Cargando…

Mining influential genes based on deep learning

BACKGROUND: Currently, large-scale gene expression profiling has been successfully applied to the discovery of functional connections among diseases, genetic perturbation, and drug action. To address the cost of an ever-expanding gene expression profile, a new, low-cost, high-throughput reduced repr...

Descripción completa

Detalles Bibliográficos
Autores principales:	Kong, Lingpeng, Chen, Yuanyuan, Xu, Fengjiao, Xu, Mingmin, Li, Zutan, Fang, Jingya, Zhang, Liangyun, Pian, Cong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2021
Materias:	Methodology Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821411/ https://www.ncbi.nlm.nih.gov/pubmed/33482718 http://dx.doi.org/10.1186/s12859-021-03972-5

Ejemplares similares

EpiMOGA: An Epistasis Detection Method Based on a Multi-Objective Genetic Algorithm
por: Chen, Yuanyuan, et al.
Publicado: (2021)

Revealing Prognosis-Related Pathways at the Individual Level by a Comprehensive Analysis of Different Cancer Transcription Data
por: Fang, Jingya, et al.
Publicado: (2020)

SPMLMI: predicting lncRNA–miRNA interactions in humans using a structural perturbation method
por: Xu, Mingmin, et al.
Publicado: (2021)

Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species
por: Li, Zutan, et al.
Publicado: (2021)

Identification and Functional Analysis of Individual-Specific Subpathways in Lung Adenocarcinoma
por: Fang, Jingya, et al.
Publicado: (2022)

NcPath: a novel platform for visualization and enrichment analysis of human non-coding RNA and KEGG signaling pathways
por: Li, Zutan, et al.
Publicado: (2022)

Identification of cancer-related miRNA-lncRNA biomarkers using a basic miRNA-lncRNA network
por: Zhang, Guangle, et al.
Publicado: (2018)

Motif mining based on network space compression
por: Zhang, Qiang, et al.
Publicado: (2014)

Impact of alternative approaches to assess outlying and influential observations on health care costs
por: Weichle, Thomas, et al.
Publicado: (2013)

Identifying RNA N6-Methyladenine Sites in Three Species Based on a Markov Model
por: Pian, Cong, et al.
Publicado: (2021)

Effects of influential points and sample size on the selection and replicability of multivariable fractional polynomial models
por: Sauerbrei, Willi, et al.
Publicado: (2023)

DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field
por: Jiang, Yu, et al.
Publicado: (2020)

Segmentation and counting of wheat spike grains based on deep learning and textural feature
por: Xu, Xin, et al.
Publicado: (2023)

DeepMF: deciphering the latent patterns in omics profiles with a deep learning method
por: Chen, Lingxi, et al.
Publicado: (2019)

HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes
por: Li, Yu, et al.
Publicado: (2021)

Template-based prediction of protein structure with deep learning
por: Zhang, Haicang, et al.
Publicado: (2020)

A New Method for Motif Mining in Biological Networks
por: Xu, Yuan, et al.
Publicado: (2014)

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data
por: Lee, Hyeonjeong, et al.
Publicado: (2017)

EpiMINE, a computational program for mining epigenomic data
por: Jammula, SriGanesh, et al.
Publicado: (2016)

Deep phenotyping: deep learning for temporal phenotype/genotype classification
por: Taghavi Namin, Sarah, et al.
Publicado: (2018)

Endoscopy-based IBD identification by a quantized deep learning pipeline
por: Datres, Massimiliano, et al.
Publicado: (2023)

Aligning text mining and machine learning algorithms with best practices for study selection in systematic literature reviews
por: Popoff, E., et al.
Publicado: (2020)

Multiple comparisons permutation test for image based data mining in radiotherapy
por: Chen, Chun, et al.
Publicado: (2013)

Fast rule-based bioactivity prediction using associative classification mining
por: Yu, Pulan, et al.
Publicado: (2012)

MiningABs: mining associated biomarkers across multi-connected gene expression datasets
por: Cheng, Chun-Pei, et al.
Publicado: (2014)

LncRNApred: Classification of Long Non-Coding RNAs and Protein-Coding Transcripts by the Ensemble Algorithm with a New Hybrid Feature
por: Pian, Cong, et al.
Publicado: (2016)

Deep learning based high-throughput phenotyping of chalkiness in rice exposed to high night temperature
por: Wang, Chaoxin, et al.
Publicado: (2022)

On the utilization of deep and ensemble learning to detect milk adulteration
por: Neto, Habib Asseiss, et al.
Publicado: (2019)

Uncovering mechanisms of transcriptional regulations by systematic mining of cis regulatory elements with gene expression profiles
por: Ma, Qicheng, et al.
Publicado: (2008)

Two Influential Primate Classifications Logically Aligned
por: Franz, Nico M., et al.
Publicado: (2016)

Atmospheric correction of vegetation reflectance with simulation-trained deep learning for ground-based hyperspectral remote sensing
por: Qamar, Farid, et al.
Publicado: (2023)

An open source software for fast grid-based data-mining in spatial epidemiology (FGBASE)
por: Baker, David M, et al.
Publicado: (2014)

MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra
por: Huber, Florian, et al.
Publicado: (2021)

DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information
por: Yang, Xiaoyun, et al.
Publicado: (2021)

Improving multi-scale detection layers in the deep learning network for wheat spike detection based on interpretive analysis
por: Yan, Jiawei, et al.
Publicado: (2023)

Human polyomaviruses identification by logic mining techniques
por: Weitschek, Emanuel, et al.
Publicado: (2012)

MGS2AMR: a gene-centric mining of metagenomic sequencing data for pathogens and their antimicrobial resistance profile
por: Van Camp, Pieter-Jan, et al.
Publicado: (2023)

Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20
por: Darst, Burcu, et al.
Publicado: (2018)

DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics
por: Kienbaum, Lydia, et al.
Publicado: (2021)

Automatic estimation of heading date of paddy rice using deep learning
por: Desai, Sai Vikas, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_i7a0tpi2r41odhcrtbjdb4q6ev