Article

DyNDG: Identifying Leukemia-Related Genes based on the Time-Series Dynamical Network by Integrating Differential Genes

2024-11-26

Abstract excerpt

Leukemia is a malignant disease of progressive accumulation characterized by high morbidity and mortality rates, and investigating its disease genes is crucial for understanding its etiology and pathogenesis. Network propagation methods have emerged and been widely employed in disease gene prediction, but most of them focus on static biological networks, which hinders their applicability and effectiveness in the s...

Topics

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

Identifiers and source

Literature Corpus work: dde35079-8f14-5c33-b1f4-580456c57d77
DOI: 10.1101/2024.11.24.624224

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

DyNDG: Identifying Leukemia-Related Genes based on the Time-Series Dynamical Network by Integrating Differential GenesDOI 10.1101/2024.11.24.624224Read

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia DevelopmentSemantic proximity Read

A network-based dynamic criterion for early warning signal discovery: Prediction and early diagnosis for lung adenocarcinomaSemantic proximity Read

Discovery of Dynamic Models for AML Disease Progression from Longitudinal Multi-Modal Clinical Data Using Explainable Machine LearningSemantic proximity Read

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid LeukemiaSemantic proximity Read

Identifying Stage-Specific Genes in Disease Progression using Transition Centrality on Disease Temporal GraphsSemantic proximity Read

NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction.Semantic proximity Read

Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemiaSemantic proximity Read

Identifying the critical states and dynamic network biomarkers of cancers based on network entropySemantic proximity Read

Network model of survival signaling in large granular lymphocyte leukemiaSemantic proximity Read

State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemiaSemantic proximity Read

State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid LeukemiaSemantic proximity Read

Reconstructing disease dynamics for mechanistic insights and clinical benefitSemantic proximity Read