Cargando…

GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization

BACKGROUND: Bioinformatics tools have been developed to interpret gene expression data at the gene set level, and these gene set based analyses improve the biologists’ capability to discover functional relevance of their experiment design. While elucidating gene set individually, inter-gene sets ass...

Descripción completa

Detalles Bibliográficos
Autores principales:	Chen, Hung-I Harry, Chiu, Yu-Chiao, Zhang, Tinghe, Zhang, Songyao, Huang, Yufei, Chen, Yidong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2018
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302374/ https://www.ncbi.nlm.nih.gov/pubmed/30577835 http://dx.doi.org/10.1186/s12918-018-0642-2

Ejemplares similares

Predicting drug response of tumors from integrated genomic profiles by deep neural networks
por: Chiu, Yu-Chiao, et al.
Publicado: (2019)

Correction to: Predicting drug response of tumors from integrated genomic profiles by deep neural networks
por: Chiu, Yu-Chiao, et al.
Publicado: (2019)

Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes
por: Khan, Wasif, et al.
Publicado: (2023)

Cross-modal semantic autoencoder with embedding consensus
por: Sun, Shengzi, et al.
Publicado: (2021)

Graph Autoencoder with Preserving Node Attribute Similarity
por: Lin, Mugang, et al.
Publicado: (2023)

A pan-cancer somatic mutation embedding using autoencoders
por: Palazzo, Martin, et al.
Publicado: (2019)

Exploring Factor Structures Using Variational Autoencoder in Personality Research
por: Huang, Yufei, et al.
Publicado: (2022)

Locally Embedding Autoencoders: A Semi-Supervised Manifold Learning Approach of Document Representation
por: Wei, Chao, et al.
Publicado: (2016)

Convolutional neural network models for cancer type prediction based on gene expression
por: Mostavi, Milad, et al.
Publicado: (2020)

CancerSiamese: one-shot learning for predicting primary and metastatic tumor types unseen during model training
por: Mostavi, Milad, et al.
Publicado: (2021)

A simple gene set-based method accurately predicts the synergy of drug pairs
por: Hsu, Yu-Ching, et al.
Publicado: (2016)

Deep Multivariate Time Series Embedding Clustering via Attentive-Gated Autoencoder
por: Ienco, Dino, et al.
Publicado: (2020)

Embedding of Molecular Structure Using Molecular Hypergraph Variational Autoencoder with Metric Learning
por: Koge, Daiki, et al.
Publicado: (2020)

RN-Autoencoder: Reduced Noise Autoencoder for classifying imbalanced cancer genomic data
por: Arafa, Ahmed, et al.
Publicado: (2023)

Gene Regulation, Modulation, and Their Applications in Gene Expression Data Analysis
por: Flores, Mario, et al.
Publicado: (2013)

Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder
por: Dwivedi, Sanjiv K., et al.
Publicado: (2020)

AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments
por: Yu, Tianwei
Publicado: (2022)

Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder
por: Peng, Jiajie, et al.
Publicado: (2019)

Detection of high variability in gene expression from single-cell RNA-seq profiling
por: Chen, Hung-I Harry, et al.
Publicado: (2016)

Shallow Sparsely-Connected Autoencoders for Gene Set Projection
por: Gold, Maxwell P., et al.
Publicado: (2019)

CeL-ID: cell line identification using RNA-seq data
por: Mohammad, Tabrez A., et al.
Publicado: (2019)

Predicting and characterizing a cancer dependency map of tumors with deep learning
por: Chiu, Yu-Chiao, et al.
Publicado: (2021)

Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means
por: Hadipour, Hamid, et al.
Publicado: (2022)

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer
por: Chiu, Yu-Chiao, et al.
Publicado: (2017)

Designing Bioinspired Composite Structures via Genetic Algorithm and Conditional Variational Autoencoder
por: Chiu, Yi-Hung, et al.
Publicado: (2023)

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database
por: Ma, Chifeng, et al.
Publicado: (2013)

Autoencoders reloaded
por: Bourlard, Hervé, et al.
Publicado: (2022)

Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization
por: Hagad, Juan Lorenzo, et al.
Publicado: (2021)

Malware detection framework based on graph variational autoencoder extracted embeddings from API-call graphs
por: Gunduz, Hakan
Publicado: (2022)

Characterization of the complete mitochondrial genome of blacktip shark Carcharhinus limbatus (Carcharhiniformes: Carcharhinidae)
por: Huang, Xiaolin, et al.
Publicado: (2022)

Developing an Embedding, Koopman and Autoencoder Technologies-Based Multi-Omics Time Series Predictive Model (EKATP) for Systems Biology research
por: Liu, Suran, et al.
Publicado: (2021)

Open Set Audio Classification Using Autoencoders Trained on Few Data
por: Naranjo-Alcazar, Javier, et al.
Publicado: (2020)

iCircDA-NEAE: Accelerated attribute network embedding and dynamic convolutional autoencoder for circRNA-disease associations prediction
por: Yuan, Lin, et al.
Publicado: (2023)

Identifying critical nodes in temporal networks by network embedding
por: Yu, En-Yu, et al.
Publicado: (2020)

Parameter optimization for constructing competing endogenous RNA regulatory network in glioblastoma multiforme and other cancers
por: Chiu, Yu-Chiao, et al.
Publicado: (2015)

Curiosity-Driven Variational Autoencoder for Deep Q Network
por: Han, Gao-Jie, et al.
Publicado: (2020)

Graph embedding and Gaussian mixture variational autoencoder network for end-to-end analysis of single-cell RNA sequencing data
por: Xu, Junlin, et al.
Publicado: (2023)

Identification of genomic functional hotspots with copy number alteration in liver cancer
por: Hsiao, Tzu-Hung, et al.
Publicado: (2013)

An Active Learning Method Based on Variational Autoencoder and DBSCAN Clustering
por: Chen, Fang, et al.
Publicado: (2021)

RDAClone: Deciphering Tumor Heterozygosity through Single-Cell Genomics Data Analysis with Robust Deep Autoencoder
por: Xia, Jie, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_njpb7cfa20mjqi874djricpk7a