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Khakhutskyy, V.* ; Schwarzfischer, M. ; Hubig, N. ; Plant, C. ; Marr, C. ; Rieger, M.A.* ; Schröder, T.* ; Theis, F.J.

Centroid clustering of cellular lineage trees.

Lect. Notes Comput. Sc. 8649, 15-29 (2014)
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Open Access Green
Trees representing hierarchical knowledge are prevalent in biology and medicine. Some examples are phylogenetic trees, the hierarchical structure of biological tissues and cell lines. The increasing throughput of techniques generating such trees poses new challenges to the analysis of tree ensembles. Some typical tasks include the determination of common patterns of lineage decisions in cellular differentiation trees. Partitioning the dataset is crucial for further analysis of the cellular genealogies. In this work, we develop a method to cluster labeled binary tree structures. Furthermore, for every cluster our method selects a centroid tree that captures the characteristic mitosis patterns of the group. We evaluate this technique on synthetic data and apply it to experimental trees that embody the lineages of differentiating cells under specific conditions over time. The results of the cell lineage trees are thoroughly interpreted with expert domain knowledge.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Cell Lineage Tree ; Centroid Tree ; Tree Clustering
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
ISBN 978-3-319-10264-1
Konferenztitel Information Technology in Bio- and Medical Informatics
Konferzenzdatum 2. September 2014
Konferenzort Munich, Germany
Quellenangaben Band: 8649, Heft: , Seiten: 15-29 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]