Back to search

Article

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia Development

2017-12-22

Abstract excerpt

Temporal dynamics of gene expression are informative of changes associated with disease development and evolution. Given the complexity of high-dimensional temporal datasets, an analytical framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Herein, we use acute myeloid leukemia as a proof-of-principle to model gene expression dynamics in a transcriptom...

Topics

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

Identifiers and source

Literature Corpus work
26c14316-f23f-5f9d-9753-331d2242ccc8
DOI
10.1101/238923
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.
State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia DevelopmentDOI 10.1101/238923
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 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
Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid LeukemiaSemantic proximity
Longitudinal single cell RNA-sequencing reveals evolution of micro- and macro-states in chronic myeloid leukemiaSemantic proximity
Integrating trajectory inference and gene regulatory network analysis to resolve transcriptional programs of T cell state transitions in the tumor microenvironmentSemantic proximity
DyNDG: Identifying Leukemia-Related Genes based on the Time-Series Dynamical Network by Integrating Differential GenesSemantic proximity
Single-Cell Trajectory Inference for Detecting Transient Events in Biological ProcessesSemantic proximity
Generating and navigating single cell dynamics via a geodesic bridge between nonlinear transcriptional and linear latent manifoldsSemantic proximity
Gene-level alignment of single cell trajectoriesSemantic proximity
Generating and navigating single cell dynamics via a geodesic bridge between nonlinear transcriptional and linear latent manifoldsSemantic proximity
Select a neighboring publication to make it the new centre.