Article

PathExpSurv: Pathway Expansion for Explainable Survival Analysis and Disease Gene Discovery

2022-11-09

Abstract excerpt

<h4>Motivation</h4> In the field of biology and medicine, the interpretability and accuracy are both important when designing predictive models. The interpretability of many machine learning models such as neural networks is still a challenge. Recently, many researchers utilized prior information such as biological pathways to develop bioinformatics methods based on neural networks, so that the prior information...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 13aa86dc-6c28-5cf6-99a4-a985e079e4fb
DOI: 10.1101/2022.11.08.515625

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

PathExpSurv: Pathway Expansion for Explainable Survival Analysis and Disease Gene DiscoveryDOI 10.1101/2022.11.08.515625Read

Investigate the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning modelSemantic proximity Read

Investigating the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning modelSemantic proximity Read

PathX-CNN: An Enhanced Explainable Convolutional Neural Network for Survival Prediction and Pathway Analysis in GlioblastomaSemantic proximity Read

MPVNN: Mutated Pathway Visible Neural Network architecture for interpretable prediction of cancer-specific survival risk.Semantic proximity Read

Cancer subtype classification and modeling by pathway attention and propagationSemantic proximity Read

Path2Surv: Pathway/gene set-based survival analysis using multiple kernel learningSemantic proximity Read

Pathway-guided deep neural network toward interpretable and predictive modeling of drug sensitivitySemantic proximity Read

AUTOSurv: Interpretable Deep Learning Framework for Cancer Survival Analysis Incorporating Clinical and Multi-omics DataSemantic proximity Read

PINT: Pathway-pathway interactions for predicting interpretable clinical outcomes from gene expressionSemantic proximity Read

A comprehensive analysis of prognosis prediction models based on pathway‑level, gene‑level and clinical information for glioblastomaSemantic proximity Read

PINNet: a deep neural network with pathway prior knowledge for Alzheimer's diseaseSemantic proximity Read

Identification of informative genes and sub-pathways using Improved Differential Expression Analysis for Pathways (iDEAP) for cancer classificationSemantic proximity Read