Research graph
References from Cervical cancer survival analysis by integrating multi-omics data through an adaptive weighted deep neural network. Local targets link to admitted publications; unresolved targets remain external evidence.
A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology
10.1093/bfgp/elae013 · 2024 · External reference
decoupleR: ensemble of computational methods to infer biological activities from omics data
10.1093/bioadv/vbac016 · 2022 · External reference
IPF-LASSO: integrative-penalized regression with penalty factors for prediction based on multi-omics data
10.1155/2017/7691937 · 2017 · External reference
Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
2024 · External reference
Machine learning for multi-omics data integration in cancer
10.1016/j.isci.2022.103798 · 2022 · External reference
Integrating multi-omics data through deep learning for accurate cancer prognosis prediction
10.1016/j.compbiomed.2021.104481 · 2021 · External reference
Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer
10.1158/1078-0432.ccr-17-0853 · 2018 · External reference
Deep learning with multimodal representation for pancancer prognosis prediction
10.1093/bioinformatics/btz342 · 2019 · External reference
irGSEA: the integration of single-cell rank-based gene set enrichment analysis
10.1093/bib/bbae243 · 2024 · External reference
Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer
10.1038/s41591-022-02134-1 · 2023 · External reference
SEURAT: visual analytics for the integrated analysis of microarray data
10.1186/1755-8794-3-21 · 2010 · External reference
Spatiotemporally deciphering the mysterious mechanism of persistent HPV-induced malignant transition and immune remodelling from HPV-infected normal cervix, precancer to cervical cancer: Integrating single-cell RNA-sequencing and spatial transcriptome
10.1002/ctm2.1219 · 2023 · External reference
Prediction models for prognosis of cervical cancer: systematic review and critical appraisal
10.3389/fpubh.2021.654454 · 2021 · External reference
Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
10.1016/j.cell.2018.03.022 · 2018 · External reference
Exogenous cathepsin V protein protects human cardiomyocytes HCM from angiotensin Ⅱ-Induced hypertrophy
10.1016/j.biocel.2017.05.020 · 2017 · External reference
MMTM: Multimodal transfer module for CNN fusion
2020 · External reference
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
10.1186/s12874-018-0482-1 · 2018 · External reference
Incidence and mortality of cervix cancer and their relationship with the human development index in 185 countries in the world: An ecology study in 2018
10.4103/aihb.aihb_15_19 · 2019 · External reference
Incorporating deep learning and multi-omics autoencoding for analysis of lung adenocarcinoma prognostication
2020 · External reference
Foundations & trends in multimodal machine learning: Principles, challenges, and open questions
2024 · External reference
Clustering of single-cell multi-omics data with a multimodal deep learning method
10.1038/s41467-022-35031-9 · 2022 · External reference
Interactions of Indoleamine 2, 3-dioxygenase-expressing LAMP3+ dendritic cells with CD4+ regulatory T cells and CD8+ exhausted T cells: synergistically remodeling of the immunosuppressive microenvironment in cervical cancer and therapeutic implications
10.1002/cac2.12486 · 2023 · External reference
limma powers differential expression analyses for RNA-sequencing and microarray studies
10.1093/nar/gkv007 · 2015 · External reference
Perturbation-response genes reveal signaling footprints in cancer gene expression
10.1038/s41467-017-02391-6 · 2018 · External reference
Immunedeconv: an R package for unified access to computational methods for estimating immune cell fractions from bulk RNA-sequencing data
10.1007/978-1-0716-0327-7_16 · 2020 · External reference
The lasso method for variable selection in the Cox model
10.1002/(sici)1097-0258(19970228)16:4<385::aid-sim380>3.0.co;2-3 · 1997 · External reference
Support vector methods for survival analysis: a comparison between ranking and regression approaches
10.1016/j.artmed.2011.06.006 · 2011 · External reference
TCGA-assembler 2: software pipeline for retrieval and processing of TCGA/CPTAC data
10.1093/bioinformatics/btx812 · 2018 · External reference
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks
2022 · External reference
Decontamination of ambient RNA in single-cell RNA-seq with DecontX
10.1186/s13059-020-1950-6 · 2020 · External reference
Inferring tumour purity and stromal and immune cell admixture from expression data
10.1038/ncomms3612 · 2013 · External reference
clusterProfiler: an R package for comparing biological themes among gene clusters
10.1089/omi.2011.0118 · 2012 · External reference
IOBR: multi-omics immuno-oncology biological research to decode tumor microenvironment and signatures
10.3389/fimmu.2021.687975 · 2021 · External reference
Unsupervised inference of developmental directions for single cells using VECTOR
10.1016/j.celrep.2020.108069 · 2020 · External reference
