arXiv: Research article Reconstructing large networks with time-varying interactions Authors: Chun-Wei Chang1,2, Takeshi Miki3,4.5, Masayuki Ushio6,7, Hsiao-Pei Lu8, Fuh- Kwo Shiah2,3, Chih-hao Hsieh1,2,3,9* Affiliations: 1National Center for Theoretical Sciences, Taipei 10617, Taiwan 2Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan 3Institute of Oceanography, National Taiwan University, Taipei 10617, Taiwan 4Department of Environmental Engineering and Ecology, Faculty of Advanced Science and Technology, Ryukoku University, Otsu, Shiga, 520-2194, Japan 5Center for Biodiversity Science, Ryukoku University, Otsu, Shiga, 520-2194, Japan 6Hakubi Center, Kyoto University, Kyoto, Kyoto 606-8501, Japan 7Center for Ecological Research, Kyoto University, Otsu, Shiga 520-2113, Japan 8Department of Biotechnology and Bioindustry Sciences, National Cheng Kung University, Tainan, Taiwan 9Institute of Ecology and Evolutionary Biology, Department of Life Science, National Taiwan University, Taipei 10617, Taiwan * Correspondence to: Chih-hao Hsieh; Email:
[email protected] Running title: Reconstruction of high-dimensional networks Keywords: Interaction network, Network topology, Dynamical stability, Microbial community. 1 Number of words in abstract: 196 Number of words in main text: 4252 Number of cited references: 47 Number of tables & figures: 4 figures and 1 table 2 Abstract Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality (i.e. number of interacting components) is usually high and interactions are time-varying. These pose a challenge to existing methods that can quantify only small interaction networks or assume static interactions under steady state. Here, we proposed a novel approach to reconstruct high-dimensional, time-varying interaction networks using empirical time series.