Improved Membrane Algorithm Under the Framework of P Systems to Solve Multimodal Multiobjective Problems

Multimodal multiobjective problems (MMOPs) exist in scientific research and practical projects, and their Pareto solution sets correspond to the same Pareto front. Existing evolutionary algorithms often fall into local optima when solving such problems, which usually leads to insufficient search solutions and their uneven distribution in the Pareto front. In this work, an improved membrane algorithm is proposed for solving MMOPs, which is based on the framework of P system. More specifically, the proposed algorithm employs three elements from P system: object, reaction rule, and membrane structure. The object is implemented by real number coding and represents a candidate solution to the optimization problem to be solved. The function of the reaction rule of the proposed algorithm is similar to the evolution operation of the evolutionary algorithm. It can evolve the object to obtain a better candidate solution set. The membrane structure is the evolutionary logic of the proposed algorithm. It consists of several membranes, each of which is an independent evolutionary unit. This structure is used to maintain the diversity of objects, so that it provides multiple Pareto sets as output. The effectiveness verification study was carried out in simulation experiments. The simulation results show that compared with other experimental algorithms, the proposed algorithm has a competitive advantage in solving all 22 multimodal benchmark test problems in CEC2019.

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Reaction rule-extended Linear Code is an unambiguous representation for describing glycosylation reactions in both literature and code.

Ab initio study of the mechanism of formation of a spiro-Sn-heterocyclic ring compound by the cycloaddition reaction of H2C=Sn: and ethylene

X2C=Sn: (X = H, Me, F, Cl, Br, Ph, Ar?) are new species of chemistry. The cycloaddition reactions of X2C=Sn: is a new study field of stannylene chemistry. The mechanism of cycloaddition reaction of singlet H2C=Sn: with ethylene is studied for the first time using the MP2/GENECP (C, H in 6-311++G**; Sn in LanL2dz) method in this paper. From the potential energy profile, it could be predicted that the reaction has one dominant reaction channel. The reaction rule presented is that the 5p unoccupied orbital of tin in H2C=Sn: sidewise overlaps with the bonding ? orbital of ethylene resulting in the formation of an intermediate. The instability of the intermediate makes it isomerise to a four-membered ring stannylene. As the 5p unoccupied orbital of the Sn atom in the four-membered ring stannylene and the ? orbital of ethylene form a ??p donor?acceptor bond, the four-membered ring stannylene further combines with ethylene to form another intermediate, and this intermediate further isomerises to a spiro-Sn-heterocyclic ring compound. The Sn in the spiro-Sn-heterocyclic ring compound is combined with adjacent atoms by sp3 hybridization. The results of this study reveal the mechanism of cycloaddition reaction of X2C=Sn: with symmetric ?-bond compounds.

Predicting Novel Metabolic Pathways through Subgraph Mining

The ability to predict pathways for biosynthesis of metabolites is very important in metabolic engineering. It is possible to mine the repertoire of biochemical transformations from reaction databases, and apply the knowledge to predict reactions to synthesize new molecules. However, this usually involves a careful understanding of the mechanism and the knowledge of the exact bonds being created and broken. There is clearly a need for a method to rapidly predict reactions for synthesizing new molecules, which relies only on the structures of the molecules, without demanding additional information such as thermodynamics or hand-curated information such as atom-atom mapping, which are often hard to obtain accurately.We here describe a robust method based on subgraph mining, to predict a series of biochemical transformations, which can convert between two (even previously unseen) molecules. We first describe a reliable method based on subgraph edit distance to map reactants and products, using only their chemical structures. Having mapped reactants and products, we identify the reaction centre and its neighbourhood, the reaction signature, and store this in a reaction rule network. This novel representation enables us to rapidly predict pathways, even between previously unseen molecules. We also propose a heuristic that predominantly recovers natural biosynthetic pathways from amongst hundreds of possible alternatives, through a directed search of the reaction rule network, enabling us to provide a reliable ranking of the different pathways. Our approach scales well, even to databases with > 100,000 reactions. A Java-based implementation of our algorithms is available at https://github.com/RamanLab/ReactionMinerCCS CONCEPTS•Information systems →Data mining; •Applied computing →Bioinformatics;

Ab initio study of the mechanism of forming a spiro-Si-heterocyclic ring compound involving Ge from H2Ge=Si: and acetaldehyde

The H2Ge=Si: and its derivatives(X2Ge=Si:, X = H, Me, F, Cl, Br, Ph, Ar??) is a new species. Its cycloaddition reactions is a new area for the study of silylene chemistry. The mechanism of the cycloaddition reaction between singlet H2Ge=Si: and acetaldehyde has been investigated with MP2/6-311++G** method, From the potential energy profile, it can be predicted that the reaction has a dominant reaction pathway. The reaction rule presented is that the two reactants firstly form a four-membered Ge-heterocyclic ring silylene through the [2+2] cycloaddition reaction. Because of the 3p unoccupied orbital of Si: atom in the four-membered Ge-heterocyclic ring silylene and the ? orbital of acetaldehyde form a ??p donor-acceptor bond, the four-membered Ge-heterocyclic ring silylene further combines with acetaldehyde to form an intermediate. Then the intermediate isomerizes to a spiro-Si-heterocyclic ring compound involving Ge via a transition state.

Rules Capturing Events and Reactivity

Event-driven reactive functionalities are urgently needed in present-day distributed systems and dynamic Web-based environments. Reaction rules constitute a promising approach to specify and program such reactive systems in a declarative manner. In particular, they provide the ability to reason over events, actions and their effects, and allow detecting events and responding to them automatically. Various reaction rule approaches have been developed, which for the most part have been advanced separately, hence led to different views and terminologies. This chapter surveys and classifies the wide variety of rule-based calculi approaches, engines and languages for event, action and state processing, and describes their main features. Founded on the original formalisms, major lines of development are traced to the present and extrapolated to the future.