHODS
- Impact of commonly used drugs on the composition and metabolic function of the gut microbiota
- (2020) Arnau Vich Vila et al. Nature Communications
- Statin therapy is associated with lower prevalence of gut microbiota dysbiosis
- (2020) Sara Vieira-Silva et al. NATURE
- Integrated Multi-Omics Analyses in Oncology: A Review of Machine Learning Methods and Tools
- (2020) Giovanna Nicora et al. Frontiers in Oncology
- Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study
- (2020) Valborg Gudmundsdottir et al. Genome Medicine
- DIABLO: an integrative approach for identifying key molecular drivers from multi-omic assays
- (2019) Amrit Singh et al. BIOINFORMATICS
- Unsupervised classification of multi-omics data during cardiac remodeling using deep learning
- (2019) Neo Christopher Chung et al. METHODS
- Metformin-induced changes of the gut microbiota in healthy young men: results of a non-blinded, one-armed intervention study
- (2019) Thomas Bryrup et al. DIABETOLOGIA
- Longitudinal multi-omics of host–microbe dynamics in prediabetes
- (2019) Wenyu Zhou et al. NATURE
- WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs
- (2019) Yuxing Liao et al. NUCLEIC ACIDS RESEARCH
- Hepatic transcriptomic signatures of statin treatment are associated with impaired glucose homeostasis in severely obese patients
- (2019) Daniel Margerie et al. BMC Medical Genomics
- Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium
- (2019) Robert W. Koivula et al. DIABETOLOGIA
- Mapping human microbiome drug metabolism by gut bacteria and their genes
- (2019) Michael Zimmermann et al. NATURE
- Glycine Metabolism and Its Alterations in Obesity and Metabolic Diseases
- (2019) Anaïs Alves et al. Nutrients
- Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals
- (2019) Monta Ustinova et al. PLoS One
- MetaboAnalystR: an R package for flexible and reproducible analysis of metabolomics data
- (2018) Jasmine Chong et al. BIOINFORMATICS
- Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
- (2018) Ricard Argelaguet et al. Molecular Systems Biology
- Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
- (2018) Jiarui Ding et al. Nature Communications
- Metformin Alters Gut Microbiota of Healthy Mice: Implication for Its Potential Role in Gut Microbiota Homeostasis
- (2018) Wei Ma et al. Frontiers in Microbiology
- Analysis of Time-Series Gene Expression Data to Explore Mechanisms of Chemical-Induced Hepatic Steatosis Toxicity
- (2018) Alejandro Aguayo-Orozco et al. Frontiers in Genetics
- Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps
- (2018) Anubha Mahajan et al. NATURE GENETICS
- Deep generative modeling for single-cell transcriptomics
- (2018) Romain Lopez et al. NATURE METHODS
- Deep Learning-Based Multi-Omics Data Integration Reveals Two Prognostic Subtypes in High-Risk Neuroblastoma
- (2018) Li Zhang et al. Frontiers in Genetics
- Metformin Suppressed CXCL8 Expression and Cell Migration in HEK293/TLR4 Cell Line
- (2017) Zhihui Xiao et al. MEDIATORS OF INFLAMMATION
- Atorvastatin increases Fads1, Fads2 and Elovl5 gene expression via the geranylgeranyl pyrophosphate-dependent Rho kinase pathway in 3T3-L1 cells
- (2017) Noriko Ishihara et al. Molecular Medicine Reports
- mixOmics: An R package for ‘omics feature selection and multiple data integration
- (2017) Florian Rohart et al. PLoS Computational Biology
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- (2016) Jessica Xin Hu et al. NATURE REVIEWS GENETICS
- Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota
- (2015) Kristoffer Forslund et al. NATURE
- Metformin inhibits cell cycle progression of B-cell chronic lymphocytic leukemia cells
- (2015) Silvia Bruno et al. Oncotarget
- High-Dose Simvastatin Exhibits Enhanced Lipid-Lowering Effects Relative to Simvastatin/Ezetimibe Combination Therapy
- (2014) S. G. Snowden et al. Circulation-Cardiovascular Genetics
- Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium
- (2014) Robert W. Koivula et al. DIABETOLOGIA
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- (2014) H Bjørn Nielsen et al. NATURE BIOTECHNOLOGY
- Statins and T2DM—an IGF link?
- (2013) Joana Osório Nature Reviews Endocrinology
- Quantifying the Effect of Metformin Treatment and Dose on Glycemic Control
- (2012) J. A. Hirst et al. DIABETES CARE
- The n-of-1 clinical trial: the ultimate strategy for individualizing medicine?
- (2011) Elizabeth O Lillie et al. Personalized Medicine
- Observational Studies: Cohort and Case-Control Studies
- (2010) Jae W. Song et al. PLASTIC AND RECONSTRUCTIVE SURGERY
- Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis
- (2009) Ronglai Shen et al. BIOINFORMATICS
- Effect of statins on HDL-C: a complex process unrelated to changes in LDL-C: analysis of the VOYAGER Database
- (2009) Philip J. Barter et al. JOURNAL OF LIPID RESEARCH
- The gastric HK-ATPase: structure, function, and inhibition
- (2008) Jai Moo Shin et al. PFLUGERS ARCHIV-EUROPEAN JOURNAL OF PHYSIOLOGY
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