@inproceedings{c31ad6453ed14e85ae8cc145b242225c,
title = "Centroid clustering of cellular lineage trees",
abstract = "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.",
keywords = "cell lineage tree, centroid tree, tree clustering",
author = "Valeriy Khakhutskyy and Michael Schwarzfischer and Nina Hubig and Claudia Plant and Carsten Marr and Rieger, {Michael A.} and Timm Schroeder and Theis, {Fabian J.}",
year = "2014",
doi = "10.1007/978-3-319-10265-8_2",
language = "English",
isbn = "9783319102641",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "15--29",
booktitle = "Information Technology in Bio- and Medical Informatics - 5th International Conference, ITBAM 2014, Proceedings",
note = "5th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2014 ; Conference date: 02-09-2014 Through 02-09-2014",
}