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References from Integration strategies of multi-omics data for machine learning analysis. Local targets link to admitted publications; unresolved targets remain external evidence.
Integrated omics: tools, advances, and future approaches
2018 · External reference
Practicing precision medicine with intelligently integrative clinical and multi-omics data analysis
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Precision Medicine: Where have we reached and where are we headed?
2017 · External reference
Evidence-based precision medicine is needed to move toward general internal precision medicine
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10.1186/s13059-017-1215-1
10.1186/s13059-017-1215-1 · External reference
Integrative analysis of multi-omics data for discovery and functional studies of complex human diseases
10.1016/bs.adgen.2015.11.004 · 2016 · External reference
Synthesizing systems biology knowledge from omics using genome-scale models
10.1002/pmic.201900282 · 2020 · External reference
Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data
2018 · External reference
Integration of multi-omics data for integrative gene regulatory network inference
10.1504/ijdmb.2017.087178 · 2017 · External reference
MONET: Multi-omic module discovery by omic selection
10.1371/journal.pcbi.1008182 · 2020 · External reference
10.1093/bioinformatics/btz318
10.1093/bioinformatics/btz318 · External reference
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Unresolved reference
External reference
10.1089/omi.2015.0020
10.1089/omi.2015.0020 · External reference
10.1016/j.inffus.2018.09.012
10.1016/j.inffus.2018.09.012 · External reference
Methods for the integration of multi-omics data: mathematical aspects
10.1186/s12859-015-0857-9 · 2016 · External reference
More is better: recent progress in multi-omics data integration methods
10.3389/fgene.2017.00084 · 2017 · External reference
A review on machine learning principles for multi-view biological data integration
2018 · External reference
Integrated multi-omics analyses in oncology: a review of machine learning methods and tools
10.3389/fonc.2020.01030 · 2020 · External reference
10.1038/nrg3868
10.1038/nrg3868 · External reference
A selective review of multi-level omics data integration using variable selection
2019 · External reference
Dimension reduction techniques for the integrative analysis of multi-omics data
10.1093/bib/bbv108 · 2016 · External reference
Performance comparison of deep learning autoencoders for cancer subtype detection using multi-omics data
10.3390/cancers13092013 · 2021 · External reference
Multi-omic and multi-view clustering algorithms: review and cancer benchmark
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Evaluation of integrative clustering methods for the analysis of multi-omics data
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10.20944/preprints201804.0352.v1 · External reference
Heterogeneous multi-layered network model for omics data integration and analysis
10.3389/fgene.2019.01381 · 2019 · External reference
Transcriptomic and metabolomic data integration
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Metabolomics and multi-omics integration: a survey of computational methods and resources
10.3390/metabo10050202 · 2020 · External reference
Computational analysis of phosphoproteomics data in multi-omics cancer studies
10.1002/pmic.201900312 · 2021 · External reference
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10.1007/s00204-020-02656-y · External reference
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10.1089/omi.2015.0185 · External reference
10.1021/acsinfecdis.9b00080
10.1021/acsinfecdis.9b00080 · External reference
Systematic multi-omics integration (MOI) approach in plant systems biology
10.3389/fpls.2020.00944 · 2020 · External reference
Relevance of multi-omics studies in cardiovascular diseases
10.3389/fcvm.2019.00091 · 2019 · External reference
Multi-omics approaches to improve mitochondrial disease diagnosis: challenges, advances, and perspectives
10.3389/fmolb.2020.590842 · 2020 · External reference
From multi-omics approaches to precision medicine in amyotrophic lateral sclerosis
10.3389/fnins.2020.577755 · 2020 · External reference
A review of integrative imputation for multi-omics datasets
10.3389/fgene.2020.570255 · 2020 · External reference
Machine learning and integrative analysis of biomedical big data
10.3390/genes10020087 · 2019 · External reference
10.1145/2347736.2347755
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10.1038/227561a0
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Exploring the molecular basis of age-related disease comorbidities using a multi-omics graphical model
10.1038/srep37646 · 2016 · External reference
Unresolved reference
External reference
Integrating correlation-based feature selection and clustering for improved cardiovascular disease diagnosis
10.1155/2018/2520706 · 2018 · External reference
10.1007/3-540-57868-4_57
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Theoretical comparison between the Gini index and information gain criteria
10.1023/b:amai.0000018580.96245.c6 · 2004 · External reference
Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy
10.1109/tpami.2005.159 · 2005 · External reference
Unresolved reference
External reference
Structured sparsity regularization for analyzing high-dimensional omics data
10.1093/bib/bbaa122 · 2021 · External reference
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10.1038/nbt0308-303 · External reference
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Independent component analysis for unraveling the complexity of cancer omics datasets
10.3390/ijms20184414 · 2019 · External reference
10.1198/106186006x113430
10.1198/106186006x113430 · External reference
Sparse canonical correlation analysis
10.1007/s10994-010-5222-7 · 2011 · External reference
Sparse nonnegative matrix factorization with ℓ0-constraints
10.1016/j.neucom.2011.09.024 · 2012 · External reference
Unresolved reference
External reference
integrative analysis of multi-omics data based on blockwise sparse principal components
10.3390/ijms21218202 · 2020 · External reference
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10.1186/1471-2164-10-32 · 2009 · External reference
Unresolved reference
External reference
10.1101/317982
10.1101/317982 · External reference
Integration of clinical chemistry, expression, and metabolite data leads to better toxicological class separation
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Group lasso regularized deep learning for cancer prognosis from multi-omics and clinical features
2019 · External reference
10.1158/1078-0432.ccr-17-0853
10.1158/1078-0432.ccr-17-0853 · External reference
Interpretation of deep learning in genomics and epigenomics
2020 · External reference
Unresolved reference
External reference
Pathway-guided deep neural network toward interpretable and predictive modeling of drug sensitivity
10.1021/acs.jcim.0c00331 · 2020 · External reference
Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data
2019 · External reference
Learning the structure of mixed graphical models
10.1080/10618600.2014.900500 · 2015 · External reference
10.1016/j.bbagrm.2019.194418
10.1016/j.bbagrm.2019.194418 · External reference
Stable graphical model estimation with Random Forests for discrete, continuous, and mixed variables
10.1016/j.csda.2013.02.022 · 2013 · External reference
piMGM: incorporating multi-source priors in mixed graphical models for learning disease networks
10.1093/bioinformatics/bty591 · 2018 · External reference
10.1093/bioinformatics/btv268
10.1093/bioinformatics/btv268 · External reference
Inferring regulatory networks from mixed observational data using directed acyclic graphs
10.3389/fgene.2020.00008 · 2020 · External reference
Inferring interaction networks from multi-omics data
2019 · External reference
Unresolved reference
External reference
10.1007/978-1-4615-0907-3_3
10.1007/978-1-4615-0907-3_3 · External reference
Multilevel heterogeneous omics data integration with kernel fusion
10.1093/bib/bby115 · 2018 · External reference
Integrating Clinical and Multiple Omics Data for Prognostic Assessment across Human Cancers
2017 · External reference
Multiple kernel learning algorithms
2011 · External reference
10.1101/415950
10.1101/415950 · External reference
SimpleMKL
2008 · External reference
SpicyMKL: a fast algorithm for Multiple Kernel Learning with thousands of kernels
10.1007/s10994-011-5252-9 · 2011 · External reference
Classifying breast cancer subtypes using multiple kernel learning based on omics data
2019 · External reference
Improve glioblastoma multiforme prognosis prediction by using feature selection and multiple kernel learning
10.1109/tcbb.2016.2551745 · 2016 · External reference
Integrating somatic mutations for breast cancer survival prediction using machine learning methods
2021 · External reference
10.1038/nmeth.4207
10.1038/nmeth.4207 · External reference
Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival
10.1038/s41467-018-06921-8 · 2018 · External reference
10.1101/139287
10.1101/139287 · External reference
Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery
10.1093/bioinformatics/btv244 · 2015 · External reference
Unresolved reference
External reference
10.1038/nmeth.2810
10.1038/nmeth.2810 · External reference
Affinity network fusion and semi-supervised learning for cancer patient clustering
10.1016/j.ymeth.2018.05.020 · 2018 · External reference
Multi-dimensional data integration algorithm based on random walk with restart
2021 · External reference
10.21203/rs.3.rs-56433/v1
10.21203/rs.3.rs-56433/v1 · External reference
Integrative network fusion: a multi-omics approach in molecular profiling
10.3389/fonc.2020.01065 · 2020 · External reference
10.1093/bioinformatics/bty637
10.1093/bioinformatics/bty637 · External reference
Network-based prioritization of cancer genes by integrative ranks from multi-omics data
10.1016/j.compbiomed.2020.103692 · 2020 · External reference
Unresolved reference
External reference
Topologically inferring risk-active pathways toward precise cancer classification by directed random walk
10.1093/bioinformatics/btt373 · 2013 · External reference
Robust pathway-based multi-omics data integration using directed random walks for survival prediction in multiple cancer studies
2019 · External reference
10.1101/2020.07.22.163949
10.1101/2020.07.22.163949 · External reference
To embed or not: network embedding as a paradigm in computational biology
10.3389/fgene.2019.00381 · 2019 · External reference
Graph embedding on biomedical networks: methods, applications and evaluations
2019 · External reference
A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
2017 · External reference
Diffusion component analysis: unraveling functional topology in biological networks
10.1007/978-3-319-16706-0_9 · 2015 · External reference
Gradient boosting decision tree-based method for predicting interactions between target genes and drugs
10.3389/fgene.2019.00459 · 2019 · External reference
deepNF: deep network fusion for protein function prediction
10.1093/bioinformatics/bty440 · 2018 · External reference
10.1093/bioinformatics/btz418
10.1093/bioinformatics/btz418 · External reference
10.1145/3270323.3270326
10.1145/3270323.3270326 · External reference
PIMKL: Pathway-induced multiple kernel learning
10.1038/s41540-019-0086-3 · 2019 · External reference
PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering
10.1093/bioinformatics/btaa655 · 2021 · External reference
A Comprehensive survey on graph neural networks
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10.1093/bioinformatics/bty294
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10.1101/2020.07.08.192930
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Deep learning-based multi-omics data integration reveals two prognostic subtypes in high-risk neuroblastoma
10.3389/fgene.2018.00477 · 2018 · External reference
A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data
2019 · External reference
Classifying breast cancer subtypes using deep neural networks based on multi-omics data
10.3390/genes11080888 · 2020 · External reference
10.1016/j.csbj.2020.08.005 · 2020 · Admitted local publication
Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data
10.1093/bioinformatics/btab109 · 2021 · External reference
Structural learning and integrative decomposition of multi-view data
10.1111/biom.13108 · 2019 · External reference
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A non-negative matrix factorization method for detecting modules in heterogeneous omics multi-modal data
2015 · External reference
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Benchmarking joint multi-omics dimensionality reduction approaches for the study of cancer
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2016 · External reference
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Network-based integrative clustering of multiple types of genomic data using non-negative matrix factorization
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Biomarker discovery by integrated joint non-negative matrix factorization and pathway signature analyses
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Multi-Omics Factor Analysis—a framework for unsupervised integration of multi-omics data sets
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An integrative multi-omics approach reveals new central nervous system pathway alterations in Alzheimer’s disease
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DNA methylation and gene expression integration in cardiovascular disease
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