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Clinical trajectories estimated from bulk tumoral molecular profiles using elastic principal trees

Authors: Chervov, Alexander; Zinovyev, Andrei;

Clinical trajectories estimated from bulk tumoral molecular profiles using elastic principal trees

Abstract

Clinical trajectory is a clinically relevant sequence of ordered patient phenotypes representing consecutive states of a developing disease and leading to some final state. Extracting trajectories from large scale medical data is of great interest for dynamical phenotyping of various diseases but remains a challenge for machine learning methods, especially in the case of synchronic (with short follow up) observations. Here we describe an approach for trajectory-based analysis of cancer data using elastic principal trees and test it on a large collection of molecular tumoral profiles for breast cancer. We show that the disease progress quantified with pseudotime (the geodesic distance from the root) along a particular trajectory can serve as a significant prognostic factor, not redundant with gene expression-based predictors. We conclude that application of the elastic principal trees to transcriptomic data can be of interest for clinical applications.

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France
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Subjects by Vocabulary

Microsoft Academic Graph classification: Sequence Prognostic factor Geodesic Scale (ratio) Computer science business.industry Principal (computer security) Pattern recognition Cancer data Trajectory Artificial intelligence Disease progress business

Keywords

principal tree, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], survival analysis, breast cancer, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], clinical trajectories,, transcriptome

32 references, page 1 of 4

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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