Modified variational Bayes EM estimation of hidden Markov tree model of cell lineages | Zendy

Victor Olariu | Zendy; Daniel Coca | Zendy; S.A. Billings | Zendy; Peter J. Tonge | Zendy; Paul J. Gokhale | Zendy; Peter W. Andrews | Zendy; Visakan Kadirkamanathan | Zendy

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Modified variational Bayes EM estimation of hidden Markov tree model of cell lineages

Author(s) -

Victor Olariu,

Daniel Coca,

S.A. Billings,

Peter J. Tonge,

Paul J. Gokhale,

Peter W. Andrews,

Visakan Kadirkamanathan

Publication year - 2009

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btp456

Subject(s) - lineage (genetic) , tree (set theory) , computer science , bayes' theorem , markov chain , coalescent theory , population , markov model , hidden markov model , bayesian probability , algorithm , expectation–maximization algorithm , artificial intelligence , biology , mathematics , machine learning , statistics , combinatorics , phylogenetic tree , maximum likelihood , genetics , sociology , demography , gene

Human pluripotent stem cell lines persist in culture as a heterogeneous population of SSEA3 positive and SSEA3 negative cells. Tracking individual stem cells in real time can elucidate the kinetics of cells switching between the SSEA3 positive and negative substates. However, identifying a cell's substate at all time points within a cell lineage tree is technically difficult.

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