字符串匹配算法在DNA序列比对中的应用

高通量测序技术的飞速发展让生物信息领域迎来了大数据时代。新技术在提供海量生物遗传信息的同时,也给分析这些数据带来了新的挑战。DNA序列比对是信息分析流程中的关键步骤,为后续的变异检测提供序列比对信息。2015“深圳杯”数学建模夏令营B题以DNA序列比对为研究课题,希望参赛学生给出序列快速比对的最佳方案。本文简要点评了各参赛队伍的解答情况,然后介绍了现有DNA序列比对软件中用到的算法和数据结构。     

An improved ensemble learning machine for biological activity prediction of tyrosine kinase inhibitors

Boosting is one of the most important strategies in ensemble learning because of its ability to improve the stability and performance of weak learners. It is nonparametric, multivariate, fast and interpretable but is not robust against outliers. To enhance its prediction accuracy as well as immunize it against outliers, a modified version of a boosting algorithm (AdaBoost R2) was developed and called AdaBoost R3. In the sampling step, extremum samples were added to the boosting set. In the robustness step, a modified Huber loss function was applied to overcome the outlier problem. In the output step, a deterministic threshold was used to guarantee that bad predictions do not participate in the final output. The performance of the modified algorithm was investigated with two anticancer data sets of tyrosine kinase inhibitors, and the mechanism of inhibition was studied using the relative weighted variable importance procedure. Investigating the effect of base learner's strength reveals that boosting is only successful using the classification and regression tree method (a weak to moderate learner) and does not have a significant effect using the radial basis functions partial least square method (a strong base learners). Copyright © 2015 John Wiley & Sons, Ltd.     

Induction of decision trees using genetic programming for modelling ecotoxicity data: adaptive discretization of real-valued endpoints

Recent literature has demonstrated the applicability of genetic programming to induction of decision trees for modelling toxicity endpoints. Compared with other decision tree induction techniques that are based upon recursive partitioning employing greedy searches to choose the best splitting attribute and value at each node that will necessarily miss regions of the search space, the genetic programming based approach can overcome the problem. However, the method still requires the discretization of the often continuous-valued toxicity endpoints prior to the tree induction. A novel extension of this method, YAdapt, is introduced in this work which models the original continuous endpoint by adaptively finding suitable ranges to describe the endpoints during the tree induction process, removing the need for discretization prior to tree induction and allowing the ordinal nature of the endpoint to be taken into account in the models built.     

Identification tree based on fragmentation rules for structure elucidation of organophosphorus esters by electrospray mass spectrometry

Organophosphorus compounds have played important roles as pesticides, chemical warfare agents and extractors of radioactive material. Structural elucidation of phosphonates poses a particular challenge because their initial forms can be hydrolyzed, thus, degradation products may predominate in samples acquired in the field. The analysis of non‐volatile organophosphorus compounds and their degradation products is possible using electrospray tandem mass spectrometry ESI‐MS/MS. Here, we present a generic strategy that allows the unambiguous identification of substituents for two families of organophosphorus compounds: the phosphonates and phosphates. General fragmentation rules were deduced based on the study of decomposition pathways of 55 organophosphorus esters, including examples found in the literature. Multistage MS (MSⁿ) experiments at high resolution in a hybrid mass spectrometer provide accurate mass measurements, whereas collision‐induced dissociation experiments in a triple quadrupole give access to small fragment ions. The creation of a specific nomenclature for each possible structure of organophosphorus compound, depending on the alkyl side chain linked to the oxygen, was achieved by applying these fragmentation rules. This led to the creation of an ‘identification tree’ based upon the unique consecutive decomposition pathways uncovered for each individual compound. Hence, seven structural motifs were created that orient an unequivocal identification using the ‘identification tree’. Despite the similar structures of the ensemble of phosphate and phosphonate esters, distinct identifications based upon characteristic neutral losses and diagnostic fragment ions were possible in all cases. Copyright © 2013 John Wiley & Sons, Ltd.     

大型砂尘风洞中砂尘浓度测量与控制方法的研究

砂尘浓度指标严重影响砂尘风洞试验效果;在大型砂尘风洞中准确的测量及有效的控制砂尘浓度是砂尘风洞设备研制中的两个关键问题;针对动态试验工况环境中浓度传感器标定的问题,分析了浓度测量时标定参数与风速和浓度的关系,使用模型树算法建立了三者之间的关系模型,以此模型来预测各种动态情况下的标定参数;针对复杂环境下浓度动态控制问题,采用专家PID算法,提出了多回路控制系统结构和专家规则;工程实践表明该测量和控制方法满足了动态试验环境的需求,取得了良好效果;模型树算法和专家PID系统能有效的解决动态工况下砂尘浓度的测量与控制问题。     

非齐次树上马氏链的若干强偏差定理

通过构造适当的非负鞅,将Doob鞅收敛定理应用于几乎处处收敛的研究,给出了一类非齐次树上马氏链场加权和滑动平均的若干强偏差定理.     

Uncommon suffix tries

Common assumptions on the source producing the words inserted in a suffix trie with n leaves lead to a height and saturation level. We provide an example of a suffix trie whose height increases faster than a power of n and another one whose saturation level is negligible with respect to . Both are built from VLMC (Variable Length Markov Chain) probabilistic sources and are easily extended to families of tries having the same properties. The first example corresponds to a “logarithmic infinite comb” and enjoys a non uniform polynomial mixing. The second one corresponds to a “factorial infinite comb” for which mixing is uniform and exponential. © 2013 Wiley Periodicals, Inc. Random Struct. Alg., 46, 117–141, 2015     

Covariate model-based fault tree analysis for risk assessment in chemical process industries: A case study of a chlorine manufacturing facility

Fault tree analysis (FTA) is a promising quantitative technique for risk analysis in chemical process industries (CPIs). In FTA, a certain sequence of basic events (causes) leads to one specific Top event (critical event of interest). However, the conventional fault tree analysis has the limitations of staticity and uncertainty. The staticity in conventional FTA arises due to its inability to accommodate time-dependent characteristics of the process system. Whereas uncertainty primarily lies in the failure probability data of basic events. This paper proposes an innovative methodology that uses a time-dependent covariate model to update the failure probability values of major contributing basic events in FTA. A novel subclass of the family of phase-type distributions is used to model the covariates corresponding to the basic events. The newly developed methodology is applied for a case study in a chlorine manufacturing facility to estimate the chlorine release probability. The blockage in the pipeline was identified as the significant reason for chlorine release from expert opinion and sensitivity analysis. The results of the proposed model of FTA are compared with that of conventional FTA.     

多值测试诊断策略优化设计

针对电子系统中多值测试条件下的测试排序问题,提出了一种诊断策略优化方法。首先,以相关性矩阵模型为基础,将已有的二值测试的优化算法同多值测试问题相结合,提出了适用于多值测试的基于霍夫曼编码的启发式函数;其次,将平均测试代价最小和平均测试步骤最少作为优化目标,采用与或树启发式搜索算法生成诊断树,得到多值测试的诊断策略,并给出了诊断策略优化方法的具体实现步骤;最后,将其应用到航空设备的实例中。结果表明提出的基于霍夫曼编码的与或树启发式搜索算法是可行的,其生成的诊断树是最优的,比基于信息熵的与或树启发式搜索算法具有更小的平均测试代价和更少的平均测试步骤。     

Addendum to: “Hamilton-laceable bi-powers of locally finite bipartite graphs” [Discrete Math. 345 (2022) 112777]

In this addendum we give a short and easy negative answer to the two questions raised in the original article.