Back to search

Article

Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid Leukemia

2026-05-24

Abstract excerpt

Temporal dynamics of the peripheral blood transcriptome are crucial for understanding leukemia evolution and response to therapy because they can reveal how gene expression programs drive abnormal cell states, disease heterogeneity, and treatment resistance. Using a mathematical model of state-transitions, we studied the temporal dynamics of peripheral blood messenger RNA (mRNA) and microRNA (miRNA) transcriptomes...

Topics

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

Identifiers and source

Literature Corpus work
3b682527-048a-53ae-83a6-92dd2d07f3d7
DOI
10.64898/2026.05.20.726707
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid LeukemiaDOI 10.64898/2026.05.20.726707
State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid LeukemiaSemantic proximity
State-Transition Analysis of Time-Sequential microRNA Expression Predicts Development of Acute Myeloid LeukemiaSemantic proximity
State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia DevelopmentSemantic proximity
State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemiaSemantic proximity
State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid LeukemiaSemantic proximity
Longitudinal single cell RNA-sequencing reveals evolution of micro- and macro-states in chronic myeloid leukemiaSemantic proximity
Data-Driven Math Model of FLT3-ITD Acute Myeloid Leukemia Reveals Potential Therapeutic TargetsSemantic proximity
From molecular interaction to acute promyelocytic leukemia: Calculating leukemogenesis and remission from endogenous molecular-cellular networkSemantic proximity
Molecular Systems Architecture of Interactome in the Acute Myeloid Leukemia MicroenvironmentSemantic proximity
Single-cell immune ecotypes shape microenvironment-modulated evolutionary dynamics in pediatric leukemiaSemantic proximity
A mathematical framework for human neutrophil state transitions inferred from single-cell RNA sequence dataSemantic proximity
Transcriptome free energy can serve as a dynamic patient-specific biomarker in acute myeloid leukemia.Semantic proximity
Select a neighboring publication to make it the new centre.