A New Online Computational Biology Curriculum

A recent proliferation of Massive Open Online Courses (MOOCs) and other web-based educational resources has greatly increased the potential for effective self-study in many fields. This article introduces a catalog of several hundred free video courses of potential interest to those wishing to expand their knowledge of bioinformatics and computational biology. The courses are organized into eleven subject areas modeled on university departments and are accompanied by commentary and career advice.     

dbOGAP - An Integrated Bioinformatics Resource for Protein O-GlcNAcylation

Background  

Protein O-GlcNAcylation (or O-GlcNAc-ylation) is an O-linked glycosylation involving the transfer of β-N-acetylglucosamine to the hydroxyl group of serine or threonine residues of proteins. Growing evidences suggest that protein O-GlcNAcylation is common and is analogous to phosphorylation in modulating broad ranges of biological processes. However, compared to phosphorylation, the amount of protein O-GlcNAcylation data is relatively limited and its annotation in databases is scarce. Furthermore, a bioinformatics resource for O-GlcNAcylation is lacking, and an O-GlcNAcylation site prediction tool is much needed.     

An International Bioinformatics Infrastructure to Underpin the Arabidopsis Community

The future bioinformatics needs of the Arabidopsis community as well as those of other scientific communities that depend on Arabidopsis resources were discussed at a pair of recent meetings held by the Multinational Arabidopsis Steering Committee and the North American Arabidopsis Steering Committee. There are extensive tools and resources for information storage, curation, and retrieval of Arabidopsis data that have been developed over recent years primarily through the activities of The Arabidopsis Information Resource, the Nottingham Arabidopsis Stock Centre, and the Arabidopsis Biological Resource Center, among others. However, the rapid expansion in many data types, the international basis of the Arabidopsis community, and changing priorities of the funding agencies all suggest the need for changes in the way informatics infrastructure is developed and maintained. We propose that there is a need for a single core resource that is integrated into a larger international consortium of investigators. We envision this to consist of a distributed system of data, tools, and resources, accessed via a single information portal and funded by a variety of sources, under shared international management of an International Arabidopsis Informatics Consortium (IAIC). This article outlines the proposal for the development, management, operations, and continued funding for the IAIC.The Multinational Arabidopsis Steering Committee (MASC) and the North American Arabidopsis Steering Committee (NAASC) hosted workshops in Nottingham, UK (April 15 to 16, 2010) and Washington DC (May 10 to 11, 2010) to consider the future bioinformatics needs of the Arabidopsis community as well as other science communities that depend vitally on Arabidopsis resources. The outcomes of both workshops were presented and discussed at the International Conference on Arabidopsis Research (ICAR) in Yokohama, Japan. The focus of the workshops was on Arabidopsis because of its unique and essential role as a reference organism for all seed plant species. The development of the highly annotated “gold standard” Arabidopsis genome sequence has been an invaluable resource for plant and crop sciences. This platform provides important information and working practices for other species and for comparative genomic and evolutionary studies. Arabidopsis tools and resources for information storage, curation, and retrieval have been developed over recent years primarily through the activities of The Arabidopsis Information Resource (TAIR), the Nottingham Arabidopsis Stock Centre (NASC), and the Arabidopsis Biological Resource Center, among others. However, the Arabidopsis community and funding agencies recognize the need for a single data management infrastructure. The key challenge is to develop and fund this resource in a sustainable and transparent manner.Global challenges surrounding food and energy security require intelligent plant breeding strategies that will be dependent on a central Arabidopsis information resource to aid our understanding of gene function and associated phenotype in many different environments. The knowledge accrued in Arabidopsis informs our understanding of the genetic basis of plant processes and crop traits. To date, this has accumulated primarily through analysis of single genes. However, gene products do not act alone but rather in complex interacting networks. Thus, the challenge for the Arabidopsis community is to understand this higher level of complexity, to a significant extent through the application of new high volume, quantitative experimental techniques. The goals of these efforts are to develop gene/protein/metabolite networks that will enable systems-level modeling of plant processes and ultimately to translate these findings to crop plants. To achieve these goals, we must develop novel approaches to data management, integration, and access.The UK workshop addressed three principal issues: the types of data generated by the Arabidopsis community, the types of data used by the community, and future needs of the community. The objective was to produce recommendations for the type of infrastructure necessary to address the challenges and opportunities associated with the application of new technologies and recommendations for a sustainable funding model to support this infrastructure. These recommendations were considered and expanded upon at the US workshop with the ultimate goal of generating solutions to the issues discussed in the first meeting. It was recognized that cohesive, cooperative, and long-term international collaboration will be critical to successfully maintain an Arabidopsis database infrastructure that is essential for plant biology research worldwide.The workshop participants concluded that there is a continued need for a central Arabidopsis information resource, based on the productivity of the Arabidopsis community and the critical importance of the findings generated by this community. For example, ∼3000 Arabidopsis publications are currently published in peer-reviewed journals each year, a nearly 10-fold increase since the early 1990s; and in 2009, TAIR was accessed by 335,692 unique visitors and had nearly 20 million page views. Furthermore, the importance of a current, well-organized, and carefully curated Arabidopsis genome to researchers studying other plants, including crops, cannot be overstated. In the future, this resource should be part of a larger infrastructure that would be dynamic and responsive to new directions in plant biology research.     

隐马尔科夫过程在生物信息学中的应用

隐马尔科夫过程（hidden markov model,简称HMM）是20世纪70年代提出来的一种统计方法,以前主要用于语音识别。1989年Churchill将其引入计算生物学。目前,HMM是生物信息学中应用比较广泛的一种统计方法,主要用于：线性序列分析、模型分析、基因发现等方面。对HMM进行了简明扼要的描述,并对其在上述几个方面的应用作一概略介绍。     

生物信息学

生物信息学是采用计算机技术和信息论方法研究生命科学中各种生物信息的表达;采集,储存,传递,检索,分析和解读的科学,是现代生命科学与信息科学,计算机科学,数学,统计学,物理学,化学等学科相互渗透和高度交叉形成的学科,本文简要介绍了现代生物信息学的主要研究领域。     

Bioinformatics

Bioinformatics is an interdisciplinary field that blends computer science and biostatistics with biological and biomedical sciences such as biochemistry, cell biology, developmental biology, genetics, genomics, and physiology. An important goal of bioinformatics is to facilitate the management, analysis, and interpretation of data from biological experiments and observational studies. The goal of this review is to introduce some of the important concepts in bioinformatics that must be considered when planning and executing a modern biological research study. We review database resources as well as data mining software tools.     

生物信息学

即将到来的21世纪,人类将全面进入生命科学时代和信息时代。生物信息学(Ｂｉｏｉｎｆｏｒｍａｔｉｃｓ)正成为当今备受关注的新型产业的支撑点。生物信息学是以生物大分子(ＤＮＡ和蛋白质)为分析对象,运用数理方法对其进行分析,来理解生物大分子的生物学意义。从国外近年研究进展来看,它已成为崭新的生物工程、医药产业和高科技农业的巨大推动力。有科学家预言,现今的生物科学在信息学的结合和推动下,将会发生一场革....     

Bioinformatics 2000

A report from the Bioinformatics 2000 conference [], held in Elsinore, Denmark, 27-30 April, 2000.     

Open discovery: An integrated live Linux platform of Bioinformatics tools

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery ‐ a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD.     

An Object-Oriented Programming System for the Integration of Internet-Based Bioinformatics Resources

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.