A Dynamic Workflow Approach for the Integration of Bioinformatics Services

Modern biological and chemical studies rely on life science databases as well as sophisticated software tools (e.g., homology search tools, modeling and visualization tools). These tools often have to be combined and integrated in order to support a given study. SIBIOS (System for the Integration of Bioinformatics Services) serves this purpose. The services are both life science database search services and software tools. The task engine is the core component of SIBIOS. It supports the execution of dynamic workflows that incorporate multiple bioinformatics services. The architecture of SIBIOS, the approaches to addressing the heterogeneity as well as interoperability of bioinformatics services, including data integration are presented in this paper.     

Facilities that make the PDB data collection more powerful

We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF‐formatted files with a computer‐readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB‐REDO collection of reanalyzed and re‐refined protein structures that were solved by X‐ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.     

Pise: software for building bioinformatics webs

Pise is interface construction software for bioinformatics applications that run by command-line operations. It creates common, easy-to-use interfaces to these applications for the Web, or other uses. It is adaptable to new bioinformatics tools, and offers program chaining, Unix system batch and other controls, making it an attractive method for building and using your own bioinformatics web services.     

BioManager: the use of a bioinformatics web application as a teaching tool in undergraduate bioinformatics training

The completion of the human genome project, and other genome sequencing projects, has spearheaded the emergence of the field of bioinformatics. Using computer programs to analyse DNA and protein information has become an important area of life science research and development. While it is not necessary for most life science researchers to develop specialist bioinformatic skills (including software development), basic skills in the application of common bioinformatics software and the effective interpretation of results are increasingly required by all life science researchers. Training in bioinformatics is increasingly occurring within the university system as part of existing undergraduate science and specialist degrees. One difficulty in bioinformatics education is the sheer number of software programs required in order to provide a thorough grounding in the subject to the student. Teaching requires either a well-maintained internal server with all the required software, properly interfacing with student terminals, and with sufficient capacity to handle multiple simultaneous requests, or it requires the individual installation and maintenance of every piece of software on each computer. In both cases, there are difficult issues regarding site maintenance and accessibility. In this article, we discuss the use of BioManager, a web-based bioinformatics application integrating a variety of common bioinformatics tools, for teaching, including its role as the main bioinformatics training tool in some Australian and international universities. We discuss some of the issues with using a bioinformatics resource primarily created for research in an undergraduate teaching environment.     

Software agents in molecular computational biology

Progress made in applying agent systems to molecular computational biology is reviewed and strategies by which to exploit agent technology to greater advantage are investigated. Communities of software agents could play an important role in helping genome scientists design reagents for future research. The advent of genome sequencing in cattle and swine increases the complexity of data analysis required to conduct research in livestock genomics. Databases are always expanding and semantic differences among data are common. Agent platforms have been developed to deal with generic issues such as agent communication, life cycle management and advertisement of services (white and yellow pages). This frees computational biologists from the drudgery of having to re-invent the wheel on these common chores, giving them more time to focus on biology and bioinformatics. Agent platforms that comply with the Foundation for Intelligent Physical Agents (FIPA) standards are able to interoperate. In other words, agents developed on different platforms can communicate and cooperate with one another if domain-specific higher-level communication protocol details are agreed upon between different agent developers. Many software agent platforms are peer-to-peer, which means that even if some of the agents and data repositories are temporarily unavailable, a subset of the goals of the system can still be met. Past use of software agents in bioinformatics indicates that an agent approach should prove fruitful. Examination of current problems in bioinformatics indicates that existing agent platforms should be adaptable to novel situations.     

Open source tools and toolkits for bioinformatics: significance, and where are we?

This review summarizes important work in open-source bioinformatics software that has occurred over the past couple of years. The survey is intended to illustrate how programs and toolkits whose source code has been developed or released under an Open Source license have changed informatics-heavy areas of life science research. Rather than creating a comprehensive list of all tools developed over the last 2-3 years, we use a few selected projects encompassing toolkit libraries, analysis tools, data analysis environments and interoperability standards to show how freely available and modifiable open-source software can serve as the foundation for building important applications, analysis workflows and resources.     

生物信息学在昆虫学研究中的应用

随着深度测序和基因芯片技术的不断发展,基因组、转录组、表达谱数据大量积累。目前,至少有10多个昆虫的基因组已被测序,30多个昆虫的转录组数据被报道。显然,传统的生物统计学方法无法处理如此海量的生物数据。量变引发质变,生物数据的大量积累催生了一门新兴学科,生物信息学。生物信息学融合了统计学、信息科学和生物学等各学科的理论和研究内容,在医学、基础生物学、农业科学以及昆虫学等方面获得了广泛的应用。生物信息学的目标是存储数据、管理数据和数据挖掘。因此,建立维护生物学数据库、设计开发基于模式识别、机器学习、数据挖掘等方法的生物软件,以及运用上述工具进行深度的数据挖掘,是生物信息学的重要研究内容。本文首先简要介绍了生物信息学的历史、研究现状及其在昆虫学科中的应用,然后综述了昆虫基因组学和转录组学的研究进展,最后对生物信息学在昆虫学研究中的应用前景进行了展望。     

Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.     

Scalable Data Analysis in Proteomics and Metabolomics Using BioContainers and Workflows Engines

The recent improvements in mass spectrometry instruments and new analytical methods are increasing the intersection between proteomics and big data science. In addition, bioinformatics analysis is becoming increasingly complex and convoluted, involving multiple algorithms and tools. A wide variety of methods and software tools have been developed for computational proteomics and metabolomics during recent years, and this trend is likely to continue. However, most of the computational proteomics and metabolomics tools are designed as single‐tiered software application where the analytics tasks cannot be distributed, limiting the scalability and reproducibility of the data analysis. In this paper the key steps of metabolomics and proteomics data processing, including the main tools and software used to perform the data analysis, are summarized. The combination of software containers with workflows environments for large‐scale metabolomics and proteomics analysis is discussed. Finally, a new approach for reproducible and large‐scale data analysis based on BioContainers and two of the most popular workflow environments, Galaxy and Nextflow, is introduced to the proteomics and metabolomics communities.     

肠道噬菌体组生物信息学分析方法的研究进展

噬菌体是感染细菌的病毒,广泛存在于各类环境中。由于传统实验研究的局限性及噬菌体基因的特异性,导致对肠道噬菌体的研究很少。随着宏基因组测序技术的发展和各种生物信息分析软件的开发,可以通过噬菌体组学,加深对肠道噬菌体的认识。噬菌体组分析流程主要包括原始数据质量控制和预处理,病毒基因组序列的拼接组装,类病毒颗粒的筛选和系统分类注释以及进化分析和预测相应宿主细菌。本文对噬菌体组分析流程和其中所需要的常用生物信息分析工具和数据库进行详细的介绍,可以为肠道噬菌体研究以及相关的研究人员提供参考。     

Model-driven user interfaces for bioinformatics data resources: regenerating the wheel as an alternative to reinventing it

Background  

The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories. Interfaces developed by public laboratories are often created with limited developer resources. In such environments, reducing the time spent on creating user interfaces allows for a better deployment of resources for specialised tasks, such as data integration or analysis. Laboratories maintaining data resources are challenged to reconcile requirements for software that is reliable, functional and flexible with limitations on software development resources.     

探讨生物信息标准化研究

针对生物信息在国内的发展现状,提出研制生物信息标准的需求。首先从生物数据资源收集、管理规范入手,在此基础上进行了生物信息资源管理体系的研究,最后讨论了共享交流软件系统的开发和生物信息数据挖掘,并期望通过以上研究能为我国生物信息学相关标准的制定提供参考和依据。     

CRISPR相关生物信息学基础

成簇规律间隔短回文序列（clustered regularly interspaced short palindromic repeats,CRISPR）是细菌和古细菌在不断进化的过程中获得的一种适应性免疫防御机制,该结构与一些功能相关的蛋白质（CRISPR associated, Cas）合称CRISPR Cas系统。由于其致突变效率高、操作简单及成本较低的特点,近年来对CRISPR/Cas系统的研究获得越来越广泛的关注。该系统迅速在各领域中得到广泛应用,被认为是一种具有广阔应用前景的基因组定点改造分子工具。但是,该系统存在脱靶效应、测序数据分析等挑战。为此,许多研究者开发出各种软件解决以上问题。本文着重从生物信息学的角度出发,对CRISPR/Cas系统中sgRNA的设计软件、CRISPR全基因组筛选功能基因的测序数据分析软件以及CRISPR在生物信息学中的运用作一系统综述。     

The FaceBase Consortium: a comprehensive program to facilitate craniofacial research

The FaceBase Consortium consists of ten interlinked research and technology projects whose goal is to generate craniofacial research data and technology for use by the research community through a central data management and integrated bioinformatics hub. Funded by the National Institute of Dental and Craniofacial Research (NIDCR) and currently focused on studying the development of the middle region of the face, the Consortium will produce comprehensive datasets of global gene expression patterns, regulatory elements and sequencing; will generate anatomical and molecular atlases; will provide human normative facial data and other phenotypes; conduct follow up studies of a completed genome-wide association study; generate independent data on the genetics of craniofacial development, build repositories of animal models and of human samples and data for community access and analysis; and will develop software tools and animal models for analyzing and functionally testing and integrating these data. The FaceBase website (http://www.facebase.org) will serve as a web home for these efforts, providing interactive tools for exploring these datasets, together with discussion forums and other services to support and foster collaboration within the craniofacial research community.     

国内外生物信息学数据库服务新进展

生物信息学是生命科学中最活跃的领域之一. 各类生物信息学数据库在近年不断出现,其规模呈爆炸趋势增长,同时数据结构日趋复杂. 目前生物信息学数据库服务已实现了高度的计算机和网络化. 算法和软件的进步、数据库的一体化、服务器-客户模式的建立使之成为生物、医药、农业等学科的强有力工具. 在国内北京大学物理化学研究所于1996年建立了第一家生物信息学网络服务器. 现已为国内外科学家提供了7万余次服务,在国际上具有一定影响.     

生物信息学在工业生物催化研究中的应用

随着石油等不可再生资源的日益减少以及环境污染问题的日益严重,应用工业生物催化技术改造或取代传统化工工艺已经成为新世纪化学工业可持续发展的研究热点。工业生物催化技术的研究对象是生物催化剂及其催化过程。近来,利用生物信息学技术进行工业生物催化研究已经越来越受到人们的重视。随着工业生物催化的发展,生物信息学将直接指导并加快新型高效生物催化剂的发现及功能改造进程。     

Bioinformatics and data mining in proteomics

Proteomic studies involve the identification as well as qualitative and quantitative comparison of proteins expressed under different conditions, and elucidation of their properties and functions, usually in a large-scale, high-throughput format. The high dimensionality of data generated from these studies will require the development of improved bioinformatics tools and data-mining approaches for efficient and accurate data analysis of biological specimens from healthy and diseased individuals. Mining large proteomics data sets provides a better understanding of the complexities between the normal and abnormal cell proteome of various biological systems, including environmental hazards, infectious agents (bioterrorism) and cancers. This review will shed light on recent developments in bioinformatics and data-mining approaches, and their limitations when applied to proteomics data sets, in order to strengthen the interdependence between proteomic technologies and bioinformatics tools.     

面向生物信息学的工作流管理系统框架

生物信息学实验的实施通常需要整合多种类型的数据和工具,随着大量的web服务、算法程序和分析工具的出现,如何高效整合这些可用资源共同完成分析实验是当前生物信息学研究的重要内容之一,工作流技术已经成为解决这类问题的一种通用机制.然而,生物信息学工作流的实施涉及高通量数据的计算与存储,同时面临着资源异构性和分布性的挑战.本文首先介绍了生物信息学工作流的基本机制,然后阐述了面向生物信息学的工作流管理系统框架,最后讨论了框架应用中存在的问题和可能的解决途径.