基于遗传算法的蛋白质结构预测方法

遗传算法源于自然界的进化规律,是一种自适应启发式概率性迭代式全局搜索算法。本文主要介绍了GA的基本原理,算法及优点;总结GA在蛋白质结构预测中建立模型和执行策略,以及多种算法相互结合预测蛋白质结构的研究进展。     

南海北部近海竹荚鱼栖息地分布特征

根据2014—2017年南海北部近海渔业资源调查的8个航次数据,结合遥感影像数据,包括海表温、盐度、叶绿素,对近海竹荚鱼空间分布的季节性变化进行分析。将单位捕捞努力量渔获量(catch per unit effort,CPUE)作为适宜性指数(suitability index,SI),分别采用最大值法、最小值法、算术平均法、几何平均法按季度建立栖息地适宜性指数(habitat suitability index,HSI)模型,并对各模型进行精度检验。结果表明:SI模型拟合准确,均呈单峰分布;几何平均法更适用各季HSI建模,模型平均准确度达到92%,CPUE高的渔场主要分布于HSI大于0.6的海域,其他HSI高值海域为潜在渔场。对各季环境因子进行主成分分析,发现海表温的影响最为显著。研究表明,栖息地适宜性指数模型可较好分析南海北部近海竹荚鱼资源丰度及空间分布。     

遗传算法在蛋白质结构预测中的应用

遗传算法(geneticalgorithm,GA)作为一种自适应启发式概率性迭代式全局搜索算法,具有不依赖于问题模型的特性、全局最优性、隐含并行性、高效性、解决不同非线性问题的鲁棒性特点,目前已经广泛应用于自动控制、机器人学、计算机科学、模式识别、模糊人工神经和工程优化等设计领域。本文首先介绍了GA的基本原理,即搜索的基本过程;随后总结了GA与传统算法相比所具有的优点;第三部分则分别综述了GA在蛋白质结构预测中主要使用的模型、设计和执行策略,以及使用GA与其他算法相互结合预测蛋白质结构的研究进展;最后提出了作者对GA研究中存在问题的认识和研究展望。     

马鞍列岛褐菖鲉Sebasticus marmoratus栖息地适宜性评价

为了评估趋礁鱼类在岛礁海域的生境适宜度,选取马鞍列岛的褐菖鲉(Sebasticus marmoratus)为指示物种,以2009年获取的水深、盐度、叶绿素a、浊度和底质数据作为褐菖鲉春、冬季栖息地指示因子,建立栖息地适宜度曲线,并计算各站点的栖息地适宜性指数(HSI)。结果显示:1)绿华、花鸟、嵊山沿岸站点HSI普遍较低,枸杞岛、三横山、东库山沿岸站点褐菖鲉HSI相对较高,其中最大值1.0出现在枸杞岛沿岸的站点;2)春季褐菖鲉幼鱼的适宜水深在6 m左右,成鱼适宜在8—12 m的水深处生存;冬季褐菖鲉对8—12 m的水深适宜性良好;3)春季所有褐菖鲉的适宜盐度为30PSU,冬季幼鱼的适宜盐度为27—31PSU,成鱼的适宜盐度为27PSU、31PSU;4)随着叶绿素a和浊度值的增大,褐菖鲉适宜性逐渐降低。底质类型为岩时最适合褐菖鲉生存。5)相关分析显示,褐菖鲉丰度与底质类型相关性最大,而与叶绿素a、浊度呈显著负相关。研究结果表明,初级生产力和浑浊程度越高对褐菖鲉丰度抑制越明显。底质类型是褐菖鲉丰度分布的重要影响因子,其中分布有较多大型海藻的岩礁生境是其最适宜的栖息地。利用2010年春、冬季环境调查和渔获数据进行HSI模型验证,资源丰度随HSI值升高而增加,因此构建的模型可用于趋礁鱼类在岛礁海域的栖息地适宜性分析。     

中西太平洋鲣鱼围网渔业资源的热点分析和空间异质性

中西太平洋是世界鲣鱼围网主要作业水域。基于我国渔船2005—2009年的中西太平洋鲣鱼围网生产数据,运用空间统计方法对该水域鲣鱼资源的空间自相关性和空间异质性特征进行分析,并结合海洋环境特征分析资源分布的热点区域。(1)通过常规统计学计算获得鲣鱼资源的偏态Sk、峰态数Ku、变异值Cv、s2/m和全局空间自相关Geary c系数,发现中西太平洋鲣鱼资源总体上是以低密度区域为主,高密度区域较少;鱼类资源密度值差异较大,资源表现出强烈集聚分布,总体的空间自相关性中等偏弱。(2)通过局部空间自相关的热点分析方法计算,发现局部空间自相关性较强,存在多个在统计学上通过显著性检验的资源热点和冷点。(3)通过地统计方法研究鲣鱼资源的空间变异性特征和方向变异时,空间自相关类型上最优模型是球形模型,鲣鱼资源密度各向同性,最大相关距离1000km左右。发现空间自相关引起的差异占整个差异的50%左右,为中等强度变异;在方向性变异上,主要体现在南北向上,其该向上结构性误差占67%,而东西向结构性误差占49%。这一结果和海洋环境的南北向上结构性远好于东西向结构性有关;从各方向的分维数看,数值介于1.876—1.9之间,数值较大,空间自相关较弱。(4)以资源热点区域作为区域性渔场,结合海洋温度和叶绿素场海洋环境特征,将中西太平洋鲣鱼资源分为3个不同的局部渔场,即2个暖池渔场,1个冷舌渔场。冷舌渔场由中东太平洋赤道上升流引起,在锋面地带提供了较为丰富的初级生产力,便于鱼类获得丰富的食物;暖池渔场靠近岛屿和陆地区域,近岸上升流系统提供了丰富的初级生产力。(5)将热点分析和渔场重心方法及栖息地指数的优缺点做了对比,建议以后采用空间残差模型深入研究空间自相关问题。     

中东大西洋中部海域中上层鱼类中心渔场的时空变化

根据2012年1—8月和2014年12月—2015年7月中国大型拖网渔船在中东大西洋中部海域佛得角海岸(FAO34渔区3.11小区)的渔捞日志资料以及遥感获取的海洋环境数据,利用产量重心法、地统计插值、数理统计、广义加性模型(generalized additive models,GAM)等方法 ,对该海域中上层鱼类平均单位捕捞努力渔获量(CPUE)的月变化、中心渔场的时空变动及其与海表温度(SST)、叶绿素a浓度、经度、纬度的关系进行了分析。结果表明:该海域各月平均CPUE基本呈先减少、后增加的趋势;中心渔场的分布具有明显的月变化,基本呈先由北往南推移,且在3—4月份到达最南端,后由南往北推移趋势;不同月份渔场中心叶绿素a浓度为0~10 mg·m-3,且渔场中心叶绿素a浓度以7~9 mg·m~(-3)居多;不同月份渔场中心的SST为17.3~27.6℃,且渔场中心的SST以19~21℃居多。GAM模型分析表明,渔场的最适SST为20~22℃,最适叶绿素a浓度为4.480~7.388 mg·m~(-3),经度集中在16°40'W附近,纬度集中在19°N附近。海洋环境与CPUE的回归方程显著性检验表明,除了SST呈不显著外,叶绿素a浓度和空间因子与CPUE的回归关系均极显著(P0.01),影响渔场的因子按重要性从大到小依次为经度、纬度、叶绿素a浓度和SST。分析认为,洋流产生并导致的涌升流的位置变化对佛得角海岸FAO34渔区3.11小区中心渔场的时空变化具有重要影响。     

闽南-台湾浅滩渔场二长棘鲷群体景观多样性

根据1998年7月到2000年6月闽南-台湾浅滩渔场开展二长棘鲷资源的专项调查资料,以各个渔区CPUE(Catch Per Unit Effort)及其到渔场重心距离为参数,构建基于渔场重心动能的景观要素,运用景观多样性,并结合因子分析,分析了二长棘鲷群体景观多样性的空间格局及其与海洋环境因子之间的关系,探究了种群空间分布格局与生态过程之间的相互作用关系,旨在揭示闽南-台湾浅滩渔场二长棘鲷的生态境况及空间变异特征,为从生态水平上合理综合利用二长棘鲷渔业资源提供新的依据。结果表明:(1)不同月份鱼群的分布特征差别明显,8月鱼群分布范围最广,11月鱼群分布最为均匀,2月和12月鱼群分布最集中,而9月鱼群占据渔场空间能力最强;(2)不同群体之间具有不同分布特征,生殖群体分布范围最小,且最集中,其占据渔场空间能力最弱,幼鱼群体分布范围小,且相对均匀,其占据渔场空间能力强,索饵群体分布范围最广,且较均匀,鱼群分散索饵,其占据渔场空间能力最强,而9—11月群体平均分布范围较广,且最均匀,其占据渔场空间能力较弱;(3)鱼群综合景观指数是具空间结构的CPUE指数,从生态水平上反映了鱼群CPUE,其排名依次为8月、6月、7月、9月、10月、11月、5月、1月、4月、3月、2月、12月;(4)多样性指数、均匀度指数和优势度指数指示的生态学意义分别为鱼群的分布范围、均匀程度和鱼群空间竞争能力,其中多样性指数和均匀度指数呈正相关;(5)水温是影响鱼群景观均匀度的主要因子,索饵是增加鱼群景观多样性和优势度的主要因子,而生殖因子则降低鱼群景观多样性和优势度,水温、索饵和生殖是二长棘鲷群体景观格局变化的主要驱动因素。     

改进GA-SVM在冠状动脉疾病诊断中的应用

改进的遗传算法（GA）自动优化支持向量机（SVM）参数,同步决策最优特征子集。新颖的分组多基因交叉技术保留了基因小组中的信息,而且允许后代继承更多的来自染色体的遗传信息。该算法促进可行解集中的高质量染色体信息交换,提高了解空间的搜索能力。实验结果说明：改进GA-SVM不仅可决策出与疾病相关的重要特征变量、优化SVM参数,而且可提升分类性能。与前馈BP神经网络及自适应模糊推理系统两种学习算法的比较表明,改进GA-SVM具有更好地表现。     

基于地理加权模型的南设得兰群岛北部南极磷虾渔场空间分布影响分析

结合南极磷虾渔业科学观察员收集的渔业数据和海洋环境数据,本研究利用地理加权回归模型(GWR),分析了具有空间属性的虾群深度和离岸距离两个因子,以及海水表温对南设得兰群岛北侧水域南极磷虾渔场空间分布的影响.结果表明:各年南极磷虾渔业单位捕捞努力量渔获量(CPUE)在空间上的分布无显著的集聚性;2010和2013年,3个因子之间存在空间自相关性(正相关),而2012和2016年则无自相关性.GWR模型结果显示,3个因子对CPUE的空间分布具有不同程度的影响,影响程度大小依次为虾群深度>离岸距离>温度.拟合结果发现,南设得兰群岛东、西两侧水域中表温对CPUE空间分布的影响与其他两个因子具有相反的趋势.虾群深度和离岸距离对CPUE的空间效应主要表现为负相关,但存在着年际和区域性差异.本研究结果可为南极磷虾渔场形成机制研究提供方法上的参考.     

长江口棘头梅童鱼幼鱼栖息地的初步评估

为了评估鱼类对长江口栖息地的选择偏好,选取长江口春季的优势种棘头梅童鱼幼鱼为模式物种,从19个水文、水质因子及生物因素指标中,筛选出狭额绒螯蟹丰度、盐度、底质类型和水深4个因子作为棘头梅童鱼栖息地指示因子,建立栖息地适合曲线,并计算了栖息地适宜度指数(HSI).结果表明: 长江口北支水域棘头梅童鱼幼鱼HSI普遍较高,基本在0.5以上,而南支水域普遍较低,基本上在0.2以下,表明长江口北支为棘头梅童鱼幼鱼的主要索饵场,同时发现,其幼鱼的最适生长水域为盐度大于14、底质平均粒径在29 μm以下、水深2~5 m的水域,与HSI的空间分布一致.生物因子可较好地表征棘头梅童鱼幼鱼对水文、水质等因素的响应;化学需氧量、铵氮、总磷和挥发性酚与棘头梅童鱼幼鱼丰度不具有显著相关性,亚硝酸盐氮、硝酸盐氮和总氮与其丰度具有显著正相关性,说明调查水域内水质的富营养化尚未对棘头梅童鱼栖息地造成破坏;而铜离子和镉离子浓度与其丰度具有极显著的负相关性,表明重金属污染已经对棘头梅童鱼幼鱼的生长和分布造成了一定的危害,推测重金属污染对长江口水域的鱼类栖息地分布具有限制性影响.     

Variability of Suitable Habitat of Western Winter-Spring Cohort for Neon Flying Squid in the Northwest Pacific under Anomalous Environments

We developed a habitat suitability index (HSI) model to evaluate the variability of suitable habitat for neon flying squid (Ommastrephes bartramii) under anomalous environments in the Northwest Pacific Ocean. Commercial fisheries data from the Chinese squid-jigging vessels on the traditional fishing ground bounded by 35°-45°N and 150°-175°E from July to November during 1998-2009 were used for analyses, as well as the environmental variables including sea surface temperature (SST), chlorophyll-a (Chl-a) concentration, sea surface height anomaly (SSHA) and sea surface salinity (SSS). Two empirical HSI models (arithmetic mean model, AMM; geometric mean model, GMM) were established according to the frequency distribution of fishing efforts. The AMM model was found to perform better than the GMM model. The AMM-based HSI model was further validated by the fishery and environmental data in 2010. The predicted HSI values in 1998 (high catch), 2008 (average catch) and 2009 (low catch) indicated that the squid habitat quality was strongly associated with the ENSO-induced variability in the oceanic conditions on the fishing ground. The La Niña events in 1998 tended to yield warm SST and favorable range of Chl-a concentration and SSHA, resulting in high-quality habitats for O. bartramii. While the fishing ground in the El Niño year of 2009 experienced anomalous cool waters and unfavorable range of Chl-a concentration and SSHA, leading to relatively low-quality squid habitats. Our findings suggest that the La Niña event in 1998 tended to result in more favorable habitats for O. bartramii in the Northwest Pacific with the gravity centers of fishing efforts falling within the defined suitable habitat and yielding high squid catch; whereas the El Niño event in 2009 yielded less favorable habitat areas with the fishing effort distribution mismatching the suitable habitat and a dramatic decline of the catch of O. bartramii. This study might provide some potentially valuable insights into exploring the relationship between the underlying squid habitat and the inter-annual environmental change.     

Genetic algorithms and evolution

The genetic algorithm (GA) as developed by Holland (1975, Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press) is an optimization technique based on natural selection. We use a modified version of this technique to investigate which aspects of natural selection make it an efficient search procedure. Our main modification to Holland's GA is the subdividing of the population into semi-isolated demes. We consider two examples. One is a fitness landscape with many local optima. The other is a model of singing in birds that has been previously analysed using dynamic programming. Both examples have epistatic interactions. In the first example we show that the GA can find the global optimum and that its success is improved by subdividing the population. In the second example we show that GAs can evolve to the optimal policy found by dynamic programming.     

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low‐quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision‐making framework will result in better‐informed, more robust decisions.     

基于栖息地指数的东太平洋黄鳍金枪鱼渔场预报

黄鳍金枪鱼是东太平洋海域重要的金枪鱼种类之一,也是我国金枪鱼延绳钓的主要捕捞对象之一。根据2011年东太平洋海域(20°N—35°S、85°W—155°W)延绳钓生产统计数据,结合表温(SST)和海面高度(SSH)的遥感数据,采用频次分析法获得黄鳍金枪鱼分布的SST和SSH适宜范围;运用一元非线性回归方法,以渔获量为适应性指数,按季度分别建立了基于SST和SSH的长鳍金枪鱼栖息地适应性指数,采用算术平均法获得基于SST和SSH环境因子的栖息地指数综合模型,并用2012年各月实际作业渔场进行验证。结果显示,黄鳍金枪鱼渔场多分布在SST为24—29℃、SSH为0.3—0.7 m的海域。采用一元非线性回归建立的各因子适应性指数模型在统计上均为显著(P0.05)。经与2012年实际生产情况比较,作业渔场预报准确性达66%以上。研究获得栖息地指数模型可为金枪鱼延绳钓渔船寻找中心渔场提供参考。     

Impact of a mouth parasite in a marine fish differs between geographical areas

Considerable variation exists in parasite virulence and host tolerance which may have a genetic and/or environmental basis. In this article, we study the effects of a striking, mouth‐dwelling, blood‐feeding isopod parasite (Ceratothoa italica) on the life history and physiological condition of two Mediterranean populations of the coastal fish, Lithognathus mormyrus. The growth and hepatosomatic index (HSI) of fish in a heavily human‐exploited population were severely impacted by this parasite, whereas C. italica showed negligible virulence in fish close to a marine protected area. In particular, for HSI, the parasite load explained 34.4% of the variation in HSI in the exploited population, whereas there was no significant relationship (0.3%) between parasite load and HSI for fish in the marine protected area. Both host and parasite populations were not differentiated for neutral genetic variation and were likely to exchange migrants. We discuss the role of local genetic adaptation and phenotypic plasticity, and how deteriorated environmental conditions with significant fishing pressure can exacerbate the effects of parasitism. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105 , 842–852.     

Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing process operating conditions, is optimized using two stochastic optimization (SO) formalisms, viz., genetic algorithms (GAs) and simultaneous perturbation stochastic approximation (SPSA). These SO formalisms possess certain unique advantages over the commonly used gradient-based optimization techniques. The principal advantage of the GP-GA and GP-SPSA hybrid techniques is that process modeling and optimization can be performed exclusively from the process input-output data without invoking the detailed knowledge of the process phenomenology. The GP-GA and GP-SPSA techniques have been employed for modeling and optimization of the glucose to gluconic acid bioprocess, and the optimized process operating conditions obtained thereby have been compared with those obtained using two other hybrid modeling-optimization paradigms integrating artificial neural networks (ANNs) and GA/SPSA formalisms. Finally, the overall optimized operating conditions given by the GP-GA method, when verified experimentally resulted in a significant improvement in the gluconic acid yield. The hybrid strategies presented here are generic in nature and can be employed for modeling and optimization of a wide variety of batch and continuous bioprocesses.     

Generalists versus specialists in fluctuating environments: a bet-hedging perspective

Bet-hedging evolves in fluctuating environments because long-term genotype success is determined by geometric (rather than arithmetic) mean fitness across generations. Diversifying bet-hedging produces different specialist offspring, whereas conservative bet-hedging produces similar generalist offspring. However, many fields, such as behavioral ecology and thermal physiology, typically consider specialist versus generalist strategies only in terms of maximizing arithmetic mean fitness benefits to individuals. Here we model how environmental variability affects optimal amounts of phenotypic variation within and among individuals to maximise genotype fitness, and we disentangle the effects of individual-level optimization and genotype-level bet-hedging by comparing long-term arithmetic versus geometric mean fitness. For traits with additive fitness effects within lifetimes (e.g. foraging-related traits), genotypes of similar generalists or diversified specialists perform equally well. However, if fitness effects are multiplicative within lifetimes (e.g. sequential survival probabilities), generalist individuals are always favored. In this case, geometric mean fitness optimization requires even more within-individual phenotypic variation than does arithmetic mean fitness, causing individuals to be more generalist than required to simply maximize their own expected fitness. In contrast to previous results in the bet-hedging literature, this generalist conservative bet-hedging effect is always favored over diversifying bet-hedging. These results link the evolution of behavioral and ecological specialization with earlier models of bet-hedging, and we apply our framework to a range of natural phenomena from habitat choice to host specificity in parasites.     

Gibberellic acid in plant: Still a mystery unresolved

Gibberellic acid (GA), a plant hormone stimulating plant growth and development, is a tetracyclic di-terpenoid compound. GAs stimulate seed germination, trigger transitions from meristem to shoot growth, juvenile to adult leaf stage, vegetative to flowering, determines sex expression and grain development along with an interaction of different environmental factors viz., light, temperature and water. The major site of bioactive GA is stamens that influence male flower production and pedicel growth. However, this opens up the question of how female flowers regulate growth and development, since regulatory mechanisms/organs other than those in male flowers are mandatory. Although GAs are thought to act occasionally like paracrine signals do, it is still a mystery to understand the GA biosynthesis and its movement. It has not yet confirmed the appropriate site of bioactive GA in plants or which tissues targeted by bioactive GAs to initiate their action. Presently, it is a great challenge for scientific community to understand the appropriate mechanism of GA movement in plant’s growth, floral development, sex expression, grain development and seed germination. The appropriate elucidation of GA transport mechanism is essential for the survival of plant species and successful crop production.