Learning to Count Isomorphisms with Graph Neural Networks

Subgraph isomorphism counting is an important problem on graphs, as many graph-based tasks exploit recurring subgraph patterns. Classical methods usually boil down to a backtracking framework that needs to navigate a huge search space with prohibitive computational costs. Some recent studies resort to graph neural networks (GNNs) to learn a low-dimensional representation for both the query and input graphs, in order to predict the number of subgraph isomorphisms on the input graph. However, typical GNNs employ a node-centric message passing scheme that receives and aggregates messages on nodes, which is inadequate in complex structure matching for isomorphism counting. Moreover, on an input graph, the space of possible query graphs is enormous, and different parts of the input graph will be triggered to match different queries. Thus, expecting a fixed representation of the input graph to match diversely structured query graphs is unrealistic. In this paper, we propose a novel GNN called Count-GNN for subgraph isomorphism counting, to deal with the above challenges. At the edge level, given that an edge is an atomic unit of encoding graph structures, we propose an edge-centric message passing scheme, where messages on edges are propagated and aggregated based on the edge adjacency to preserve fine-grained structural information. At the graph level, we modulate the input graph representation conditioned on the query, so that the input graph can be adapted to each query individually to improve their matching. Finally, we conduct extensive experiments on a number of benchmark datasets to demonstrate the superior performance of Count-GNN.Comment: AAAI-23 main trac

Towards locality-aware meta-learning of tail node embeddings on networks

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Identification of a laccase Glac15 from Ganoderma lucidum 77002 and its application in bioethanol production

Background Laccases have potential applications in detoxification of lignocellulosic biomass after thermochemical pretreatment and production of value-added products or biofuels from renewable biomass. However, their application in large-scale industrial and environmental processes has been severely thwarted by the high cost of commercial laccases. Therefore, it is necessary to identify new laccases with lower cost but higher activity to detoxify lignocellulosic hydrolysates and better efficiency to produce biofuels such as bioethanol. Laccases from Ganoderma lucidum represent proper candidates in processing of lignocellulosic biomass. Results G. lucidum 77002 produces three laccase isoenzymes with a total laccase activity of 141.1 U/mL within 6 days when using wheat bran and peanut powder as energy sources in liquid culture medium. A new isoenzyme named Glac15 was identified, purified, and characterized. Glac15 possesses an optimum pH of 4.5 to 5.0 and a temperature range of 45°C to 55°C for the substrates tested. It was stable at pH values ranging from 5.0 to 7.0 and temperatures lower than 55°C, with more than 80% activity retained after incubation for 2 h. When used in bioethanol production process, 0.05 U/mL Glac15 removed 84% of the phenolic compounds in prehydrolysate, and the yeast biomass reached 11.81 (optimal density at 600 nm (OD600)), compared to no growth in the untreated one. Addition of Glac15 before cellulase hydrolysis had no significant effect on glucose recovery. However, ethanol yield were improved in samples treated with laccases compared to that in control samples. The final ethanol concentration of 9.74, 10.05, 10.11, and 10.81 g/L were obtained from samples containing only solid content, solid content treated with Glac15, solid content containing 50% prehydrolysate, and solid content containing 50% prehydrolysate treated with Glac15, respectively. Conclusions The G. lucidum laccase Glac15 has potentials in bioethanol production industry

The GARP/MYB-related grape transcription factor AQUILO improves cold tolerance and promotes the accumulation of raffinose family oligosaccharides

Grapevine (Vitis vinifera L.) is a widely cultivated fruit crop whose growth and productivity are greatly affected by low temperatures. On the other hand, wild Vitis species represent valuable genetic resources of natural stress tolerance. We have isolated and characterized a MYB-like gene encoding a putative GARP-type transcription factor from Amur grape (V. amurensis) designated as VaAQUILO. AQUILO (AQ) is induced by cold in both V. amurensis and V. vinifera, and its overexpression results in significantly improved tolerance to cold both in transgenic Arabidopsis and in Amur grape calli. In Arabidopsis, the ectopic expression of VaAQ increased antioxidant enzyme activities and up-regulated reactive oxygen species- (ROS) scavenging-related genes. Comparative mRNA sequencing profiling of 35S:VaAQ Arabidopsis plants suggests that this transcription factor is related to phosphate homeostasis like their Arabidopsis closest homologues: AtHRS1 and AtHHO2. However, when a cold stress is imposed, AQ is tightly associated with the cold-responsive pathway and with the raffinose family oligosaccharides (RFOs), as observed by the up-regulation of galactinol synthase (GoLS) and raffinose synthase genes. Gene co-expression network (GCN) and cis-regulatory element (CRE) analyses in grapevine indicated AQ as potentially regulating VvGoLS genes. Increased RFO content was confirmed in both transgenic Arabidopsis and Amur grape calli overexpressing VaAQ. Taken together, our results imply that AQ improves cold tolerance through promoting the accumulation of osmoprotectants.This work was supported by the Youth Innovation Promotion Association of CAS (2015281), project funded by the China Postdoctoral Science Foundation (2016M601166), Science and Technology Service Network Initiative of CAS (KFJ-STS-ZDTP-025), and Grape Breeding Project of Ningxia (NXNYYZ201502)

The GARP/MYB-related grape transcription factor AQUILO improves cold tolerance and promotes the accumulation of raffinose family oligosaccharides

Grapevine (Vitis vinifera L.) is a widely cultivated fruit crop whose growth and productivity are greatly affected by low temperatures. On the other hand, wild Vitis species represent valuable genetic resources of natural stress tolerance. We have isolated and characterized a MYB-like gene encoding a putative GARP-type transcription factor from Amur grape (V. amurensis) designated as VaAQUILO. AQUILO (AQ) is induced by cold in both V. amurensis and V. vinifera, and its overexpression results in significantly improved tolerance to cold both in transgenic Arabidopsis and in Amur grape calli. In Arabidopsis, the ectopic expression of VaAQ increased antioxidant enzyme activities and up-regulated reactive oxygen species- (ROS) scavenging-related genes. Comparative mRNA sequencing profiling of 35S:VaAQ Arabidopsis plants suggests that this transcription factor is related to phosphate homeostasis like their Arabidopsis closest homologues: AtHRS1 and AtHHO2. However, when a cold stress is imposed, AQ is tightly associated with the cold-responsive pathway and with the raffinose family oligosaccharides (RFOs), as observed by the up-regulation of galactinol synthase (GoLS) and raffinose synthase genes. Gene co-expression network (GCN) and cis-regulatory element (CRE) analyses in grapevine indicated AQ as potentially regulating VvGoLS genes. Increased RFO content was confirmed in both transgenic Arabidopsis and Amur grape calli overexpressing VaAQ. Taken together, our results imply that AQ improves cold tolerance through promoting the accumulation of osmoprotectants

Meta-inductive node classification across graphs

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