TY  - JOUR
A1  - Hempel, Stefan
A1  - Koseska, Aneta
A1  - Kurths, Jürgen
A1  - Nikoloski, Zoran
T1  - Inner composition alignment for inferring directed networks from short time series
T2  - Physical review letters
N2  - Identifying causal links (couplings) is a fundamental problem that facilitates the understanding of emerging structures in complex networks. We propose and analyze inner composition alignment-a novel, permutation-based asymmetric association measure to detect regulatory links from very short time series, currently applied to gene expression. The measure can be used to infer the direction of couplings, detect indirect (superfluous) links, and account for autoregulation. Applications to the gene regulatory network of E. coli are presented.
Y1  - 2011
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/36730
SN  - 0031-9007
VL  - 107
IS  - 5
PB  - American Physical Society
CY  - College Park
ER  -