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Frontiers of Electrical and Electronic Engineering in China 2017年第3期5卷 236-250页

作者： Kai Yuan Ying Zhou Xumin Ni Yuchen Wang Chang Liu Shuhua Xu CAS Key Laboratory of computational biology Max Planck Independent Research Group on Population Genomics CAS-MPG Partner Institute for Computational Biology Shanghai Institutes for Biological Sciences CAS Shanghai 200031 China University of Chinese Academy of Sciences Beijing 100049 China Department of Mathematics School of Science Beijing Jiaotong University Beijing 100044 China School of Life Science and Technology ShanghaiTech University Shanghai 201210 China Collaborative Innovation center of Genetics and Development Shanghai 200438 China

Background： Genetic admixture refers to the process or consequence of interbreeding between two or more previously isolated populations within a species. Compared to many other evolutionary driving forces such as mutations, genetic drift, and natural selection, genetic admixture is a quick mechanism for shaping population genomie diversity. In particular, admixture results in ＂recombination＂ of genetic variants that have been fixed in different populations, which has many evolutionary and medical implications. Results： However, it is challenging to accurately reconstruct population admixture history and to understand of population admixture dynamics. In this review, we provide an overview of models, methods, and tools for ancestry inference and admixture analysis. Conclusions： Many methods and tools used for admixture analysis were originally developed to analyze human data, but these methods can also be directly applied and/or slightly modified to study non-human species as well.

关键词： genetic admixture ancestry population structures demographic history archaic introgression incomplete lineage sorting

Ethiopian vegetation types,climate and topography

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Plant Diversity 2020年第4期42卷 302-311页

作者： Mengesha Asefa Min Cao Yunyun He Ewuketu Mekonnen Xiaoyang Song Jie Yang CAS Key Laboratory of Tropical Forest EcologyXishuangbanna Tropical Botanical GardenChinese Academy of Sciences666303YunnanChina Department of biology College of Natural and Computational SciencesUniversity of Gondar196GondarEthiopia

Ethiopia is land of geographical contrasts with elevations that range from 125 m below sea level in the Danakil Depression to 4533 m above sea level in the Semien Mountains,a world heritage *** diverse climate of various ecological regions of the country has driven the establishment of diverse vegetation,which range from Afroalpine vegetation in the mountains to the arid and semi-arid vegetation type in the *** formation of Ethiopian vegetation is highly connected to the climate and geological history of the *** uplift and rift formation due to volcanic forces formed novel habitats with different topography and climatic conditions that have ultimately become drivers for vegetation *** to Ethiopia's connection with the temperate biome in the north and the Arabian Peninsula during the dry glacial period,the biotic assemblage of Ethiopian highlands consists of both Afrotropical and palearctic *** general,eight distinct vegetation types have been identified in Ethiopia,based mainly on elevation and climate *** vegetation types host their own unique species,but also share several common *** of the vegetation types are identified as centers of endemism and have subsequently been identified globally as the East African Afromontane *** is biologically rich,with more than 6500 vascular plant *** these species,12%are endemic mainly due to geographical isolation and unique climatic ***,researchers have yet to extensively investigate the ecology,phenology,as well as the evolutionary,genetics,and conservation status of Ethiopian vegetations at community and species level over space and *** lack of research is a barrier to achieving the goal of zero global plant *** extinction risk assessment has not been extensively carried out for majority of Ethiopian *** research is needed to explore how vegetation and species respond to rapidly growing envir

关键词： Elevation Biodiversity Climate Ethiopia Vegetation types Topography

High-order accurate solutions of generalized Riemann problems of nonlinear hyperbolic balance laws

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Science China Mathematics 2023年第7期66卷 1609-1648页

作者： Jianzhen Qian Shuanghu Wang Institute of Applied Physics and computational Mathematics Beijing 100094China

We provide a systematic study for the generalized Riemann problem(GRP)of the nonlinear hyperbolic balance law,which is critically concerned with the construction of the spatial-temporally coupled high-order Godunov-type *** full analytical GRP solvers up to the third-order accuracy and also a collection of properties of the GRP solution are derived by resolving the elementary *** resolution of the rarefaction wave is a crucial point,which relies on the use of the generalized characteristic coordinate(GCC)to analyze the solution at the *** the analysis on the GCC,we derive for the general nonlinear system the evolutionary equations for the derivatives of generalized Riemann *** the nonsonic case,the full set of spatial and temporal derivatives of the GRP solution at the singularity are obtained,whereas for the sonic case the limiting directional derivatives inside the rarefaction wave are *** addition,the acoustic approximation of the analytical GRP solver is deduced by estimating the error it *** is shown that the computationally more efficient Toro-Titarev solver can be the approximation of the analytical solver under the suitable *** this work also provides a theoretical basis of the approximate GRP *** theoretical results are illustrated via the examples of the Burgers equation,the shallow water equations and a system for compressible flows under gravity *** results demonstrate the accuracy of the GRP solvers for both weak and strong discontinuity cases.

关键词： nonlinear hyperbolic balance law generalized Riemann problem GRP solver generalized Riemann invariant

Neighborhood Combination Search for Single-Machine Scheduling with Sequence-Dependent Setup Time

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Journal of Computer Science & Technology 2024年第3期39卷 737-752页

作者：刘晓路徐宏云陈嘉铭苏宙行吕志鹏丁俊文 College of System Engineering National University of Defense TechnologyChangsha 410015China School of Artificial Intelligence Jianghan UniversityWuhan 430056China Xi’an Satellite Control center Xi’an 710043China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China CCF

In a local search algorithm,one of its most important features is the definition of its neighborhood which is crucial to the algorithm's *** this paper,we present an analysis of neighborhood combination search for solv-ing the single-machine scheduling problem with sequence-dependent setup time with the objective of minimizing total weighted tardiness(SMSWT).First,We propose a new neighborhood structure named Block Swap(B1)which can be con-sidered as an extension of the previously widely used Block Move(B2)neighborhood,and a fast incremental evaluation technique to enhance its evaluation ***,based on the Block Swap and Block Move neighborhoods,we present two kinds of neighborhood structures:neighborhood union(denoted by B1UB2)and token-ring search(denoted by B1→B2),both of which are combinations of B1 and ***,we incorporate the neighborhood union and token-ring search into two representative metaheuristic algorithms:the Iterated Local Search Algorithm(ILSnew)and the Hybrid evolutionary Algorithm(HEA_(new))to investigate the performance of the neighborhood union and token-ring ***-sive experiments show the competitiveness of the token-ring search combination mechanism of the two *** on the 120 public benchmark instances,our HEA_(new)has a highly competitive performance in solution quality and computational time compared with both the exact algorithms and recent *** have also tested the HEA,new algorithm with the selected neighborhood combination search to deal with the 64 public benchmark instances of the single-machine scheduling problem with sequence-dependent setup *** is able to match the optimal or the best known results for all the 64 *** particular,the computational time for reaching the best well-known results for five chal-lenging instances is reduced by at least 61.25%.

关键词： single-machine scheduling sequence-dependent setup time neighborhood combination search token-ring search hybrid evolutionary algorithm

Possible Impact of Global Warming on the Evolution of Hemagglutinins from Influenza A Viruses

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Biomedical and Environmental Sciences 2011年第1期24卷 62-67页

作者： YAN ShaoMin WU Guang National Engineering Research center for Non-food Biorefinery Guangxi Academy of Sciences Nanning 530007 Guangxi China computational Mutation Project DreamSciTech Consulting Shenzhen 518054 Guangdong China

Objective To determine if global warming has an impact on the evolution of hemagglutinins from influenza A viruses, because both global warming and influenza pandemics/epidemics threaten the world. Methods 4 706 hemagglutinins from influenza A viruses sampled from 1956 to 2009 were converted to a time‐series to show their evolutionary process and compared with the global, northern hemisphere and southern hemisphere temperatures, to determine if their trends run in similar or opposite directions. Point‐to‐point comparisons between temperature and quantified hemagglutinins were performed for all species and for the major prevailing species. Results The comparisons show that the trends for both hemagglutinin evolution and temperature change run in a similar direction. Conclusion Global warming has a consistent and progressive impact on the hemagglutinin evolution of influenza A viruses.

关键词： Evolution Global warming Hemagglutinin Influenza A virus Mutation

Time Complexity of evolutionary Algorithms for Combinatorial Optimization:A Decade of Results

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International Journal of Automation and computing 2007年第3期4卷 281-293页

作者： Pietro S.Oliveto The center of Excellence for Research in computational Intelligence and Applications (CERCIA) School of Computer Science University of BirminghamEdgbastonBirmingham B15 2TTUK

computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems. These efforts produced a deeper understanding of how EAs perform on different kinds of fitness landscapes and general mathematical tools that may be extended to the analysis of more complicated EAs on more realistic problems. In fact, in recent years, it has been possible to analyze the （1＋1）-EA on combinatorial optimization problems with practical applications and more realistic population-based EAs on structured toy problems. This paper presents a survey of the results obtained in the last decade along these two research lines. The most common mathematical techniques are introduced, the basic ideas behind them are discussed and their elective applications are highlighted. Solved problems that were still open are enumerated as are those still awaiting for a solution. New questions and problems arisen in the meantime are also considered.

关键词： evolutionary algorithms computational complexity combinatorial optimization evolutionary computation theory.

Adaptive evolution and ecological speciation between Populus euphratica and ***:evidence from the transcriptome orthologs

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Adaptive evolution and ecological speciation between Populus...

Adaptive candidate estimation-assisted multi-objective particle swarm optimization

后植物志时代的系统与进化植物学——2011年全国系统与进化植物学暨第十届青年学术研讨会

作者： Martin Lascoux Thomas Meagher Laboratory of evolutionary Genomics CAS-MPG Partner Institutefor Computational BiologyChinese Academy of SciencesShanghaiChina Program in evolutionary Functional Genomics Evolutionary Biology CentreUppsala UniversityNorbyvgen18D75326 UppsalaSweden School of biology Mitchell BuildingUniversity of St AndrewsSt AndrewsFife KY16 9THUK

Adaptive evolution and ecological divergences with gene flow were suggested to be common between the closely related species with parapatric *** aimed to test this assumption in two poplar species,Popidus euphratica and ***,which diverged in the recent past in the *** firstly conducted the deep transcriptomic analyses of *** we aligned transcriptomes of this species and *** with the genome sequences of *** and generated orthologous sequence alignments for 5,537 potential *** on the ratio of nonsynonymous to synonymous substitutions, we identified four and six candidate sequences(genes) in *** and *** respectively, exhibiting a signature of strong natural selection(Ka/Ks>1).These genes are involved in stimulus, metabolic and cellular process,immune responses and biological regulations of two species during their ecological adaptation to arid *** then selected 2,383 orthologous sequences with nearly‘neutral’ evolution to examine alternative speciation hypotheses between two *** coalescent tests obviously supported the hypothesis of the ecological speciation with gene flow between two *** findings provides a good example to infer adaptive evolution and speciation history between closely related non-model plant species based on transcriptome data using next-generation sequencing technologies.

关键词： Illumina/Solexa sequencing Populus pruinosa transcriptome adaptive evolution speciation coalescent test

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Science China(Technological Sciences) 2022年第8期65卷 1685-1699页

作者： HAN HongGui ZHANG LinLin HOU Ying QIAO JunFei Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Beijing Key Laboratory of computational Intelligence and Intelligent System Beijing 100124China Engineering Research center of Digital Community Ministry of EducationBeijing 100124China

The selection of global best(Gbest) exerts a high influence on the searching performance of multi-objective particle swarm optimization algorithm(MOPSO). The candidates of MOPSO in external archive are always estimated to select Gbest. However,in most estimation methods, the candidates are considered as the Gbest in a fixed way, which is difficult to adapt to varying evolutionary requirements for balance between convergence and diversity of MOPSO. To deal with this problem, an adaptive candidate estimation-assisted MOPSO(ACE-MOPSO) is proposed in this paper. First, the evolutionary state information,including both the global dominance information and global distribution information of non-dominated solutions, is introduced to describe the evolutionary states to extract the evolutionary requirements. Second, an adaptive candidate estimation method,based on two evaluation distances, is developed to select the excellent leader for balancing convergence and diversity during the dynamic evolutionary process. Third, a leader mutation strategy, using the elite local search(ELS), is devised to select Gbest to improve the searching ability of ACE-MOPSO. Fourth, the convergence analysis is given to prove the theoretical validity of ACE-MOPSO. Finally, this proposed algorithm is compared with popular algorithms on twenty-four benchmark functions. The results demonstrate that ACE-MOPSO has advanced performance in both convergence and diversity.

关键词： multi-objective particle swarm optimization evolutionary state information adaptive candidate estimation convergence and diversity convergence analysis

Micro-coevolution of host genetics with gut microbiome in three Chinese ethnic groups

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Journal of Genetics and Genomics 2021年第11期48卷 972-983页

作者： Mingyue Cheng Xueling Ge Chaofang Zhong Ruiqing Fu Kang Ning Shuhua Xu Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Key Laboratory of Bioinformatics and Molecular-imagingCenter of AI BiologyDepartment of Bioinformatics and Systems BiologyCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of computational biology Shanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China State Key Laboratory of Genetic Engineering Center for Evolutionary BiologyCollaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesFudan UniversityShanghai 200438China School of Life Science and Technology ShanghaiTech UniversityShanghai 201210China center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China Henan Institute of Medical and Pharmaceutical Sciences Zhengzhou UniversityZhengzhou 450052China Human Phenome Institute Fudan UniversityShanghai 201203China

Understanding the micro-coevolution of the human gut microbiome with host genetics is challenging but essential in both evolutionary and medical *** gain insight into the interactions between host genetic variation and the gut microbiome,we analyzed both the human genome and gut microbiome collected from a cohort of 190 students in the same boarding college and representing 3 ethnic groups,Uyghur,Kazakh,and Han *** found that differences in gut microbiome were greater between genetically distinct ethnic groups than those genetically closely related ones in taxonomic composition,functional composition,enterotype stratification,and microbiome genetic *** also observed considerable correlations between host genetic variants and the abundance of a subset of gut microbial ***,interactions between gut microbiome species and host genetic variants might have coordinated effects on specific human *** ovatus,previously reported to modulate intestinal immunity,is significantly correlated with the host genetic variant rs12899811(meta-P=5.55×10^(-5)),which regulates the VPS33B expression in the colon,acting as a tumor suppressor of colorectal *** results advance our understanding of the micro-coevolution of the human gut microbiome and their interactive effects with host genetic variation on phenotypic diversity.

关键词： Micro-coevolution Gut microbiome Host genetics Uyghur Kazakh Han Chines