Modified variational bayes EM estimation of hidden markov tree model of cell lineages

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Abstract

Motivation: 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. Results: A variational Bayesian Expectation Maximization (EM) with smoothed probabilities (VBEMS) algorithm for hidden Markov trees (HMT) is proposed for incomplete tree structured data. The full posterior of the HMT parameters is determined and the underflow problems associated with previous algorithms are eliminated. Example results for the prediction of the types of cells in synthetic and real stem cell lineage trees are presented.

Detaljer

Författare
  • Victor Olariu
  • Daniel Coca
  • Stephen A. Billings
  • Peter Tonge
  • Paul Gokhale
  • Peter W. Andrews
  • Visakan Kadirkamanathan
Externa organisationer
  • University of Sheffield
  • Mount Sinai Hospital of University of Toronto
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Annan medicinsk bioteknologi
  • Utvecklingsbiologi
Originalspråkengelska
Sidor (från-till)2824-2830
Antal sidor7
TidskriftBioinformatics
Volym25
Utgivningsnummer21
StatusPublished - 2009 nov 1
PublikationskategoriForskning
Peer review utfördJa
Externt publiceradJa