代谢综合征风险、趋势预测和干预模型的构建

结合基因组学数据与生物学背景,利用数学与统计的方法研究代谢综合征的致病机理。首先,利用变异系数筛选出信息含量较高的数据,并且利用变异基因频数统计的方法确定高频变异基因。通过查阅相关文献和数据库可知,大部分高频变异基因都与代谢综合征有关。随后,研究高频变异基因对其他基因的调控情况,并且由此构建出高频变异基因的调控网络以及网络内部的协同和拮抗作用。最后,提出基于调控网络的患病风险预测模型,由此提供预防或治疗方案。     

GroupTracker: Video tracking system for multiple animals under severe occlusion

Quantitative analysis of behaviors shown by interacting multiple animals can provide a key for revealing high-order functions of their nervous systems. To resolve these complex behaviors, a video tracking system that preserves individual identity even under severe overlap in positions, i.e., occlusion, is needed. We developed GroupTracker, a multiple animal tracking system that accurately tracks individuals even under severe occlusion. As maximum likelihood estimation of Gaussian mixture model whose components can severely overlap is theoretically an ill-posed problem, we devised an expectation–maximization scheme with additional constraints on the eigenvalues of the covariance matrix of the mixture components. Our system was shown to accurately track multiple medaka (Oryzias latipes) which freely swim around in three dimensions and frequently overlap each other. As an accurate multiple animal tracking system, GroupTracker will contribute to revealing unexplored structures and patterns behind animal interactions. The Java source code of GroupTracker is available at https://sites.google.com/site/fukunagatsu/software/group-tracker.     

Informatics methods to enable sharing of quantitative imaging research data

Introduction

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community.

Methods

We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN.

Results

There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network.

Conclusions

As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers.     

基于材料基因组计划的计算和数据方法

 材料基因组计划的核心理念,是通过计算、数据和实验“三位一体”的方式,变革传统的主要基于经验和实验的“试错法”材料研发模式,把发现、开发、生产和应用新材料的速度提高到目前的两倍。它旨在建立一个新的以计算模拟和理论预测优先、实验验证在后的新材料研发文化,从而取代现有的以经验和实验为主的材料研发的模式。本文论述如何通过计算和数据的方法加快新材料研发,介绍帮助加快新材料发现的高通量集成计算基础平台和软件框架MatCloud。     

从罕见内分泌疾病研究看精准内分泌学的发展

 罕见病指患病率低于7/10000的疾病,是精准医学研究的重要生物学模板和理想平台。多发性内分泌腺瘤综合征（MEN）、新生儿糖尿病、库欣氏综合征、先天性瘦素缺乏症等多种罕见内分泌疾病研究都反映了精准医学在内分泌领域的作用。在此基础上,本文进一步概括精准内分泌学的发展方向,在骨质疏松症、糖尿病、肥胖等内分泌疾病中应用精准医学,有助于对个体发病风险进行评估和预防,对复杂疾病进行精确诊断及分型,对疾病进行个体化治疗。此外,医学信息学在精准内分泌学领域的应用不仅可推动大数据平台建设,也提供了针对多因素复杂内分泌疾病的诊疗新思路。随着分子生物学技术的发展,建立罕见内分泌疾病的基因型和表型大数据平台,对于实现罕见内分泌疾病的精准诊疗具有重要意义。     

安全信息学原理的体系构建

 从安全信息学、安全学和系统安全的高度与角度出发,阐述了3种安全信息现象、安全信息规律和安全信息科学阶段及其对应关系。根据安全信息现象总结出6类安全信息学科学原理,提出了由安全人体信息原理、安全物质信息原理、安全环境信息原理、安全管理信息原理、安全社会信息原理和安全系统信息原理等6条一级安全信息学原理和30条二级安全信息学原理组成的安全信息学原理体系。论述了各原理的内涵,构建了安全信息学原理的蜂巢结构,阐述了各级安全信息学原理在蜂巢结构中的联系与发展。研究表明,以系统安全及安全学为背景可以构建安全信息学下的一个全新安全科学原理体系,丰富完善了安全信息学的基础理论。     

社会计算在信息安全中的应用

在互联网日益向人们日常生活渗透和国际重大政治事件的双重驱动下,社会计算和信息安全这2个学科(群)都得到了迅速发展,它们的研究方向开始重叠。论文扼要阐述了社会计算及其相关学科的发展历史、研究领域及方法,举例描述了其中的"情报与安全信息学"和复杂网络分析在信息安全若干新兴领域,主要是舆情分析和Web2.0安全方面的应用。这些例子表明社会计算等学科为信息安全工作者提供了新的视野、建模方法和处理数据的工具。     

The Limited Predictive Power of the Pauling Rules

The Pauling rules have been used for decades to rationalise the crystal structures of ionic compounds. Despite their importance, there has been no statistical assessment of the performances of these five empirical rules so far. Here, we rigorously and automatically test all five Pauling rules for a large data set of around 5000 known oxides. We discuss each Pauling rule separately, stressing their limits and range of application in terms of chemistries and structures. We conclude that only 13 % of the oxides simultaneously satisfy the last four rules, indicating a much lower predictive power than expected.     

Teleporting N-qubit unknown atomic state by utilizing the V-type three-level atom

Realizing the teleportation of quantum state, especially the teleportation of N-qubit quantum state, is of great importance in quantum information. In this paper, Raman-interaction of the V-type degenerate three-level atom and single-mode cavity field is studied by utilizing complete quantum theory. Then a new scheme for teleporting N-qubit unknown atomic state via Raman-interaction of the V-type degenerate three-level atom with a single-mode cavity field is proposed, which is based upon the complete quantu...