基于Web技术的医学图像发布系统

目的：应用Java技术开发一个基于Web技术的操作简易、通用性强的医学图像发布环境。方法：采用Web服务器来查询和提取存储在DICOM服务器中的医学图像，客户端使用嵌有JavaApplet小程序的Web浏览器来访问Web服务器，完成客户端对服务器端医学图像的提取，JavaApplet小程序利用Web浏览器实现其图像操作。结果：我们使用Java技术开发一个基于Web技术的医学图像发布环境，完成了客户机通过Intemet对服务器端医学图像的读取操作，实现了异地专家的在线交流。结论：与大多数传统的PACS相比．基于Web技术的PACS系统易于安装和维护，与运行平台无关，可以高效的显示、处理医学图像，容易和使用Web技术构建的PACS系统整合。设置适当的安全防范措施，用户可以在医院外部实现对该系统的访问。Intemet技术的简易性和可扩展性使得该系统与传统PACS系统相比有着更大的优越性。     

DICOM数据的三维重建与协同可视化系统的开发

复杂手术常需多科医生协商制定综合性治疗方案,网络协同三维可视化软件可使方案制定直观而精确。我们采用VTK工具包对DICOM格式CT图像数据进行三维重建并作网格简化,将结果所得多边形网格模型无缝集成到用HOOPS/3DAF所开发的图形系统进行显示,并用HOOPS/Stream工具包转成适合网络传输的HSF无损压缩流文件,再用HOOPS/NET工具包实现基于Client/Server架构的协同三维交互可视化系统。所得三维重建结果清晰,协同三维可视化操作实时度高。本研究实现了一个协同手术仿真开发平台,该架构易于进一步添加模拟手术操作与修复体设计功能。     

面向精准医学的生物医学本体资源存储和应用平台

在过去10余年中,本体广泛应用于生物医学数据分析、检索、整合和再利用中。本体作为一种特殊类型的数据资源,数据量也在迅速增加。为了促进精准医疗领域数据集的整合,并为国内用户提供本体数据资源服务,构建MedPortal本体资源存储和应用平台。通过复用NCBO BioPortal技术,搭建MedPotal软件框架。遴选精准医学相关本体,建立本体资源库。对原框架中的代码和本体处理工具进行修正和完善,使之能够在本体稳定运行的基础上满足大批量数据的自动化处理。目前,该平台已整合42个生物医学本体,建立了本体之间术语映射关系,通过页面和REST API方式,提供术语检索、本体映射、数据标准化注释等本体应用服务(http://medportal.bmicc.cn)。MedPortal本体平台将为生物医学数据整合提供帮助。     

MedPortal:面向精准医学的生物医学本体资源存储和应用平台

在过去10余年中,本体广泛应用于生物医学数据分析、检索、整合和再利用中。本体作为一种特殊类型的数据资源,数据量也在迅速增加。为了促进精准医疗领域数据集的整合,并为国内用户提供本体数据资源服务,构建MedPortal本体资源存储和应用平台。通过复用NCBO BioPortal技术,搭建MedPotal软件框架。遴选精准医学相关本体,建立本体资源库。对原框架中的代码和本体处理工具进行修正和完善,使之能够在本体稳定运行的基础上满足大批量数据的自动化处理。目前,该平台已整合42个生物医学本体,建立了本体之间术语映射关系,通过页面和REST API方式,提供术语检索、本体映射、数据标准化注释等本体应用服务(http://medportal.bmicc.cn)。MedPortal本体平台将为生物医学数据整合提供帮助。     

局域网分布式超声图像信息系统(PACS)的应用与改进

目的：通过研制局域网分布式医学超声图像文字信息系统（LAN－PACS－2000），试图建立一个超声影像科内临床实用和方便的图文传输归档报告工具，以实现医院管理科学化和超声影像科图文处理的现代化。方法：该系统把多台超声设备上获得的信息，通过计算机网络及专门软件，在影像科内联成一区域网络系统。开发的原理是：基于客户服务方式，采用三层客户机／服务器配置方案，以分布式应用程序开发软件的思想，来实现信息的输入、输出、查询及数据的维护。并与L及B公司产品作简单比较。结果：该系统由网络服务器、图像采集工作站、登记、查询站等构成，系统运行稳定，有关图像和数据被分别存储在不同的物理服务器上，数据为网络内用户共享。结论：该系统布局合理，查询方便，工作流程科学，诊断报告术语规范，图文并茂，速度快捷，能较好地满足超声影像科管理和临床工作需要。     

基于稀疏表示变量选择方法的影像遗传学数据分析

目的:采用影像遗传学研究方法探索精神分裂症的影像遗传学特征。方法:在传统稀疏回归模型的基础上，改进 了其在不同范数条件下进行变量选择的能力，形成一种基于稀疏表示变量选择算法，并将该算法应用于208 个受试者的 41 236个功能磁共振成像数据和722 177个单核苷酸多态性数据的综合分析。通过对两类数据施加不同的权重因子，并 使用不同的Lp （p=0、0.5、1）范数分别对模型进行求解，筛选出两类数据在不同条件下的显著特征。结果:基因DAOA和 HTR2A在3种范数下均被筛选出。此外，在影像学数据方面，发现中央前回、枕上回、顶下缘角回、角回、内侧和旁扣带脑 回、后扣带回脑区与精神分裂症相关，此发现与先前精神分裂症的临床医学研究结果一致。结论:基于稀疏表示变量选择 方法应用于影像遗传学数据分析是一个有效可行的途径，为今后精神分裂症的影像遗传学研究提供了一种新的研究 思路。     

心肺复苏生理参数分析软件

目的:介绍一套用于分析心肺复苏生理参数的软件。方法:本软件基于微软Visual Basic6.0平台,采用模块化设计思路,在差分阈值法的基础上,通过极值点法、一阶微分法对生理记录仪记录的心肺复苏研究数据进行处理,计算结果以Excel文件保存。结果:通过与手工计算结果的统计学分析比较,证明该软件拥有良好的可靠性。结论:这套分析软件能够准确高效计算出心肺复苏研究过程中记录的生理参数波形数据结果,基本满足了心肺复苏研究需要。并且在使用过程中具有操作简单、多通道数据同时分析、效率高、运行稳定等特点,具有一定实用价值。     

基于Unity3D的脑电图检测与分析虚拟仿真实验项目的设计和开发

依托国家精品资源共享课程《生物医学信号处理》，利用三维虚拟现实开发技术（Unity3D），以C#为脚本语言，开发了脑电图检测与分析虚拟仿真实验平台。该平台通过交互式的实验流程、可视化的数据分析、生动形象的结果展示，可以让学生在有限的课程时间里真实体验脑电图检测和分析这一复杂的实验操作过程，对脑电图检测与分析进行更全面深入的学习，从而提高学生基本的实验操作与数据分析能力。最后，本文详细地介绍了实验流程的总体框架和软件系统模块设计，为虚拟仿真技术在教学上的应用和推广提供了重要参考。     

组学大数据环境下的基因变异信息并行处理与分析

随着第二代测序技术的发展与应用,其产生的测序数据也呈现快速的增长趋势,如何有效、快速、稳定地对海量测序数据进行分析成为生物研究领域迫切的需求。目前许多传统的测序数据分析软件仅支持单一功能,并不具备完整的数据分析能力,应对海量的测序数据时其处理能力也显著不足。为了应对上述问题,本文设计了一款基于Hadoop框架的测序数据分析软件,整合了现今生物研究领域内常用的多款序列分析软件,从而实现了对测序序列数据的自动化分析。该软件输入原始的测序数据后,经过碱基质量控制、序列比对、SNP位点信息提取、突变基因信息生成等几个过程,最终输出详细的突变基因信息报告。该软件实现了自动化的数据分析,提高了数据分析的效率,极大减轻了数据分析人员的工作量。     

医院临床数据分析系统的构建

目的 通过数据集成平台(data integration platform,DIP),整合医院不同业务系统的数据,构建临床数据共享库,为疾病的治疗及医院的管理提供支持.方法 采用J2EE技术以及ICE中间件通信技术实现DIP的数据通信,完成数据仓库建设工作.采用开源工具JasperReport,实现数据分析的展现.结果 数据集成是实现数据分析的前提,保障了医疗数据的来源真实可靠.结论 数据集成平台和数据分析系统结合的一体化流程,减少了临床和科研人员的二次录入工作,节约了数据处理的时间.数据挖掘的结果为医院的医疗以及管理提供了帮助.     

Tag SNP selection for candidate gene association studies using HapMap and gene resequencing data

HapMap provides linkage disequilibrium (LD) information on a sample of 3.7 million SNPs that can be used for tag SNP selection in whole-genome association studies. HapMap can also be used for tag SNP selection in candidate genes, although its performance has yet to be evaluated against gene resequencing data, where there is near-complete SNP ascertainment. The Environmental Genome Project (EGP) is the largest gene resequencing effort to date with over 500 resequenced genes. We used HapMap data to select tag SNPs and calculated the proportions of common SNPs (MAF>or=0.05) tagged (rho2>or=0.8) for each of 127 EGP Panel 2 genes where individual ethnic information was available. Median gene-tagging proportions are 50, 80 and 74% for African, Asian, and European groups, respectively. These low gene-tagging proportions may be problematic for some candidate gene studies. In addition, although HapMap targeted nonsynonymous SNPs (nsSNPs), we estimate only approximately 30% of nonsynonymous SNPs in EGP are in high LD with any HapMap SNP. We show that gene-tagging proportions can be improved by adding a relatively small number of tag SNPs that were selected based on resequencing data. We also demonstrate that ethnic-mixed data can be used to improve HapMap gene-tagging proportions, but are not as efficient as ethnic-specific data. Finally, we generalized the greedy algorithm proposed by Carlson et al (2004) to select tag SNPs for multiple populations and implemented the algorithm into a freely available software package mPopTag.     

Efficient Association Study Design Via Power‐Optimized Tag SNP Selection

Discovering statistical correlation between causal genetic variation and clinical traits through association studies is an important method for identifying the genetic basis of human diseases. Since fully resequencing a cohort is prohibitively costly, genetic association studies take advantage of local correlation structure (or linkage disequilibrium) between single nucleotide polymorphisms (SNPs) by selecting a subset of SNPs to be genotyped (tag SNPs). While many current association studies are performed using commercially available high‐throughput genotyping products that define a set of tag SNPs, choosing tag SNPs remains an important problem for both custom follow‐up studies as well as designing the high‐throughput genotyping products themselves. The most widely used tag SNP selection method optimizes the correlation between SNPs (r²). However, tag SNPs chosen based on an r² criterion do not necessarily maximize the statistical power of an association study. We propose a study design framework that chooses SNPs to maximize power and efficiently measures the power through empirical simulation. Empirical results based on the HapMap data show that our method gains considerable power over a widely used r²‐based method, or equivalently reduces the number of tag SNPs required to attain the desired power of a study. Our power‐optimized 100k whole genome tag set provides equivalent power to the Affymetrix 500k chip for the CEU population. For the design of custom follow‐up studies, our method provides up to twice the power increase using the same number of tag SNPs as r²‐based methods. Our method is publicly available via web server at http://design.cs.ucla.edu .     

DVL2基因多态性与中国汉族人群先天性脊柱侧凸遗传易感性的关联研究

背景：近20年来小鼠的分子胚胎学研究进展获得了大量关于脊椎发育的分子信息,用同线性分析法确立先天性脊柱侧凸的候选基因已成为可能。 目的：通过候选基因DVL2上关键单核苷酸多态性位点的筛查,探索DVL2与中国汉族人群先天性脊柱侧凸及其不同临床表型之间的关联。 方法：采用病例-对照研究,入选127例中国汉族先天性脊柱侧凸患者和127例对照组。根据国际人类基因组单体型图计划提供的基因型数据,应用Haploview 4.1软件选取DVL2的标签和功能单核苷酸多态性。根据椎体畸形特点、畸形部位、畸形受累程度、有无合并肋骨畸形和椎管内畸形将病例组进一步分为不同临床表型。对所有样本应用SNPstream UHT Genotyping系统对所选单核苷酸多态性位点进行基因型鉴定;进一步进行基于基因型/等位基因频率的关联分析,并用Haploview 4.1软件分析对照组单核苷酸多态性位点间是否存在连锁不平衡。 结果与结论：共筛选5个位点：单核苷酸多态性1(rs2074222)、单核苷酸多态性2(rs222837)、单核苷酸多态性3(rs222835)、单核苷酸多态性4(rs10671352)和单核苷酸多态性5(rs222836),其基因型分布在病例和对照组中均符合Hardy-Weinberg平衡;5个位点处于完全连锁不平衡状态;5个位点的基因型/等位基因/单倍体型与先天性脊柱侧凸的发生风险之间不存在相关性。在进一步与先天性脊柱侧凸临床表型的关联分析中没有发现阳性位点。提示在中国汉族人群中DVL2基因可能不是引起先天性脊柱侧凸及其不同临床表型的主要因素,有待于进一步深入研究。     

Linking disease associations with regulatory information in the human genome

Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with a large number of phenotypes. However, an associated SNP is likely part of a larger region of linkage disequilibrium. This makes it difficult to precisely identify the SNPs that have a biological link with the phenotype. We have systematically investigated the association of multiple types of ENCODE data with disease-associated SNPs and show that there is significant enrichment for functional SNPs among the currently identified associations. This enrichment is strongest when integrating multiple sources of functional information and when highest confidence disease-associated SNPs are used. We propose an approach that integrates multiple types of functional data generated by the ENCODE Consortium to help identify "functional SNPs" that may be associated with the disease phenotype. Our approach generates putative functional annotations for up to 80% of all previously reported associations. We show that for most associations, the functional SNP most strongly supported by experimental evidence is a SNP in linkage disequilibrium with the reported association rather than the reported SNP itself. Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes.     

Genetic Variation at the Chromosome 16 Chemokine Gene Cluster: Development of a Strategy for Association Studies in Complex Disease

The chemokine gene cluster [CCL22, CX3CL1, CCL17] (previously known as [SCYA22, SCYD1, SCYA17]) is a candidate locus for one of the susceptibility genes for inflammatory bowel disease that are located in the peri‐centromeric region of chromosome 16. Screening for sequence variation at this locus led to the detection of 14 single nucleotide polymorphisms (SNPs). An efficient experimental and computational approach was developed to estimate allele frequencies and pairwise linkage disequilibrium relationships between SNPs at this locus, and to test them for association with inflammatory bowel disease. The 12 common SNPs were assigned to 5 distinct linkage disequilibrium groups. Genotyping of one SNP from each linkage disequilibrium group in a large cohort of families with inflammatory bowel disease did not provide convincing evidence of association with either Crohn's disease or ulcerative colitis. We describe an efficient experimental design from SNP screening to association testing. This strategy can be used to test candidate genes for involvement in susceptibility to complex disease.     

A renaissance of "biochemical genetics"? SNPs, haplotypes, function, and complex diseases

We have made remarkable progress in understanding the molecular bases of many Mendelian diseases over the past 2-3 decades. The current interest in discovering the molecular basis of complex diseases uses either linkage or candidate gene approaches. The latter often uses case/control (or case/cohort) study designs. We believe it is critically important to have a thorough understanding of SNP (single nucleotide) and haplotype function in such endeavors. Functionally neutral SNPs and haplotypes are probably best suited for linkage studies (far away from the locus of interest). Functionally relevant SNPs and haplotypes seem best suited for candidate gene approaches. The need for functional data may result in a renaissance of biochemical genetics with a new twist in the genomic era. We propose that the functional characterization of SNPs and haplotypes be advanced with great vigor for those genes with defined assayable phenotypes. These systematic investigations will involve classical biochemistry, modern genetics, and genomics and will probably also draw on newer technologies such as microarrays. In short, a renaissance of biochemical genetics will advance our understanding of complex diseases.     

Linkage disequilibrium and age of HLA region SNPs in relation to classic HLA gene alleles within Europe

The HLA region on chromosome 6 is gene-rich and under selective pressure because of the high proportion of immunity-related genes. Linkage disequilibrium (LD) patterns and allele frequencies in this region are highly differentiated across broad geographical populations, making it a region of interest for population genetics and immunity-related disease studies. We examined LD in this important region of the genome in six European populations using 166 putatively neutral SNPs and the classical HLA-A, -B and -C gene alleles. We found that the pattern of association between classic HLA gene alleles and SNPs implied that most of the SNPs predated the origin of classic HLA gene alleles. The SNPs most strongly associated with HLA gene alleles were in some cases highly predictive of the HLA allele carrier status (misclassification rates ranged from <1 to 27%) in independent populations using five or fewer SNPs, a much smaller number than tagSNP panels previously proposed and often with similar accuracy, showing that our approach may be a viable solution to designing new HLA prediction panels. To describe the LD within this region, we developed a new haplotype clustering method/software based on r², which may be more appropriate for use within regions of strong LD. Haplotype blocks created using this proposed method, as well as classic HLA gene alleles and SNPs, were predictive of a northern versus southern European population membership (misclassification error rates ranged from 0 to 23%, depending on which independent population was used for prediction), indicating that this region may be a rich source of ancestry informative markers.     

纤维蛋白原Bβ基因启动区单核苷酸多态性及连锁不平衡分析

目的　探讨纤维蛋白原 B(fibrinogen,FGB)基因启动区 - 14 8C/ T、- 4 5 5 G/ A、- 85 4 G/ A3个位点单核苷酸多态性 (single nucleotide polymorphism,SNP)在中国南方汉族人群的分布特征及连锁不平衡关系。方法　应用聚合酶链反应 -限制性片段长度多态性技术结合 DNA测序分析检测 377名中国南方汉族人 FGBβ基因型和等位基因的分布频率 ,群体数理遗传学方法分析 FGBβ 3个基因位点 SNP的遗传平衡吻合度和相互间连锁不平衡关系。结果　 3个 FGBβ SNP位点等位基因频率分布符合 Hardy-Weinberg平衡。检出了 FGBβ3个位点 SNP的共 9种基因型 ,- 14 8CC、CT、TT基因型频率分别为0 .5 97、0 .35 8和 0 .0 4 5 ;- 4 5 5 G/ A SNP各基因型频率与 - 14 8C/ T SNP相同 ;- 85 4 GG、GA、AA基因型频率分别为 0 .82 0、0 .178和 0 .0 0 2。各 SNP位点的少见型等位基因频率分别是 0 .2 2 4 (- 14 8T)、0 .2 2 4 (-4 5 5 A)、0 .0 92 (- 85 4 A) ;常见型等位基因频率分别为 0 .776 (- 14 8C)、0 .776 (- 4 5 5 G)、0 .90 8(- 85 4 G)。男女性别间各基因型和等位基因分布频率差异无显著性 (P>0 .0 5 )。经连锁不平衡检验 ,- 14 8C与 - 4 5 5 GSNP为完全一致型 ,- 85 4 G/ A与 - 14 8C/ T、- 4 5 5 G/ A为随机分布。结     

Optimal haplotype block-free selection of tagging SNPs for genome-wide association studies

It is widely hoped that the study of sequence variation in the human genome will provide a means of elucidating the genetic component of complex diseases and variable drug responses. A major stumbling block to the successful design and execution of genome-wide disease association studies using single-nucleotide polymorphisms (SNPs) and linkage disequilibrium is the enormous number of SNPs in the human genome. This results in unacceptably high costs for exhaustive genotyping and presents a challenging problem of statistical inference. Here, we present a new method for optimally selecting minimum informative subsets of SNPs, also known as "tagging" SNPs, that is efficient for genome-wide selection. We contrast this method to published methods including haplotype block tagging, that is, grouping SNPs into segments of low haplotype diversity and typing a subset of the SNPs that can discriminate all common haplotypes within the blocks. Because our method does not rely on a predefined haplotype block structure and makes use of the weaker correlations that occur across neighboring blocks, it can be effectively applied across chromosomal regions with both high and low local linkage disequilibrium. We show that the number of tagging SNPs selected is substantially smaller than previously reported using block-based approaches and that selecting tagging SNPs optimally can result in a two- to threefold savings over selecting random SNPs.     

Mini-haplotypes as lineage informative SNPs and ancestry inference SNPs

We propose that haplotyped loci with high heterozygosity can be useful in human identification, especially within families, if recombination is very low among the sites. Three or more SNPs extending over small molecular intervals (<10 KB) can be identified in the human genome to define miniature haplotypes with moderate levels of linkage disequilibrium. Properly selected, these mini-haplotypes (or minihaps) consist of multiple haplotype lineages (alleles) that have evolved from the ancestral human haplotype but show no evidence of recurring recombination, allowing each distinct haplotype to be equated with an allele, all copies of which are essentially identical by descent. Historic recombinants, representing rare events that have drifted to common frequencies over many generations, can be identified in some cases, they do not equate to frequently recurring recombination. We have identified examples in our data collected on various projects and present eight such mini-haplotypes comprised of informative SNPs. We also discuss the ideal characteristics and advantages of minihaps for human familial identification and ancestry inference, and compare them to other types of forensic markers in use and/or that have been proposed. We expect that it is possible to carry out a systematic search and identify a useful panel of mini-haplotypes, with even better properties than the examples presented here.