利用SFU开发Windows和Linux异构环境下的分布式生物信息学应用

Microsoft SFU是一个Windows环境下的高性能UNIX子系统和互操作工具，它允许Windows和UNIX计算机共享数据、安全策略和应用程序。本文通过实例，介绍如何利用SFU将Linux下的Blat软件在Windows系统中重新编译运行，并与Linux计算机共享生物序列数据库，构建异构网络环境下的分布式生物信息学应用。实践证明该技术可集成Windows和Linux的计算能力，提高计算资源的使用效率。     

浅谈临床生物信息学在临床医学教育中的作用及初步实践

生物信息学是一门整合计算机科学及生命科学的交叉学科,已有30余年历史,但仍方兴未艾。21世纪以来,生物医学已逐渐进入大数据时代,海量的以测序为代表的基因组、转录组、蛋白质组数据将为深刻揭示人类疾病发生机制及寻找治疗药物提供了前所未有的契机。目前,在临床医学研究及教学中,生物信息学方法及应用尚未得到足够重视。作者结合临床生物信息学发展现状及未来趋势,探讨了临床生物信息学学科在临床医学教学及转化研究中的作用。     

基因打靶技术研究及其应用

基因打靶技术是20世纪80年代发展起来的新技术,是一种利用DNA同源重组原理和胚胎干细胞（embryonic stem ceils,ESCs）技术按定向组合的方式改变生物活体遗传信息的实验手段,具有定位性强、打靶后新的基因随染色体DNA稳定遗传的特点,其方法包括基因敲除、基因敲人、点突变、缺失突变、染色体组大片段删除等,相关的基因工程技术包括转基因、基因沉默和基因捕获等。基因打靶技术为生命科学、基因组学和疾病治疗等领域的研究提供了强大的工具。     

生物塑化技术及其在医学影像学教学中的应用

生物塑化技术 (Ｐｌａｓｔｉｎａｔｉｏｎ)是德国Ｈａｇｅｎｓ教授于 1 978年发明的 ,目前在解剖学、病理解剖学、胚胎学、影像学等领域的科研和教学中已有广泛的应用 ,特别是近年来随着切片制作技术的不断完善 ,使精细结构得以准确显示 ,得到了与ＣＴ、ＭＲＩ断面一一对应的断面解剖学资料 ,进一步扩大了生物塑化技术的应用范围 ,也使断面影像解剖学的教学过程更为具体和客观 ,可作为断面影像解剖学教学的一种有效方法。现将生物塑化技术的原理、特点和在教学中的应用介绍如下。1　生物塑化技术的原理其基本原理是选用多聚化合物作为生物塑…     

高效毛细管电泳技术近年在中药分析中的应用

从中药分析、鉴别和对映体拆分等三个方面综述了毛细血管电泳在近2年来的研究进展。随着现代科技的飞速发展，中药分析技术（TLC、HPLC、GC、UV、IR、NMR等）取得了长足的进步，近年来毛细血管电泳技术得到了快速应用和发展，为中药质量评价提供了经有力的工具。与前面技术相比，毛细血管电泳显示出高效、快速、简便等特点和优势，作为一种新型技术，其必将在中药领域有着广阔的前景。     

生物样品处理技术研究进展与策略

生物样品主要包括生物组织、体液、血液、细胞等,具有成分复杂、活性成分含量高、保存时间短及干扰物质多等特点。在进行生物科学研究时,往往需要对各种生物样品进行处理,以获得目标分析物。常用的样品处理方法有萃取法,膜分离法和色谱法等。随着科技手段的进步,这些传统的方法被不断地改进与创新,在操作过程的简易化、分离提取的高效性和应用的广泛性上获得了极大的提高。本文针对生物样品处理技术在近些年来的研究报道进行了综述,包括技术的特点、方法及其在生物学上的应用。最后预测了其在空间生物学上的应用前景。     

GPU计算及其在生物医学研究中的应用

高性能计算是现代生物医学研究的重要工具和手段,传统的基于通用处理器（CPU）的计算机已很难满足生物医学研究对计算性能、效率和成本等多方面的综合性要求。近年来,图形处理器（GPU）计算技术异军突起,成为高性能计算领域的研究热点。本文介绍了GPU计算的基本概念、编程方法和特点,总结和讨论了GPU计算在生物医学中的应用现状和存在问题。最后,结合实际情况提出了利用GPU计算的一些研究工作设想。     

大数据概念在医学影像中的应用探索

大数据(big data)概念的兴起是随着信息技术和统计技术的发展而来的,在商业和社会科学领域展现了一定的应用价值,在健康领域的应用也初步得到认可.但由于医学影像专业的特点,大数据的应用仍处于初步探索阶段.本文对大数据在医学影像学领域的应用进展作一综述.     

多花木兰应用价值及丰产栽培技术研究

多花木兰是一种起源于热带、亚热带的多年生豆科植物.耐旱、耐酸、耐瘠薄、生物量大、营养价值高。是优良的饲用灌木树种。本文介绍了多花木兰的生物生态学特性和抗性强的特点。综述了多花木兰在水土保持等方面的应用价值。且建议对多花木兰的刈割技术做进一步的研究。并总结出一套饲用型多花木兰优质丰产栽培技术。     

定量成像生物标志物的计量标准

正摘要尽管影像工作者努力开发和评估定量成像生物标志物(QIB),但由于界定技术性能及统计学概念的术语或者方法的应用不连续或不准确等原因,QIB的发展和应用受到限制。技术性能是评价怎样在控制纳入标准的情况下对参考物和受试者进行实验的一种指标。本文复习了一些相关统计概念,描述了用于评估和比较QIB的方法,并讨论了一些有关生物标记成像的技术性能问题。连续且准确的应用术语及     

系统生物技术——组学时代的代谢工程

高通量实验技术的广泛应用产生了海量数据,利用生物信息学工具整合这些数据,加深了人们对细菌生理活动规律的认识,系统生物学应运而生.系统生物学的出现使代谢工程从局部通路水平上升到整体水平,代谢工程也因此进入了新的发展阶段--系统生物技术时代.系统生物技术通过整合各个层次组学数据,建立数学模型,或通过比较不同菌株或同一菌株在不同条件下基因组、转录组、蛋白组或代谢组的差异以阐明生命活动规律,在此基础上,对影响表型的靶基因进行改造,得到符合预期的表型.随着新的高通量实验技术的不断运用以及生物信息学的发展,系统生物技术必将取得更大进步.     

AQME: A forensic mitochondrial DNA analysis tool for next-generation sequencing data

The feasibility of generating mitochondrial DNA (mtDNA) data has expanded considerably with the advent of next-generation sequencing (NGS), specifically in the generation of entire mtDNA genome (mitogenome) sequences. However, the analysis of these data has emerged as the greatest challenge to implementation in forensics. To address this need, a custom toolkit for use in the CLC Genomics Workbench (QIAGEN, Hilden, Germany) was developed through a collaborative effort between the Armed Forces Medical Examiner System − Armed Forces DNA Identification Laboratory (AFMES-AFDIL) and QIAGEN Bioinformatics. The AFDIL-QIAGEN mtDNA Expert, or AQME, generates an editable mtDNA profile that employs forensic conventions and includes the interpretation range required for mtDNA data reporting. AQME also integrates an mtDNA haplogroup estimate into the analysis workflow, which provides the analyst with phylogenetic nomenclature guidance and a profile quality check without the use of an external tool. Supplemental AQME outputs such as nucleotide-per-position metrics, configurable export files, and an audit trail are produced to assist the analyst during review. AQME is applied to standard CLC outputs and thus can be incorporated into any mtDNA bioinformatics pipeline within CLC regardless of sample type, library preparation or NGS platform.An evaluation of AQME was performed to demonstrate its functionality and reliability for the analysis of mitogenome NGS data. The study analyzed Illumina mitogenome data from 21 samples (including associated controls) of varying quality and sample preparations with the AQME toolkit. A total of 211 tool edits were automatically applied to 130 of the 698 total variants reported in an effort to adhere to forensic nomenclature. Although additional manual edits were required for three samples, supplemental tools such as mtDNA haplogroup estimation assisted in identifying and guiding these necessary modifications to the AQME-generated profile. Along with profile generation, AQME reported accurate haplogroups for 18 of the 19 samples analyzed. The single errant haplogroup assignment, although phylogenetically close, identified a bug that only affects partial mitogenome data. Future adjustments to AQME’s haplogrouping tool will address this bug as well as enhance the overall scoring strategy to better refine and automate haplogroup assignments. As NGS enables broader use of the mtDNA locus in forensics, the availability of AQME and other forensic-focused mtDNA analysis tools will ease the transition and further support mitogenome analysis within routine casework. Toward this end, the AFMES-AFDIL has utilized the AQME toolbox in conjunction with the CLC Genomics Workbench to successfully validate and implement two NGS mitogenome methods.     

颅内囊状未破裂动脉瘤MRI影像标注专家共识

人工智能(AI)技术的不断发展使得影像数据分析更加精准,由此对大数据的规范化使用提出了更高要求。准确标注是实现数据信息价值最大化的重要前提,直接影响AI模型的应用效能。目前AI技术已在颅内动脉瘤检出及破裂风险评估等方面开展研究。为了规范颅内动脉瘤MRI数据的标注操作及处理流程,中国女医师协会医学影像专委会及中国脑动脉瘤智能影像诊治评估协作组联合人工智能产学研领域的专家,经过反复讨论,提出颅内囊状未破裂动脉瘤的MRI标注初步指导意见,为建设该病的影像数据库提供有力保障,从而推动AI在临床的实际应用。     

Massively parallel sequencing for the forensic scientist – sequencing archived amplified products of AmpFlSTR Identifiler and PowerPlex Y multiplex kits to capture additional information

In the last few years the cost and ease of massively parallel sequencing (MPS) has reduced dramatically to the point that it can now be considered as a tool for use in forensic case work. An important consideration for the implementation of any new forensic technology is the ability to remain compatible with previous technology. During this study we sequenced the amplicons of two commercial forensic short tandem repeat (STR) multiplexes AmpFlSTR Identifiler and PowerPlex Y using the Illumina MiSeq and Ion PGM Sequencer (Life Technologies) and characterised the sequence data from a forensic perspective. Using the MPS data from both platforms we determined the STR genotypes of forensic samples and found previously undocumented sequence variation in seven STR alleles. By characterising features of the DNA sequence profiles, such as stutter and locus imbalance we identified areas for future development that will be needed prior to casework implementation. The rapid development of this technology has meant many in the forensic community have been ‘left behind’. We also provide an explanation, for forensic scientists, of what is happening at the different stages of the MPS workflow, from library preparation through to bioinformatics, and how this may affect the results.     

Population-based imaging biobanks as source of big data

Advances of computational sciences over the last decades have enabled the introduction of novel methodological approaches in biomedical research. Acquiring extensive and comprehensive data about a research subject and subsequently extracting significant information has opened new possibilities in gaining insight into biological and medical processes. This so-called big data approach has recently found entrance into medical imaging and numerous epidemiological studies have been implementing advanced imaging to identify imaging biomarkers that provide information about physiological processes, including normal development and aging but also on the development of pathological disease states. The purpose of this article is to present existing epidemiological imaging studies and to discuss opportunities, methodological and organizational aspects, and challenges that population imaging poses to the field of big data research.     

BioSun2.0:一个综合性的辅助分子生物学实验设计软件

我们曾于2004年推出了计算机辅助分子生物学实验设计的软件系统BioSun 1．0，该系统提供了较为全面的数据处理与分析功能。为了更好地服务于生物医学工作者，我们对该软件系统进行了升级，推出了2．0版本，新增的功能主要有：基于Blast的多种形式的序列比对、基于ClustalW的多序列比对与进化树构建、蛋白质三维结构展示、基于RNAfold的RNA二级结构预测和序列格式转换等。通过与商业化综合性的生物信息学软件系统DNA-SIS MAX2．05、DNAStar5．0、VectorNTI9．1和BioEdit7．0的比较发现，BioSun2．0具有操作简便、功能众多和性价比高等特点，能够满足生物医学实验室的常规需求。     

Integration of PACS and HIS into the workflow of a nuclear medicine department. Experience in Regensburg

AIM: The development of new diagnostic techniques and the implementation of a modern quality control management system requires the continuous adaptation of existing data processing tools to the nuclear medicine diagnostic workflow. Furthermore, PACS connected to HIS facilitates and enhances the transfer of data and pictures, and satisfies the legal requirements for data retention as regulated by law. Therefore, the aim of this work is to present the architecture, structure and results of such a system newly installed in a department of nuclear medicine. METHODS: Initially, the nuclear medicine workflow was carefully analyzed and each step was correlated to the corresponding module. The standard SAP R/3 and IS-H/IS-H(*)med based software used for patient administration at the University of Regensburg Hospital was adapted to the needs of the Nuclear Medicine Department. The networking of the imaging systems was done by integration of a PACS. Finally, the PACS was connected to the HIS to allow the attachment of images to the medical report. RESULTS, CONCLUSION: By connecting the HIS to the nuclear medicine PACS, the workflow was significantly improved. The data management sequence starting at the reception desk, continuing through the nuclear medical examination, to the physician's final written and image report is clearly structured. Although high demands exist on technical support and administration the integration of PACS and HIS into the nuclear medicine workflow leads to enhanced efficiency and reduction in hospital costs. Patient and data management are considerably improved in this way.     

Image-assisted knowledge discovery and decision support in radiation therapy planning.

The need for quantified knowledge and decision-support tools to handle complex radiation therapy (RT) imaging and informatics data is becoming steadily apparent. Lessons can be learned from current CAD applications in radiology. This paper proposes a methodology to develop this quantified knowledge and decision-support tools to facilitate RT treatment planning. The methodology is applied to cancer patient cases treated by intensity modulated radiation therapy (IMRT). The use of the "inverse treatment planning" and imaging intensive nature of IMRT allows for the development of such image-assisted tools for supporting decision-making thus providing better workflow efficiency and more precise dose predictions.     

Big Data and Radiology Research

Our understanding of human health may be significantly enhanced in the near future because of the unprecedented volume of digitized health care data and the availability of artificial intelligence to mine these data for correlations that could drive new research hypotheses and improved patient care. Observational studies and randomized trials are traditional methods to generate and test hypotheses. Another way to generate research hypotheses is to use big data to reveal patterns and associations for further study. In 2018, the National Institutes of Health unveiled its Strategic Plan for Data Science, which includes a far-reaching plan for the use of big data to stimulate new research discoveries. Both researchers and physicians will need to learn and apply new skills in understanding the use of artificial intelligence and other tools, as well as in the direct application of data collection and mining in their own practices and patients.