Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Research graph
References from Deep learning based deconvolution methods: A systematic review. Local targets link to admitted publications; unresolved targets remain external evidence.
High-throughput transcriptomics
10.1038/s41598-022-23985-1 · 2022 · External reference
Immune cell infiltration-based signature for prognosis and immunogenomic analysis in breast cancer
10.1093/bib/bbaa026 · 2020 · External reference
Core immune cell infiltration signatures identify molecular subtypes and promote precise checkpoint immunotherapy in cutaneous melanoma
2022 · External reference
AGR, LMR and SIRI are the optimal combinations for risk stratification in advanced patients with non-small cell lung cancer following immune checkpoint blockers
10.1016/j.intimp.2025.114215 · 2025 · External reference
10.1093/nar/gkae267
10.1093/nar/gkae267 · External reference
Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective
2025 · External reference
AI-driven deep learning techniques in protein structure prediction
2024 · External reference
Deep learning-based approaches for multi-omics data integration and analysis
10.1186/s13040-024-00391-z · 2024 · External reference
Generative artificial intelligence empowers digital twins in drug discovery and clinical trials
10.1080/17460441.2023.2273839 · 2024 · External reference
10.1038/nmeth.3337
10.1038/nmeth.3337 · External reference
10.1007/978-1-0716-0327-7_17
10.1007/978-1-0716-0327-7_17 · External reference
Correction to: molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data
2019 · External reference
10.1038/nature14539
10.1038/nature14539 · External reference
10.1038/s41576-019-0122-6
10.1038/s41576-019-0122-6 · External reference
10.1038/nmeth.3547
10.1038/nmeth.3547 · External reference
10.1038/nature21056
10.1038/nature21056 · External reference
In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics
10.1016/j.compbiolchem.2025.108420 · 2025 · External reference
Modeling polypharmacy side effects with graph convolutional networks
10.1093/bioinformatics/bty294 · 2018 · External reference
10.1038/s41586-021-03819-2
10.1038/s41586-021-03819-2 · External reference
10.1186/gb-2006-7-10-r100
10.1186/gb-2006-7-10-r100 · External reference
10.1038/nbt.4235
10.1038/nbt.4235 · External reference
10.1038/s41467-020-19015-1
10.1038/s41467-020-19015-1 · External reference
10.1038/ncomms3612
10.1038/ncomms3612 · External reference
10.1038/s41587-019-0114-2
10.1038/s41587-019-0114-2 · External reference
10.1038/s41467-018-08023-x
10.1038/s41467-018-08023-x · External reference
CDSeq: a novel complete deconvolution method for dissecting heterogeneous samples using gene expression data
10.1371/journal.pcbi.1007510 · 2019 · External reference
UNDO: a bioconductor R package for unsupervised deconvolution of mixed gene expressions in tumor samples
10.1093/bioinformatics/btu607 · 2014 · External reference
10.1186/s13059-019-1778-0
10.1186/s13059-019-1778-0 · External reference
10.1038/nbt.2203
10.1038/nbt.2203 · External reference
A survey of deep learning models in medical therapeutic areas
10.1016/j.artmed.2021.102020 · 2021 · External reference
10.1038/s41592-018-0229-2
10.1038/s41592-018-0229-2 · External reference
Single-cell type annotation with deep learning in 265 cell types for humans
10.1093/bioadv/vbae054 · 2024 · External reference
Hybrid deep learning models for time series forecasting of solar power
10.1007/s00521-024-09558-5 · 2024 · External reference
A survey of multimodal hybrid deep learning for computer vision: architectures, applications, trends, and challenges
10.1016/j.inffus.2023.102217 · 2024 · External reference
Hybrid deep learning approach to improve classification of low-volume high-dimensional data
10.1186/s12859-023-05557-w · 2023 · External reference
10.1038/s41586-021-03819-2
10.1038/s41586-021-03819-2 · External reference
10.1038/s42256-022-00534-z
10.1038/s42256-022-00534-z · External reference
10.1016/b978-1-4832-1446-7.50035-2
10.1016/b978-1-4832-1446-7.50035-2 · 1988 · External reference
Deep learning in bioinformatics
2016 · External reference
10.1162/neco.1989.1.4.541
10.1162/neco.1989.1.4.541 · External reference
10.7551/mitpress/5236.001.0001
10.7551/mitpress/5236.001.0001 · 1986 · External reference
Unresolved reference
External reference
10.1038/s43588-021-00099-8
10.1038/s43588-021-00099-8 · External reference
scSemiProfiler: advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning
10.1038/s41467-024-50150-1 · 2024 · External reference
Unresolved reference
2014 · External reference
10.1201/b13411
10.1201/b13411 · 2011 · External reference
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
10.1016/j.ijsu.2010.02.007 · 2010 · External reference
10.1186/s13643-021-01626-4
10.1186/s13643-021-01626-4 · External reference
Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement
10.1016/j.jclinepi.2021.02.003 · 2021 · External reference
Digitaldlsorter: deep-learning on scRNA-seq to deconvolute gene expression data
10.3389/fgene.2019.00978 · 2019 · External reference
10.1126/sciadv.aba2619
10.1126/sciadv.aba2619 · External reference
Predicting algorithm of tissue cell ratio based on deep learning using single-cell RNA sequencing
2022 · External reference
10.1016/j.patter.2022.100440
10.1016/j.patter.2022.100440 · External reference
10.1038/s41467-022-34550-9
10.1038/s41467-022-34550-9 · External reference
HArmonized single-cell RNA-seq cell type assisted deconvolution (HASCAD)
10.1186/s12920-023-01674-w · 2023 · External reference
10.1038/ncomms15081
10.1038/ncomms15081 · External reference
10.1038/s41467-023-36961-8
10.1038/s41467-023-36961-8 · External reference
Deep neural network based tissue deconvolution of circulating tumor cell RNA
10.1186/s12967-023-04663-w · 2023 · External reference
NNICE: a deep quantile neural network algorithm for expression deconvolution
10.1038/s41598-024-65053-w · 2024 · External reference
10.1016/j.patter.2024.100969
10.1016/j.patter.2024.100969 · External reference
10.1186/s13059-024-03251-5
10.1186/s13059-024-03251-5 · External reference
10.1016/j.future.2024.07.013
10.1016/j.future.2024.07.013 · External reference
10.1101/2024.07.11.602650
10.1101/2024.07.11.602650 · External reference
10.1016/j.csbj.2021.01.015 · Admitted local publication
Perspectives on systems modeling of human peripheral blood mononuclear cells
2018 · External reference
10.1186/s13059-016-1070-5
10.1186/s13059-016-1070-5 · External reference
10.1038/s41592-019-0355-5
10.1038/s41592-019-0355-5 · External reference
10.1158/1538-7445.am2017-108
10.1158/1538-7445.am2017-108 · External reference
10.1016/j.celrep.2019.01.041
10.1016/j.celrep.2019.01.041 · External reference
10.1101/gr.272344.120
10.1101/gr.272344.120 · External reference
Accurate estimation of cell-type composition from gene expression data
10.1038/s41467-019-10802-z · 2019 · External reference
10.1038/s41467-020-15816-6
10.1038/s41467-020-15816-6 · External reference
10.1038/s43018-022-00356-3
10.1038/s43018-022-00356-3 · External reference
SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references
10.1093/bib/bbz166 · 2020 · External reference
10.1038/s41587-022-01272-8
10.1038/s41587-022-01272-8 · External reference
PUREE: accurate pan-cancer tumor purity estimation from gene expression data
10.1038/s42003-023-04764-8 · 2023 · External reference
10.1101/gr.268722.120
10.1101/gr.268722.120 · External reference
Synthetic single cell RNA sequencing data from small pilot studies using deep generative models
10.1038/s41598-021-88875-4 · 2021 · External reference
ACTIVA: realistic single-cell RNA-seq generation with automatic cell-type identification using introspective variational autoencoders
10.1093/bioinformatics/btac095 · 2022 · External reference
10.1038/s41467-019-14018-z
10.1038/s41467-019-14018-z · External reference