Pages that link to "Q31141362"
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The following pages link to ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions (Q31141362):
Displaying 29 items.
- Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data (Q27976639) (← links)
- A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastoma (Q30274830) (← links)
- Sequence-specific bias correction for RNA-seq data using recurrent neural networks (Q31162024) (← links)
- Biofilms 2015: Multidisciplinary Approaches Shed Light into Microbial Life on Surfaces (Q37248269) (← links)
- Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks. (Q38677652) (← links)
- Using neural networks for reducing the dimensions of single-cell RNA-Seq data (Q42777960) (← links)
- A deep ensemble model to predict miRNA-disease association (Q45334190) (← links)
- Assigning chemoreceptors to chemosensory pathways in Pseudomonas aeruginosa. (Q46761709) (← links)
- Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders (Q47132893) (← links)
- ADAGE signature analysis: differential expression analysis with data-defined gene sets (Q47142467) (← links)
- Deep Learning based multi-omics integration robustly predicts survival in liver cancer. (Q47855807) (← links)
- Learning the Structural Vocabulary of a Network (Q50466142) (← links)
- Opportunities and obstacles for deep learning in biology and medicine. (Q52331906) (← links)
- PathCORE-T: identifying and visualizing globally co-occurring pathways in large transcriptomic compendia. (Q55467557) (← links)
- A primer on investigating the role of the microbiome in brain and cognitive development (Q57459082) (← links)
- Data-driven human transcriptomic modules determined by independent component analysis (Q58732991) (← links)
- Integrative pathway-based survival prediction utilizing the interaction between gene expression and DNA methylation in breast cancer (Q58739264) (← links)
- GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization (Q60937686) (← links)
- Single-cell RNA-seq denoising using a deep count autoencoder (Q61124666) (← links)
- Applications of machine learning in drug discovery and development. (Q63979755) (← links)
- MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease (Q64039237) (← links)
- A primer on deep learning in genomics (Q64120751) (← links)
- Cell Identity Codes: Understanding Cell Identity from Gene Expression Profiles using Deep Neural Networks (Q64263662) (← links)
- Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder (Q89686128) (← links)
- DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types (Q89863675) (← links)
- Exploring single-cell data with deep multitasking neural networks (Q90576457) (← links)
- Ethanol Stimulates Trehalose Production through a SpoT-DksA-AlgU-Dependent Pathway in Pseudomonas aeruginosa (Q92766631) (← links)
- Unsupervised generative and graph representation learning for modelling cell differentiation (Q96576811) (← links)
- Deep learning models in genomics; are we there yet? (Q97421918) (← links)