Learning Causal Biological Networks with Parallel Ant Colony Optimization Algorithm

A wealth of causal relationships exists in biological systems, both causal brain networks and causal protein signaling networks are very classical causal biological networks (CBNs). Learning CBNs from biological signal data reliably is a critical problem today. However, most of the existing methods are not excellent enough in terms of accuracy and time performance, and tend to fall into local optima because they do not take full advantage of global information. In this paper, we propose a parallel ant colony optimization algorithm to learn causal biological networks from biological signal data, called PACO. Specifically, PACO first maps the construction of CBNs to ants, then searches for CBNs in parallel by simulating multiple groups of ants foraging, and finally obtains the optimal CBN through pheromone fusion and CBNs fusion between different ant colonies. Extensive experimental results on simulation data sets as well as two real-world data sets, the fMRI signal data set and the Single-cell data set, show that PACO can accurately and efficiently learn CBNs from biological signal data

Water sources effects on soil salinity and biomass production of agriculture and agroforest systems in raised fields

This study investigates the sources of water under four modes, namely, normal fields, Raised Fields, single agriculture in Raised Fields, and agroforest system in Raised Fields, by using a combination of δ18O, δ2H and δ13C and their effects on crop yield and water use efficiency. The results show that the soil electrical conductivity of Raised Fields during summer maize seasons was lower than that during winter wheat seasons, and that in the marginal regions was higher than in the central regions, because of the Water Sources. Under agroforest conditions in Raised Fields, Soil Salinity can be reduced because approximately 10% of the water originates from tree trunks. The biomass yield and intrinsic water use efficiency of winter crops under agroforest was 15.1% and 5.5% higher than that under single agriculture, respectively. Thus, soil salinization can be reduced and productivity can be increased by controlling the Water Sources in ecosystems