PBEAM: A parallel implementation of BEAM for genome-wide inference of epistatic interactions

The software tool PBEAM provides a parallel implementation of the BEAM, which is the first algorithm for large scale epistatic interaction mapping, including genome-wide studies with hundreds of thousands of markers. BEAM describes markers and their interactions with a Bayesian partitioning model and computes the posterior probability of each marker sets via Markov Chain Monte Carlo (MCMC). PBEAM takes the advantage of simulating multiple Markov chains simultaneously. This design can efficiently reduce ~n-fold execution time in the circumstance of n CPUs. The implementation of PBEAM is based on MPI libraries.

Availability

PBEAM is available for download at http://bioinfo.au.tsinghua.edu.cn/pbeam/     

An adaptive and robust biological network based on the vacant-particle transportation model

A living system reveals local computing by referring to a whole system beyond the exploration-exploitation dilemma. The slime mold, Physarum polycephalum, uses protoplasmic flow to change its own outer shape, which yields the boundary condition and forms an adaptive and robust network. This observation suggests that the whole Physarum can be represented as a local protoplasmic flow system. Here, we show that a system composed of particles, which move and are modified based upon the particle transformation that contains the relationship between the parts and the whole, can emulate the network formed by Physarum. This system balances the exploration-exploitation trade-off and shows a scale-free sub-domain. By decreasing the number of particles, our model, VP-S, can emulate the Physarum adaptive network as it is attracted to a food stimulus. By increasing the number of particles, our model, VP-D, can emulate the pattern of a growing Physarum. The patterns produced by our model were compared with those of the Physarum pattern quantitatively, which showed that both patterns balance exploration with exploitation. This model should have a wide applicability to study biological collective phenomena in general.     

山西省医疗机构服务能力分析与评估系统开发与应用

介绍了山西省医疗机构服务能力分析与评估系统开发的必要性,描述了具体的系统设计方案、运行流程、分析方法及应用情况。通过该系统的应用,及时收集全省二级以上医疗机构病案首页数据、门诊患者的诊疗数据与医疗机构经济运行数据,及时分析评估医疗机构的医疗技术服务能力、医疗质量、管理水平、患者费用负担、经济运行状况以及影响全省人群的主要疾病等指标,为卫生行政部门实施医疗卫生体制改革、医疗机构日常监管、全省范围内疾病防控等提供数据支持。     

多媒体在微生物教学中的应用

多媒体计算机技术教学是一种新型的教学方式之一。多媒体教学克服了传统的微生物教学可视化差、形象不够直观等缺点。但全课堂多媒体教学则会扼杀教师教学中的即兴创造,成为典型的电脑“满堂灌”。所以多媒体课件的制作应符合教学规律,片面强调声形兼备,会导致许多环节与课堂脱节。教学中应目的明确、化难为易,探索其固有教学规律,努力做到教学相长。     

A new solution for maximal clique problem based sticker model

In this paper, we use stickers to construct a solution space of DNA for the maximal clique problem (MCP). Simultaneously, we also apply the DNA operation in the sticker-based model to develop a DNA algorithm. The results of the proposed algorithm show that the MCP is resolved with biological operations in the sticker-based model for the solution space of the sticker. Moreover, this work presents clear evidence of the ability of DNA computing to solve the NP-complete problem. The potential of DNA computing for the MCP is promising given the operational time complexity of O(nxk).     

A CLIQUE algorithm using DNA computing techniques based on closed-circle DNA sequences

DNA computing has been applied in broad fields such as graph theory, finite state problems, and combinatorial problem. DNA computing approaches are more suitable used to solve many combinatorial problems because of the vast parallelism and high-density storage. The CLIQUE algorithm is one of the gird-based clustering techniques for spatial data. It is the combinatorial problem of the density cells. Therefore we utilize DNA computing using the closed-circle DNA sequences to execute the CLIQUE algorithm for the two-dimensional data. In our study, the process of clustering becomes a parallel bio-chemical reaction and the DNA sequences representing the marked cells can be combined to form a closed-circle DNA sequences. This strategy is a new application of DNA computing. Although the strategy is only for the two-dimensional data, it provides a new idea to consider the grids to be vertexes in a graph and transform the search problem into a combinatorial problem.     

BDCGrid:基于Globus的生物信息高性能计算网格系统

随着分子生物信息数据量高速增长,生物信息学面临着大规模、高通量、密集型计算的巨大挑战。为有效利用计算机资源,缩短高通量生物信息计算程序执行时间,我们基于Globus Toolkit网格中间件,实现了一个支持高通量生物数据计算的网格系统(Biological Data Computing Grid,简称BDCGrid)。BDCGrid计算网格系统模型可以有效整合中小型生物信息学实验室计算机资源,大大缩短高通量生物信息计算程序执行时间,为相关研究人员利用现有计算机资源处理大规模、高通量生物信息计算任务提供一种新的途径。     

贝叶斯方法估计阈性状育种值的原理和计算技术

本文介绍了估计阈性状育种值的贝叶斯方法的原理,演示了描述阈性状观察值、建立后验概率密度函数、以及导出非线性方程组的方法．并就这一估计方法的计算技术进行了讨论,针对动物遗传育种中方程组系数矩阵往往很大,超出计算机内存的情况,提出了不需要建立方程组,在数据上迭代求解的计算方法．本文还综述了这一非线性方法与线性方法在阈性状育种值估计上的比较．     

Phenotypic and genotypic intra-diversity among Anatolian durum wheat “Kunduru” landraces

Kunduru is an important Anatolian landrace having peculiar traits that are appreciated by farmers and breeders. 33 accessions known as Kunduru collected by ICARDA from six geographical provinces of Turkey, were used to study the phenotypic and genotypic intra-diversity. Kunduru landraces exhibited high intra-diversity for most of the studied morphological traits. GPC (12.10–14.90%), vitreousness (75–100%), TKW (31.80–56.70 g), YP (4.70–8.00 ppm), b*-value (14.30–19.50), ash content (1.60–2.0%) and gluten strength (14–60 ml) showed marked variations. Gliadin and glutenin banding patterns showed high polymorphism. 65 alleles were detected with 14 SSR markers, giving a mean of 6.77 alleles per locus. The average PIC value was 0.44 and ranged from 0.11 to 0.70. The average genetic distance between pairs of landraces was 0.47 and ranged between 0.11 and 0.72. This study showed that Kunduru landraces maintains high allelic variation. PCoA indicated that eco-geographical variables have a significant effect on SSR diversity as well as morphological traits. Many of the landraces studied are in danger of disappearing from the local farmers' fields; this study demonstrates the importance of maintaining and conserving this precious genetic resources.     

人线粒体DNA的信息结构

本文报道了运用FORTRAN-77语言,在SIRIUS-1微机上计算遗传信息的冗余结构D_1、D_2、D_3的程序。计算出人线粒体DNA(16569个核苷酸残基)的H_1=1.930554,H_2=3.849254,H_3=5.760944,D_1=0.069446,D_2=0.011853,D_3=0.007011。 D_1、D_2的结果表明,人线粒体DNA的信息结构远比脊椎动物DNA的低级,这支持线粒体的共生起源学说。并对D_3的结果进行了分析,对其意义作了初步探讨。