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Discovery of RNA structural elements using evolutionary computation

NUCLEIC ACIDS RESEARCH 2002年第23期30卷 5310-5317页

作者： Fogel, GB Porto, VW Weekes, DG Fogel, DB Griffey, RH McNeil, JA Lesnik, E Ecker, DJ Sampath, R Nat Select Inc La Jolla CA 92037 USA Ibis Therapeut Carlsbad CA 92008 USA

RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to recur in multiple genes within a single organism or across the same gene in several organisms and provide a common regulatory mechanism. Search algorithms, such as RNAMotif, can be used to mine nucleotide sequence databases for these repeating motifs. RNAMotif allows users to capture essential features of known structures in detailed descriptors and can be used to identify, with high specificity, other similar motifs within the nucleotide database. However, when the descriptor constraints are relaxed to provide more flexibility, or when there is very little a priori information about hypothesized RNA structures, the number of motif 'hits' may become very large. Exhaustive methods to search for similar RNA structures over these large search spaces are likely to be computationally intractable. Here we describe a powerful new algorithm based on evolutionary computation to solve this problem. A series of experiments using ferritin IRE and SRP RNA stem-loop motifs were used to verify the method. We demonstrate that even when searching extremely large search spaces, of the order of 10(23) potential solutions, we could find the correct solution in a fraction of the time it would have taken for exhaustive comparisons.

关键词： .nucleotide sequence descriptors spaces SRP RNA structural elements very large RNA structures evolutionary computation

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Accelerating evolutionary computation using a convergence point estimated by weighted moving vectors

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COMPLEX & INTELLIGENT SYSTEMS 2020年第1期6卷 55-65页

作者： Yu, Jun Li, Yuhao Pei, Yan Takagi, Hideyuki Japan Soc Promot Sci Tokyo Japan Kyushu Univ Grad Sch Design Minami Ku 4-9-1 Shio Batu Fukuoka Japan Univ Aizu Tsuniga Comp Sci Div Ikki Machi Aizu Wakamatsu Fukushima Japan Kyushu Univ Fac Design Minami Ku 4-9-1 Shiobaru Fukuoka Japan

We introduce weighted moving vectors to increase the accuracy of estimating a convergence point of population and evaluate its efficiency. Key point is to weight moving vectors according to their reliability when a convergence point is calculated instead of equal weighting of the original method. We propose two different methods to evaluate the reliability of moving vectors. The first approach uses the fitness gradient information between starting points and terminal points of moving vectors for their weights. When a fitness gradient is bigger, the direction of a moving vector may have more potential, and a higher weight is given to it. The second one uses the fitness of parents, i.e., starting points of moving vectors, to give weights for moving vectors. Because an individual with higher fitness may have a high probability of being close to the optimal area, it should be given a higher weight, vice versa. If the estimated point is better than the worst individual in current population, it is used as an elite individual and replace the worst one to accelerate the convergence of evolutionary algorithms. To evaluate the performance of our proposal, we employ differential evolution and particle swarm optimization as baseline algorithms in our evaluation experiments and run them on 28 benchmark functions from CEC 2013. The experimental results confirmed that introducing weights can further improve the accuracy of an estimated convergence point, which helps to make EC search faster. Finally, some open topics are given to discuss.

关键词： evolutionary computation Estimation of convergence point Acceleration Weight-based estimation

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Software Engineering Meets evolutionary computation

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COMPUTER 2011年第10期44卷 31-39页

作者： Harman, Mark UCL Software Syst Engn Grp London WC1E 6BT England UCL Ctr Res Evolut Search & Testing Dept Comp Sci London WC1E 6BT England

The concept of evolutionary computation has affected virtually every area of software design, not merely as a metaphor, but as a realistic algorithm for exploration, insight, and improvement.

关键词： computation theory evolutionary computation evolutionary computation SBSE Software design Software engineering Software engineering evolutionary computation evolutionary computation realistic algorithm software design software engineering software engineering

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Designing Global Behavior in Multi-Agent Systems Using evolutionary computation

ELEKTROTEHNISKI VESTNIK-ELECTROCHEMICAL REVIEW

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ELEKTROTEHNISKI VESTNIK-ELECTROCHEMICAL REVIEW 2013年第5期80卷 234-239页

作者： Privosnik, Marko Univ Ljubljana Fac Comp & Informat Sci Trzaska 25 Ljubljana 1000 Slovenia

Designing a multi-agent system by specifying individual agents and their local interaction in a way that will give rise to a desired global behavior is a difficult task. In this paper, an approach is presented to designing a global emergent behavior for the heap formation task in a reactive multi-agent system using genetic algorithms. Instead of building a multi-agent system by defining the agents' reaction rules, the system is designed using evolution of the global behavior by genetically operating on single agents while evaluating fitness of the whole system. The research includes examination of scalability of the evolved solutions relative to the number of the agents by cross-testing evolved solutions in different system configurations. It is shown that the evolved solutions perform properly, but scale well only on limited intervals that do not span over a critical point corresponding to the condition where the number of the agents equals the number of the objects.

关键词： multi-agent systems evolutionary computation emergent properties

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Information theory, evolutionary computation, and Dembski's "complex specified information"

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SYNTHESE 2011年第2期178卷 237-270页

作者： Elsberry, Wesley Shallit, Jeffrey Michigan State Univ Lyman Briggs Coll E Lansing MI 48825 USA Natl Ctr Sci Educ Oakland CA 94609 USA Univ Waterloo Sch Comp Sci Waterloo ON N2L 3G1 Canada

Intelligent design advocate William Dembski has introduced a measure of information called "complex specified information", or CSI. He claims that CSI is a reliable marker of design by intelligent agents. He puts forth a "Law of Conservation of Information" which states that chance and natural laws are incapable of generating CSI. In particular, CSI cannot be generated by evolutionary computation. Dembski asserts that CSI is present in intelligent causes and in the flagellum of Escherichia coli, and concludes that neither have natural explanations. In this paper, we examine Dembski's claims, point out significant errors in his reasoning, and conclude that there is no reason to accept his assertions.

关键词： Information theory evolutionary computation Artificial life Pseudomathematics Complex specified information

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Regularized machine learning through constraint swarm and evolutionary computation applied to regression problems

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International Journal of Intelligent Computing and Cybernetics 2014年第4期7卷 346-381页

作者： Ahmad Mozaffari Nasser Lashgarian Azad Alireza Fathi Systems Design Engineering Department University of WaterlooWaterlooCanada Department of Mechanical Engineering University of TechnologyBabolIran

Purpose–The purpose of this paper is to demonstrate the applicability of swarm and evolutionary techniques for regularized machine ***,by defining a proper penalty function,regularization laws are embedded into the structure of common least square solutions to increase the numerical stability,sparsity,accuracy and robustness of regression *** regularization techniques have been proposed so far which have their own advantages and *** efforts have been made to find fast and accurate deterministic solvers to handle those regularization ***,the proposed numerical and deterministic approaches need certain knowledge of mathematical programming,and also do not guarantee the global optimality of the obtained *** this research,the authors propose the use of constraint swarm and evolutionary techniques to cope with demanding requirements of regularized extreme learning machine(ELM).Design/methodology/approach–To implement the required tools for comparative numerical study,three steps are *** considered algorithms contain both classical and swarm and evolutionary *** the classical regularization techniques,Lasso regularization,Tikhonov regularization,cascade Lasso-Tikhonov regularization,and elastic net are *** swarm and evolutionary-based regularization,an efficient constraint handling technique known as self-adaptive penalty function constraint handling is considered,and its algorithmic structure is modified so that it can efficiently perform the regularized *** well-known metaheuristics are considered to check the generalization capability of the proposed *** test the efficacy of the proposed constraint evolutionary-based regularization technique,a wide range of regression problems are ***,the proposed framework is applied to a real-life identification problem,*** the dominant factors affecting the hydrocarbon emissions of an automotive eng

关键词： evolutionary computation Function approximation Hybrid systems

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Modelling and forecasting the heterogeneous distribution of picocyanobacteria in the tropical Lajes Reservoir (Brazil) by evolutionary computation

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HYDROBIOLOGIA 2015年第1期749卷 53-67页

作者： Recknagel, Friedrich Castelo Branco, Christina W. Cao, Hongqing Huszar, Vera L. M. Sousa-Filho, Izidro F. Univ Adelaide Sch Biol Sci Adelaide SA Australia Univ Fed Estado Rio de Janeiro Inst Biociencias Rio De Janeiro Brazil Univ Fed Rio de Janeiro Museu Nacl Rio De Janeiro Brazil

Five years of water quality data from six stations across the mesotrophic and oligomictic Lajes Reservoir (Brazil) were utilized to develop 7-day ahead forecasting models for the picocyanobacteria Cyanodictyon imperfectum, Cyanogranis ferruginea and Synechococcus sp. by means of the hybrid evolutionary algorithm HEA. The data included physical and chemical water quality parameters as well as abundance data of the three picocyanobacteria. Models based on site-specific data of six monitoring stations forecasted population dynamics of Synechococcus with coefficients of determination (r (2)) between 0.58 for and 0.88, of Cyanodictyon with r (2) between 0.5 and 0.89 and of Cyanogranis with r (2) between 0.53 and 0.77. Despite phosphorus limiting conditions the sensitivity analysis revealed that the three picocyanobacteria responded much stronger to nitrate rather than to phosphate concentrations throughout the Lajes Reservoir suggesting that cyanobacteria may have adopted the sulphur-for-phosphorus strategy by utilizing sulfolipids instead. Cyanogranis displayed a negative relationship with increasing water temperature indicating its higher competitiveness at internal nutrient supply and low light levels during winter turnover. The resulting models will inform operational intervention and prevention of fast growth and dispersal of picocyanobacteria in Lajes Reservoir, and reveal environmental thresholds for outbreaks of such events.

关键词： Spatial heterogeneity Picocyanobacteria evolutionary computation

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Artificial evolutionary intelligence (AEI): evolutionary computation evolves with large language models

JOURNAL OF MEMBRANE COMPUTING

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JOURNAL OF MEMBRANE COMPUTING 2024年 1-18页

作者： He, Cheng Tian, Ye Lu, Zhichao Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Hubei Peoples R China Anhui Univ Inst Phys Sci & Informat Technol Hefei 230601 Anhui Peoples R China City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China

Deep learning (DL) and evolutionary computation (EC), two main branches of artificial intelligence, have attracted attention in a far different way over the past decades. On the one hand, the DL area focuses on recognizing data patterns for simulating the human brain's complex decision-making power, which has witnessed the boosting of large language models (LLMs). LLMs have shown inspiring adeptness at mastering many multimodal tasks, thanks to the big data for pre-training, the large-sized architecture for learning, and the tailored optimization strategies for fine-tuning. On the other hand, the EC community paid more attention to solving complex computational tasks, aiming to extend the global search capability of meta-heuristic methods by mimicking natural biological evolution. Nevertheless, the development of EC in real-world scenarios is far from satisfactory compared with DL;even the EC itself is seldom used in the optimization tasks within DL/LLMs. This paper provides a look at the future of EC from the perspective of artificial evolutionary intelligence (AEI), i.e., the cooperative evolution of EC and artificial general intelligence with the assistance of LLMs. A paradigm of LLM for EC has been discussed to provide some potential research topics for the interdisciplinary between optimization and learning. Specifically, three main issues of LLMs are considered for AEI, i.e., the multi-modal representation capability for encoding, reproduction, and selection, a general model for versatile learning such as surrogate, dimensionality reduction, configuration, recommendation, and generative models, and the ability to understand EC in terms of the EC concepts, EC codes, and EC behaviors. Furthermore, an open-source platform has been realized, which is expected to promote research in AEI and its applications.

关键词： evolutionary computation Large language model Optimization Learning Decision-making

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Thermal degradation of carbohydrates, proteins and lipids in microalgae analyzed by evolutionary computation

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ENERGY CONVERSION AND MANAGEMENT 2018年 160卷 209-219页

作者： Chen, Wei-Hsin Chu, Yen-Shih Liu, Jenn-Long Chang, Jo-Shu Natl Cheng Kung Univ Dept Aeronaut & Astronaut Tainan 701 Taiwan Natl Cheng Kung Univ Res Ctr Energy Technol & Strategy Tainan 701 Taiwan I Shou Univ Dept Informat Management Kaohsiung 840 Taiwan Natl Cheng Kung Univ Dept Chem Engn Tainan 701 Taiwan

The kinetics of microalgae pyrolysis is investigated to analyze the thermal degradation of carbohydrates, proteins and lipids in different species of microalgae. The pyrolysis processes of microalgae Chlorella vulgaris ESP-31, Nannochioropsis oceanica CY2, and Chlamydomonas sp. JSC4 are examined by thermogravimetric analysis (TGA), and independent parallel reaction (IPR) model is adopted to approach the pyrolysis kinetics. To maximize the fit quality between the established kinetic models and experimental data, particle swarm optimization (PSO), a kind of evolutionary computation, is employed. The thermal degradation characteristics of the three microalgal species are compared with each other. The results suggest that the thermal degradation curves of the three microalgae can be predicted with a fit quality of at least 97.9%. The activation energies of carbohydrates, proteins, and lipids in the microalgae are in the ranges of 53.28-53.30, 142.61-188.35, and 40.21-59.23 kJ mol(-1), respectively, while the thermal degradation of carbohydrates, proteins, and lipids are in temperature ranges of 164-497, 209-309, and 200-635 degrees C, respectively. It is proved in this work that the IPR model and the calculation of the PSO can be used to predict the pyrolysis kinetics of microalgae to a good level of fitness.

关键词： Biomass and microalgae Thermal degradation temperature Pyrolysis Particle swarm optimization (PSO) evolutionary computation TGA and kinetics

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Evolvable hardware - Using evolutionary computation to design and optimize hardware systems

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IEEE computationAL INTELLIGENCE MAGAZINE 2006年第1期1卷 19-27页

作者： Lohn, Jason D. Hornby, Gregory S. NASA Ames Res Ctr Moffett Field CA 94035 USA

Evolvable hardware lies at the intersection of evolutionary computation and physical design. Through the use of evolutionary computation methods, the field seeks to develop a variety of technologies that enable automatic design, adaptation, and reconfiguration of electrical and mechanical hardware systems in ways that outperform conventional techniques. This article surveys evolvable hardware with emphasis on some of the latest developments, many of which deliver performance exceeding traditional methods. As such, the field of evolvable hardware is just now starting to emerge from the research laboratory and into mainstream hardware applications.

关键词： Hardware evolutionary computation Design optimization Algorithm design and analysis Application software Genetic algorithms Field programmable gate arrays Automatic control Optical control Optical arrays

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