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Multi-scale context aggregation by dilated convolutions

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The Gene Ontology Resource: 20 years and still GOing strong

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Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells

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Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

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Predicting effects of noncoding variants with deep learning–based sequence model

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A universal SNP and small-indel variant caller using deep neural networks

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Deep learning for computational biology

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The human splicing code reveals new insights into the genetic determinants of disease

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

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Network-based stratification of tumor mutations

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Machine learning for integrating data in biology and medicine: principles, practice, and opportunities

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Network propagation: a universal amplifier of genetic associations

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Network-constrained regularization and variable selection for analysis of genomic data

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DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

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DeepGOPlus: improved protein function prediction from sequence

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Reproducible RNA-seq analysis using recount2

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Using deep learning to model the hierarchical structure and function of a cell

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Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets

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CYCLOPS reveals human transcriptional rhythms in health and disease

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DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning

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A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation

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Using neural networks for reducing the dimensions of single-cell RNA-Seq data

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A multi-task convolutional deep neural network for variant calling in single molecule sequencing

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Visible Machine Learning for Biomedicine

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To Embed or Not: Network Embedding as a Paradigm in Computational Biology

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

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Deep convolutional neural networks for accurate somatic mutation detection

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DEEP: a general computational framework for predicting enhancers

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MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease

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Pathway-level information extractor (PLIER) for gene expression data

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COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH)

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netNMF-sc: leveraging gene–gene interactions for imputation and dimensionality reduction in single-cell expression analysisPreprint

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Attend and Predict: Understanding Gene Regulation by Selective Attention on ChromatinPreprint

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Nonparametric pathway-based regression models for analysis of genomic data

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Circular Nodes in Neural Networks

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DeepDiff: DEEP-learning for predicting DIFFerential gene expression from histone modifications

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A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer

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Predictive Modeling of Microbiome Data Using a Phylogeny-Regularized Generalized Linear Mixed Model

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Learning Explainable Models Using Attribution Priors

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MRCNN: a deep learning model for regression of genome-wide DNA methylation

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Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer

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A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data

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Graph-regularized dual Lasso for robust eQTL mapping

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Deep learning at base-resolution reveals motif syntax of the cis-regulatory codePreprint

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Diet Networks: Thin Parameters for Fat GenomicsPreprint

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A Phylogeny-Regularized Sparse Regression Model for Predictive Modeling of Microbial Community Data

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PIMKL: Pathway-Induced Multiple Kernel Learning

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Robust phenotype prediction from gene expression data using differential shrinkage of co-regulated genes

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Genetic Neural Networks: an artificial neural network architecture for capturing gene expression relationships

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Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data

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netReg: network-regularized linear models for biological association studies

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cDeepbind: A context sensitive deep learning model of RNA-protein bindingPreprint

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A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity

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Integrative Analysis of Genetical Genomics Data Incorporating Network Structures

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Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data

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netNMF-sc: Leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysisPreprint

Elyanow, R., Dumitrascu, B., Engelhardt, B. E., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/544346 · Cited by 6 · see citing works

SICaRiO: short indel call filtering with boosting

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Analysis of Gene Interaction Graphs for Biasing Machine Learning Models

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In Response to Comment on ‘Network-constrained regularization and variable selection for analysis of genomic data’

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Machine learning-based detection of insertions and deletions in the human genomePreprint

Curnin, C., Goldfeder, R. L., Marwaha, S., Bonner, D. E., Waggott, D. M., Undiagnosed Diseases Network, Wheeler, M. T., & Ashley, E. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/628222 · Cited by 4 · see citing works

Is graph-based feature selection of genes better than random?Preprint

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Graph representation learning in biomedicine and healthcare

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Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients

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Correlation and association analyses in microbiome study integrating multiomics in health and disease

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SLNL: A novel method for gene selection and phenotype classification

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Seven myths of how transcription factors read the cis-regulatory code

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miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning

Jabeer, A., Temiz, M., Bakır-Güngör, B., & Yousef, M. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2022.1076554 · Cited by 31 · see citing works

Multiomics dynamic learning enables personalized diagnosis and prognosis for pancancer and cancer subtypes

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DMOIT: denoised multi-omics integration approach based on transformer multi-head self-attention mechanism

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MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks

Levy, J., Chen, Y., Azizgolshani, N., Petersen, C. L., Titus, A., Moen, E. L., Vaickus, L. J., Salas, L. A., & Christensen, B. C. (2021) · npj Systems Biology and Applications · doi:10.1038/s41540-021-00193-7 · Cited by 25 · see citing works

Knowledge-slanted random forest method for high-dimensional data and small sample size with a feature selection application for gene expression data

Cantor, E. J., Guauque-Olarte, S., León, R., Chabert, S., & Rodrigo Salas, F. (2024) · BioData Mining · doi:10.1186/s13040-024-00388-8 · Cited by 23 · see citing works

Visible neural networks for multi-omics integration: a critical review

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Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data

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The Validity of Machine Learning Procedures in Orthodontics: What Is Still Missing?

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Survey of Various Statistical Numerical and Machine Learning Ontological Models on Infectious Disease Ontology

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Machine learning in the prognostic appraisal of Class III growth

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Shaping the future of precision oncology: Integrating circadian medicine and mathematical models for personalized cancer treatment

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Predicting gene-level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework

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Predicting Phenotypes From High-Dimensional Genomes Using Gradient Boosting Decision Trees

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MVMSGAT: Integrating Multiview, Multi-Scale Graph Convolutional Networks with Biological Prior Knowledge for Predicting Bladder Cancer Response to Neoadjuvant Therapy

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Enhancing chemotherapy response prediction via matched colorectal tumor-organoid gene expression analysis and network-based biomarker selection

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MACHINE LEARNING FOR DETECTING EPISTASIS INTERACTIONS AND ITS RELEVANCE TO PERSONALIZED MEDICINE IN ALZHEIMER’S DISEASE: SYSTEMATIC REVIEW

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Reducing variability of breast cancer subtype predictors by grounding deep learning models in prior knowledge

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Biological knowledge-slanted random forest approach for the classification of calcified aortic valve stenosis

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Trust in Artificial Intelligence: Clinicians Are Essential

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Impacts of process parameters on diesel reforming via interpretable machine learning

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Bridging “Big Data” and Mechanistic Insight To Enable Precision Medicine

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Deep learning method for predicting the complex nonlinear dynamics of passively mode-locked fiber laser

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Development of a machine learning-based prognostic model for survival prediction in patients with lung cancer brain metastases using multicenter clinical data

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Semisupervised Contrastive Learning for Bioactivity Prediction Using Cell Painting Image Data

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Machine Learning Uses Chemo-Transcriptomic Profiles to Stratify Antimalarial Compounds With Similar Mode of Action

van Heerden, A., van Wyk, R., & Birkholtz, L. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.688256 · Cited by 3 · see citing works

Discovery of Oncogenic Mediator Genes in Rectal Cancer Chemotherapy Response using Gene Expression Data from Matched Tumor and Patient-Derived OrganoidPreprint

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Optimizing Model Performance and Interpretability: Application to Biological Data Classification

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Tree-based variational inference for Poisson log-normal models

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Using ontology embeddings for structural inductive bias in gene expression data analysisPreprint

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