@article{200201,
  author = {Paul Villoutreix and Joakim Anden and Bomyi Lim and Hang Lu and IoannisG. Kevrekidis and Amit Singer and Stanislav Y. Shvartsman},
  title = {Synthesizing developmental trajectories},
  abstract = { Dynamical processes in biol. are studied using an ever-increasing number of techniques, each of which brings out unique features of the system. One of the current challenges is to develop systematic approaches for fusing heterogeneous datasets into an integrated view of multivariable dynamics. We demonstrate that heterogeneous data fusion can be successfully implemented within a semi-supervised learning framework that exploits the intrinsic geometry of high-dimensional datasets. We illustrate our approach using a dataset from studies of pattern formation in Drosophila. The result is a continuous trajectory that reveals the joint dynamics of gene expression, subcellular protein localization, protein phosphorylation, and tissue morphogenesis. Our approach can be readily adapted to other imaging modalities and forms a starting point for further steps of data analytics and modeling of biol. dynamics. },
  year = {2017},
  journal = {PLoS Comput. Biol.},
  volume = {13},
  number = {9},
  pages = {e1005742/1},
  publisher = {Public Library of Science},
  isbn = {1553-73581553-734X},
  url = {https://doi.org/10.1371/journal.pcbi.1005742},
  language = {eng},
}