A roadmap for multi-omics data integration using deep learning

MuSA: a graphical user interface for multi-OMICs data integration in radiogenomic studies

(2021) Mario Zanfardino et al.   Scientific Reports

Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy

(2021) Sunan Cui et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

GPDBN: deep bilinear network integrating both genomic data and pathological images for breast cancer prognosis prediction

(2021) Zhiqin Wang et al.   BIOINFORMATICS

Deep learning identifies synergistic drug combinations for treating COVID-19

(2021) Wengong Jin et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Integrative analysis of cross-modal features for the prognosis prediction of clear cell renal cell carcinoma

(2020) Zhenyuan Ning et al.   BIOINFORMATICS

Optimization and expansion of non-negative matrix factorization

(2020) Xihui Lin et al.   BMC BIOINFORMATICS

A Pretraining-Retraining Strategy of Deep Learning Improves Cell-Specific Enhancer Predictions

(2020) Xiaohui Niu et al.   Frontiers in Genetics

The Application of Deep Learning in Cancer Prognosis Prediction

(2020) Wan Zhu et al.   Cancers

iSOM-GSN: An Integrative Approach for Transforming Multi-omic Data into Gene Similarity Networks via Self-organizing Maps

(2020) Nazia Fatima et al.   BIOINFORMATICS

PathME: pathway based multi-modal sparse autoencoders for clustering of patient-level multi-omics data

(2020) Amina Lemsara et al.   BMC BIOINFORMATICS

Resolving Clinical Phenotypes into Endotypes in Allergy: Molecular and Omics Approaches

(2020) Tesfaye B. Mersha et al.   CLINICAL REVIEWS IN ALLERGY & IMMUNOLOGY

Incorporating deep learning and multi-omics autoencoding for analysis of lung adenocarcinoma prognostication

(2020) Tzong-Yi Lee et al.   COMPUTATIONAL BIOLOGY AND CHEMISTRY

Whole slide images reflect DNA methylation patterns of human tumors

(2020) Hong Zheng et al.   npj Genomic Medicine

Amino acid encoding for deep learning applications

(2020) Hesham ElAbd et al.   BMC BIOINFORMATICS

Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration

(2020) Dibyendu Bikash Seal et al.   GENOMICS

Integrating Multi-Omics Data by Learning Modality Invariant Representations for Improved Prediction of Overall Survival of Cancer

(2020) Li Tong et al.   METHODS

A deep learning model to predict RNA-Seq expression of tumours from whole slide images

(2020) Benoît Schmauch et al.   Nature Communications

Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning–based neural network

(2020) Xiang Zhou et al.   GigaScience

A Deep Learning Approach for Missing Data Imputation of Rating Scales Assessing Attention-Deficit Hyperactivity Disorder

(2020) Chung-Yuan Cheng et al.   Frontiers in Psychiatry

Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis

(2020) Li Tong et al.   BMC Medical Informatics and Decision Making

A Review of Integrative Imputation for Multi-Omics Datasets

(2020) Meng Song et al.   Frontiers in Genetics

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data

(2020) Satoshi Takahashi et al.   Biomolecules

A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model

(2020) Yuhua Fu et al.   Communications Biology

Survival prediction in patients with colon adenocarcinoma via multiomics data integration using a deep learning algorithm

(2020) Jiudi Lv et al.   BIOSCIENCE REPORTS

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

(2020) Richard J. Chen et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Predicting Splicing from Primary Sequence with Deep Learning

(2019) Kishore Jaganathan et al.   CELL

Recent Advances of Deep Learning in Bioinformatics and Computational Biology

(2019) Binhua Tang et al.   Frontiers in Genetics

SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer

(2019) Zhi Huang et al.   Frontiers in Genetics

Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features

(2019) Gangcai Xie et al.   Genes

Machine Learning and Integrative Analysis of Biomedical Big Data

(2019) Bilal Mirza et al.   Genes

Performance comparison of linear and non-linear feature selection methods for the analysis of large survey datasets

(2019) Olga Krakovska et al.   PLoS One

Unsupervised classification of multi-omics data during cardiac remodeling using deep learning

(2019) Neo Christopher Chung et al.   METHODS

NEMO: cancer subtyping by integration of partial multi-omic data

(2019) Nimrod Rappoport et al.   BIOINFORMATICS

Deep learning in bioinformatics: Introduction, application, and perspective in the big data era

(2019) Yu Li et al.   METHODS

MOLI: multi-omics late integration with deep neural networks for drug response prediction

(2019) Hossein Sharifi-Noghabi et al.   BIOINFORMATICS

The Need for Multi-Omics Biomarker Signatures in Precision Medicine

(2019) Michael Olivier et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data

(2019) Jing Xu et al.   BMC BIOINFORMATICS

Bringing radiomics into a multi-omics framework for a comprehensive genotype–phenotype characterization of oncological diseases

(2019) Mario Zanfardino et al.   Journal of Translational Medicine

Definitions, methods, and applications in interpretable machine learning

(2019) W. James Murdoch et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Integrative transcriptome imputation reveals tissue-specific and shared biological mechanisms mediating susceptibility to complex traits

(2019) Wen Zhang et al.   Nature Communications

Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data

(2019) Jie Hao et al.   BMC Medical Genomics

Techniques for interpretable machine learning

(2019) Mengnan Du et al.   COMMUNICATIONS OF THE ACM

Cluster analysis on high dimensional RNA-seq data with applications to cancer research - An evaluation study

(2019) Linda Vidman et al.   PLoS One

A Review of Kernel Methods for Feature Extraction in Nonlinear Process Monitoring

(2019) Karl Ezra Pilario et al.   Processes

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

(2018) Ricard Argelaguet et al.   Molecular Systems Biology

Training neural networks on high-dimensional data using random projection

(2018) Piotr Iwo Wójcik et al.   PATTERN ANALYSIS AND APPLICATIONS

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

(2018) Travers Ching et al.   PLoS Computational Biology

TOBMI: Trans-omics block missing data imputation using a k-Nearest Neighbor weighted approach

(2018) Xuesi Dong et al.   BIOINFORMATICS

Deep-FS: A Feature Selection Algorithm for Deep Boltzmann Machines

(2018) Aboozar Taherkhani et al.   NEUROCOMPUTING

PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data

(2018) Jie Hao et al.   BMC BIOINFORMATICS

Leveraging Multilayered “Omics” Data for Atopic Dermatitis: A Road Map to Precision Medicine

(2018) Debajyoti Ghosh et al.   Frontiers in Immunology

Deep Learning-Based Multi-Omics Data Integration Reveals Two Prognostic Subtypes in High-Risk Neuroblastoma

(2018) Li Zhang et al.   Frontiers in Genetics

Late Fusion Incomplete Multi-View Clustering

(2018) Xinwang Liu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Metabolomics analysis identifies different metabotypes of asthma severity

(2017) Stacey N. Reinke et al.   EUROPEAN RESPIRATORY JOURNAL

–Omic and Electronic Health Record Big Data Analytics for Precision Medicine

(2017) Po-Yen Wu et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

(2017) Safoora Yousefi et al.   Scientific Reports

More Is Better: Recent Progress in Multi-Omics Data Integration Methods

(2017) Sijia Huang et al.   Frontiers in Genetics

Deep learning in bioinformatics

(2016) Seonwoo Min et al.   BRIEFINGS IN BIOINFORMATICS

Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks

(2016) David R. Kelley et al.   GENOME RESEARCH

Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters

(2016) Yifeng Li et al.   JOURNAL OF COMPUTATIONAL BIOLOGY

Omics Profiling in Precision Oncology

(2016) Kun-Hsing Yu et al.   MOLECULAR & CELLULAR PROTEOMICS

Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data

(2016) Alexander Aliper et al.   MOLECULAR PHARMACEUTICS

The 2016 database issue ofNucleic Acids Researchand an updated molecular biology database collection

(2016) Daniel J. Rigden et al.   NUCLEIC ACIDS RESEARCH

Systems biology of asthma and allergic diseases: A multiscale approach

(2015) Supinda Bunyavanich et al.   JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY

Clinical implications of omics and systems medicine: focus on predictive and individualized treatment

(2015) M. Benson   JOURNAL OF INTERNAL MEDICINE

Deep learning

(2015) Yann LeCun et al.   NATURE

Multiblock Discriminant Analysis for Integrative Genomic Study

(2015) Mingon Kang et al.   Biomed Research International

Knowledge Discovery and interactive Data Mining in Bioinformatics - State-of-the-Art, future challenges and research directions

(2014) Andreas Holzinger et al.   BMC BIOINFORMATICS

Survival analysis and regression models

(2014) Brandon George et al.   JOURNAL OF NUCLEAR CARDIOLOGY

Reuse of public genome-wide gene expression data

(2012) Johan Rung et al.   NATURE REVIEWS GENETICS

An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies

(2009) L. J. Lancashire et al.   BRIEFINGS IN BIOINFORMATICS

1000 Genomes project

(2008) Nayanah Siva   NATURE BIOTECHNOLOGY