基于免疫GA与Gibbs的模体识别算法

生物序列motif识别问题是当今生物信息学面临的一个复杂问题,要设计一个能识别所有motif的方法几乎是不可能的。针对该问题,在免疫遗传算法中引入了统计估计,提高了motif识别的精度,根据个体的浓度和适应值概率。设计了免疫替换算子,有效地解决了种群的多样性问题,利用Gibbs Sampler算法生成种子,提高了免疫遗传算法的搜索速度,最后得到了一个基于免疫GA与Gibbs Sampler的生物序列motif识别算法,该算法充分发挥了免疫遗传算法和Gibbs Sampler算法的优越性,较好地解决了计算速度和计算精度之间的矛盾。实验表明,该算法是有效的。     

基于字典的DNA序列压缩算法研究及应用*

在现有DNA序列数据压缩算法的基础上,以DNA序列数据的存储效率及生物学解释综合考虑,设计并实现了基于字典的DNA序列压缩算法DNADCompress.算法核心包括重复子串字典建立、字典项筛选、字串压缩编码三方面.实验数据表明,数据压缩算法压缩效果达到常用DNA序列压缩算法水平,并为序列生物学解释提供了基础.     

Improvements to the Control Techniques of Sequential Inference Machines——from Instructions to Hardware Organization

Nondeterminism of PROLOG execution requires that a block of control information or a choice point for each procedure call be stored when there are other candidate clauses to be used.When the currently selected clause fails,the bindings made by the clause must be undone and the stored choice point is reactivated,and then another clause of the candidate ones is chosen to run on it.Storing and reactivating choice points and undoing account for the great overhead are required to control PROLOG execution,which is quite different from conventional programs.This paper focuses on the techniques used in Sequential PROLOG Engine (SPE) to reduce the overhead of control operations.The control instructions of SPE store no more choice points than the necessary.Its architecture takes the approaches of analysing the potential parallelism in the control operations and developing a fraction of it due to the cost-effect consideration.The results of executing two sample programs on SPE in the form of hand timings are presented,which favor the approach.     

变形假单胞菌2-酮基葡萄糖酸激酶基因的克隆、表达及生物信息学分析

采用聚合酶链式反应技术,从2-酮基葡萄糖酸工业生产菌株变形假单胞菌JUIM01中克隆2-酮基葡萄糖酸激酶的全长基因kguK,并在此基础上构建了重组菌株大肠杆菌BL21(DE3)/pET-28a(+)-kguK。在异丙基-β-D-硫代半乳糖苷的诱导下,该重组菌株表达了一个特异的分子质量约为36.0 ku融合蛋白,且该蛋白的Western-Blot鉴定结果显示为阳性。生物信息学分析结果表明,该蛋白是一种由305个氨基酸残基组成的亲水性蛋白,定位于细胞质中,存在着与pfkB家族蛋白类似的保守结构域,其二级结构中α-螺旋、延伸链和无规则卷曲所占的比例分别为35.73%、12.79%和51.48%。     

缺血性心肌病不同阶段基因表达的改变模式研究

文章选取缺血性心肌病患者和对照组收集的外周血,对其采用微阵列数据集进行转录组分析,分为两个部分进行.在第一部分,从3组缺血性心肌病患者样本与健康对照的数据集分析中,确定了3个重要基因——成纤维细胞生长因子结合蛋白2 (FGFBP2)、葡萄糖-果糖氧化还原酶结构域(GFOD1)和伴皮层下囊肿的巨脑性白质脑病(MLC1),可作为潜在的mRNA生物标志物.在第二部分,从3个时间点(发作当天、恢复4～6天及恢复6个月)收集了2组基因表达数据集.基因代谢途径的差异性分析表明,与对照组对比,发作组和恢复组涉及到炎症和免疫途径;与恢复6个月组对比,发作组和恢复组(4～6天)涉及到代谢途径或神经分泌.这显示了缺血性心肌病的发作和恢复期间的生物学过程变化.实验结果表明,3种潜在的mRNA生物标志物——FGFBP2、GFOD1和MLC1,涉及到缺血性心肌病不同的代谢通路,具有连续的生物学过程变化.     

A Reconfigurable Index FLASH Memory tailored to Seed-Based Genomic Sequence Comparison Algorithms

Genomic sequence comparison algorithms represent the basic toolbox for processing large volume of DNA or protein sequences. They are involved both in the systematic scan of databases, mostly for detecting similarities with an unknown sequence, and in preliminary processing before advanced bioinformatics analysis. Due to the exponential growth of genomic data, new solutions are required to keep the computation time reasonable. This paper presents a specific hardware architecture to speed-up seed-based algorithms which are currently the most popular heuristics for detecting alignments. The architecture regroups FLASH and FPGA technologies on a common support, allowing a large amount of data to be rapidly accessed and quickly processed. Experiments on database search and intensive sequence comparison demonstrate a good cost/performance ratio compared to standard approaches.