A review of bioinformatics education in Germany

We describe the establishment of bioinformatics in Germany andgive an overview of current bioinformatics education in thiscountry, from the perspective of the practitioner. The aim ofthis study is to demonstrate development of a strong bioinformaticseducation at German universities and research institutes duringthe last years. Beginning with a definition of the multi-disciplinaryfield bioinformatics, we give a survey of government initiativesin Germany in support of this field, which resulted in a widespectrum of courses. To the best of our knowledge, we compileall ongoing courses at universities and research institutes.Five case studies featuring university courses with differenteducational focus illustrate the variety of efforts. In thiscontext we also discuss the main components of German bioinformaticscurricula. These components can be considered as the basic knowledgeof German bioinformaticians. We conclude by giving perspectivesfor further development of bioinformatics education.      

Bioinformatics in Sudan: Status and challenges case study: The National University-Sudan

The ever increasing applications of bioinformatics in providing effective interpretation of large and complex biological data require expertise in the use of sophisticated computational tools and advanced statistical tests, skills that are mostly lacking in the Sudanese research community. This can be attributed to paucity in the development and promotion of bioinformatics, lack of senior bioinformaticians, and the general status quo of inadequate research funding in Sudan. In this paper, we describe the challenges that have encountered the development of bioinformatics as a discipline in Sudan. Additionally, we highlight on specific actions that may help develop and promote its education and training. The paper takes the National University Biomedical Research Institute (NUBRI) as an example of an institute that has tackled many of these challenges and strives to drive powerful efforts in the development of bioinformatics in the country.     

A Methodological Framework for the Reconstruction of Contiguous Regions of Ancestral Genomes and Its Application to Mammalian Genomes

The reconstruction of ancestral genome architectures and gene orders from homologies between extant species is a long-standing problem, considered by both cytogeneticists and bioinformaticians. A comparison of the two approaches was recently investigated and discussed in a series of papers, sometimes with diverging points of view regarding the performance of these two approaches. We describe a general methodological framework for reconstructing ancestral genome segments from conserved syntenies in extant genomes. We show that this problem, from a computational point of view, is naturally related to physical mapping of chromosomes and benefits from using combinatorial tools developed in this scope. We develop this framework into a new reconstruction method considering conserved gene clusters with similar gene content, mimicking principles used in most cytogenetic studies, although on a different kind of data. We implement and apply it to datasets of mammalian genomes. We perform intensive theoretical and experimental comparisons with other bioinformatics methods for ancestral genome segments reconstruction. We show that the method that we propose is stable and reliable: it gives convergent results using several kinds of data at different levels of resolution, and all predicted ancestral regions are well supported. The results come eventually very close to cytogenetics studies. It suggests that the comparison of methods for ancestral genome reconstruction should include the algorithmic aspects of the methods as well as the disciplinary differences in data aquisition.     

中国在翻译后修饰的生物信息学研究领域的进展与前瞻

翻译后修饰在调控蛋白质构象变化、活性以及功能方面具有重要作用,并参与了几乎所有细胞通路和过程。蛋白质翻译后修饰的鉴定是阐明细胞内分子机理的基础。相对于劳动密集的、耗费时间的实验工作,利用各种生物信息学方法开展翻译后修饰预测,能够提供准确、简便和快速的研究方案,并产生有价值的信息为进一步实验研究提供参考。文章主要综述了中国生物信息学者在翻译后修饰生物信息学领域所取得的研究进展,包括修饰底物与位点预测的计算方法学设计与完善、在线或本地化工具的设计与维护、修饰相关数据库及数据资源的构建及基于修饰蛋白质组学数据的生物信息学分析。通过比较国内外的同类研究,发现优势和不足,并对未来的研究作出前瞻。     

BioMoby extensions to the Taverna workflow management and enactment software

Background  

As biology becomes an increasingly computational science, it is critical that we develop software tools that support not only bioinformaticians, but also bench biologists in their exploration of the vast and complex data-sets that continue to build from international genomic, proteomic, and systems-biology projects. The BioMoby interoperability system was created with the goal of facilitating the movement of data from one Web-based resource to another to fulfill the requirements of non-expert bioinformaticians. In parallel with the development of BioMoby, the European myGrid project was designing Taverna, a bioinformatics workflow design and enactment tool. Here we describe the marriage of these two projects in the form of a Taverna plug-in that provides access to many of BioMoby's features through the Taverna interface.     

Mind the gaps when using science to address conservation concerns

Conservation science and conservation action are assumed to have identical goals. However, in reality, there is a strong divide between research and practical conservation that has been mostly discussed with respect to the ‘knowing-doing gap’, i.e. the results from science are not being translated into practical management. In this commentary, we argue that there is not one but there are at least three different types of gaps impeding a positive impact of science on conservation: (1) the knowing-doing gap; (2) the thematic gap that exists between the topics addressed by conservation science and the problems faced in conservation; and (3) the disciplinary gap, i.e. the lack of communication and cooperation between different fields of science, e.g. between fundamental biodiversity research and conservation research. These different gaps have different origins and require different means to be overcome. In a survey, scientists from the field of conservation research (all contributing to this special issue on European grasslands) assessed the importance of these three gaps. They highlight that the disciplinary gap is just as relevant as the knowing-doing gap, while the importance of the thematic gap between practical conservation needs and theoretical conservation science is, in the view of the authors, of less importance. Also, the respondents identified the complexity of academic content in scientific publications as an additional cause for knowing-doing gaps. Based on our survey and various other studies analysing these gaps, we suggest two ways to overcome the gaps: if you consider yourself to be a conservation scientist make sure to address questions of relevance for conservation issues, if you are a scientist interested in fundamental issues, be open to mutual interaction and translation of scientific results with conservation scientists. The knowing-doing gap could be addressed by more readily translating the theoretical findings into practical advice. “Conservation Journals” could, for instance, require a second “Conservation Management Abstract”, which has to be published open-access, and back-to-back with the conventional abstract.     

The what, where, how and why of gene ontology--a primer for bioinformaticians

With high-throughput technologies providing vast amounts of data, it has become more important to provide systematic, quality annotations. The Gene Ontology (GO) project is the largest resource for cataloguing gene function. Nonetheless, its use is not yet ubiquitous and is still fraught with pitfalls. In this review, we provide a short primer to the GO for bioinformaticians. We summarize important aspects of the structure of the ontology, describe sources and types of functional annotations, survey measures of GO annotation similarity, review typical uses of GO and discuss other important considerations pertaining to the use of GO in bioinformatics applications.     

Chapter 14: Cancer Genome Analysis

Although there is great promise in the benefits to be obtained by analyzing cancer genomes, numerous challenges hinder different stages of the process, from the problem of sample preparation and the validation of the experimental techniques, to the interpretation of the results. This chapter specifically focuses on the technical issues associated with the bioinformatics analysis of cancer genome data. The main issues addressed are the use of database and software resources, the use of analysis workflows and the presentation of clinically relevant action items. We attempt to aid new developers in the field by describing the different stages of analysis and discussing current approaches, as well as by providing practical advice on how to access and use resources, and how to implement recommendations. Real cases from cancer genome projects are used as examples.

What to Learn in This Chapter

This chapter presents an overview of how cancer genomes can be analyzed, discussing some of the challenges involved and providing practical advice on how to address them. As the primary analysis of experimental data is described elsewhere (sequencing, alignment and variant calling), we will focus on the secondary analysis of the data, i.e., the selection of candidate driver genes, functional interpretation and the presentation of the results. Emphasis is placed on how to build applications that meet the needs of researchers, academics and clinicians. The general features of such applications are laid out, along with advice on their design and implementation. This document should serve as a starter guide for bioinformaticians interested in the analysis of cancer genomes, although we also hope that more experienced bioinformaticians will find interesting solutions to some key technical issues.

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

The GMOD Drupal bioinformatic server framework

MOTIVATION: Next-generation sequencing technologies have led to the widespread use of -omic applications. As a result, there is now a pronounced bioinformatic bottleneck. The general model organism database (GMOD) tool kit (http://gmod.org) has produced a number of resources aimed at addressing this issue. It lacks, however, a robust online solution that can deploy heterogeneous data and software within a Web content management system (CMS). RESULTS: We present a bioinformatic framework for the Drupal CMS. It consists of three modules. First, GMOD-DBSF is an application programming interface module for the Drupal CMS that simplifies the programming of bioinformatic Drupal modules. Second, the Drupal Bioinformatic Software Bench (biosoftware_bench) allows for a rapid and secure deployment of bioinformatic software. An innovative graphical user interface (GUI) guides both use and administration of the software, including the secure provision of pre-publication datasets. Third, we present genes4all_experiment, which exemplifies how our work supports the wider research community. Conclusion: Given the infrastructure presented here, the Drupal CMS may become a powerful new tool set for bioinformaticians. The GMOD-DBSF base module is an expandable community resource that decreases development time of Drupal modules for bioinformatics. The biosoftware_bench module can already enhance biologists' ability to mine their own data. The genes4all_experiment module has already been responsible for archiving of more than 150 studies of RNAi from Lepidoptera, which were previously unpublished. Availability and implementation: Implemented in PHP and Perl. Freely available under the GNU Public License 2 or later from http://gmod-dbsf.googlecode.com.     

A Primer on Metagenomics

Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics.     

A review of bioinformatics education in the UK

If the completion of the first draft of the human genome represents the coming of age of bioinformatics, then the emergence of bioinformatics as a university degree subject represents its establishment. In this paper bioinformatics as a subject for formal study is discussed, rather than as a subject for research, and a selection of the taught, mainly graduate, courses currently available in the UK are reviewed. Throughout, the author tries to draw parallels between the integration of bioinformatics into biomedical research and teaching today, and that of molecular biology, two decades ago. Others have made this analogy between these two relatively young disciplines. Although research sources are referenced, the author makes no pretence of objectivity. This article contains his opinions, and those of a number of current bioinformatics course organisers whose comments on the subject were solicited in advance specifically for this paper. The course organisers kindly advised how they planned their curricula, and described the special strengths of their programmes. Comments from present and former students of several bioinformatics degree programmes were also solicited. Except where individuals are directly quoted, any opinions expressed herein should be considered the author's. Compared with its sister piece [Marion Zatz, in previous issue of Briefings in Bioinformatics pp. 353], this paper is less about funding policy--which, in the UK, has lately (if belatedly) been more generous towards bioinformatics teaching--than it is about practice and content; the requirements of the bioinformatics research communities, the corresponding emphases of bioinformatics courses, and the general market for holders of bioinformatics degrees. Individual courses are cited throughout as examples, but the final section contains a full annotated listing with URL addresses. Based on the author's own experience of practising and teaching bioinformatics, he describes the skills he believes will be most useful to bioinformaticians in the near future and suggests ways to prepare students of bioinformatics for a fall in demand for those abilities.     

Bridging the gap between micro - and macro-scale perspectives on the role of microbial communities in global change ecology

In order to understand the role microbial communities play in mediating ecosystem response to disturbances it is essential to address the methodological and conceptual gap that exists between micro- and macro-scale perspectives in ecology. While there is little doubt microorganisms play a central role in ecosystem functioning and therefore in ecosystem response to global change-induced disturbance, our ability to investigate the exact nature of that role is limited by disciplinary and methodological differences among microbial and ecosystem ecologists. In this paper we present results from an interdisciplinary graduate-level seminar class focused on this topic. Through the medium of case studies in global change ecology (soil respiration, nitrogen cycling, plant species invasion and land use/cover change) we highlight differences in our respective approach to ecology and give examples where disciplinary perspective influences our interpretation of the system under study. Finally, we suggest a model for integrating perspectives that may lead to greater interdisciplinary collaboration and enhanced conceptual and mechanistic modeling of ecosystem response to disturbance.     

Composition-related structural transition of random peptides: insight into the boundary between intrinsically disordered proteins and folded proteins

Previous studies based on bioinformatics showed that there is a sharp distinction of structural features and residue composition between the intrinsically disordered proteins and the folded proteins. What induces such a composition-related structural transition? How do various kinds of interactions work in such processes? In this work, we investigate these problems based on a survey on peptides randomly composed of charged residues (including glutamic acids and lysines) and the residues with different hydrophobicity, such as alanines, glycines, or phenylalanines. Based on simulations using all-atom model and replica-exchange Monte Carlo method, a coil-globule transition is observed for each peptide. The corresponding transition temperature is found to be dependent on the contents of the hydrophobic and charged residues. For several cases, when the mean hydrophobicity is larger than a certain threshold, the transition temperature is higher than the room temperature, and vise versa. These thresholds of hydrophobicity and net charge are quantitatively consistent with the border line observed from the study of bioinformatics. These results outline the basic physical reasons for the compositional distinction between the intrinsically disordered proteins and the folded proteins. Furthermore, the contributions of various interactions to the structural variation of peptides are analyzed based on the contact statistics and the charge-pattern dependence of the gyration radii of the peptides. Our observations imply that the hydrophobicity contributes essentially to such composition-related transitions. Thus, we achieve a better understanding on composition–structure relation of the natural proteins and the underlying physics.     

ORBIT: an integrated environment for user-customized bioinformatics tools

MOTIVATION: There are a large number of computational programs freely available to bioinformaticians via a client/server, web-based environment. However, the client interface to these tools (typically an html form page) cannot be customized from the client side as it is created by the service provider. The form page is usually generic enough to cater for a wide range of users. However, this implies that a user cannot set as 'default' advanced program parameters on the form or even customize the interface to his/her specific requirements or preferences. Currently, there is a lack of end-user interface environments that can be modified by the user when accessing computer programs available on a remote server running on an intranet or over the Internet. RESULTS: We have implemented a client/server system called ORBIT (Online Researcher's Bioinformatics Interface Tools) where individual clients can have interfaces created and customized to command-line-driven, server-side programs. Thus, Internet-based interfaces can be tailored to a user's specific bioinformatic needs. As interfaces are created on the client machine independent of the server, there can be different interfaces to the same server-side program to cater for different parameter settings. The interface customization is relatively quick (between 10 and 60 min) and all client interfaces are integrated into a single modular environment which will run on any computer platform supporting Java. The system has been developed to allow for a number of future enhancements and features. ORBIT represents an important advance in the way researchers gain access to bioinformatics tools on the Internet.     

Australian Indigenous Studies: A Question of Discipline

This paper is an early discussion of the ways we are approaching Indigenous Studies in Australian Universities. The focus is on how disciplinary and scholarly issues within Indigenous Studies can be interrogated and yet retain the necessary cohesion and solidarity so important to the Indigenous struggle. The paper contrasts Indigenous Studies pursued by Indigenous scholars to other disciplinary perspectives in the academy. Categories such as the Indigenous community and Indigenous knowledge are problematised, not to dissolve them, but to explore productive avenues. I identify one of the problems that Indigenous studies faces as resisting the tendency to perpetuate an enclave within the academy whose purpose is to reflect back an impoverished and codified representation of Indigenous culture to the communities that are its source. On the other hand, there is danger also in the necessary engagement with other disciplines on their own terms. My suggestion is that we see ourselves mapping our understanding of our particular Indigenous experiences upon a terrain intersected by the pathways, both of other Indigenous experiences, and of the non‐Indigenous academic disciplines. My intention is to stimulate some thought among Indigenous academics and scholars about the future possibilities of Australian Indigenous Studies as a field of endeavour.     

Visualizing the knowledge structure and evolution of bioinformatics

Background

Bioinformatics has gained much attention as a fast growing interdisciplinary field. Several attempts have been conducted to explore the field of bioinformatics by bibliometric analysis, however, such works did not elucidate the role of visualization in analysis, nor focus on the relationship between sub-topics of bioinformatics.

Results

First, the hotspot of bioinformatics has moderately shifted from traditional molecular biology to omics research, and the computational method has also shifted from mathematical model to data mining and machine learning. Second, DNA-related topics are bridge topics in bioinformatics research. These topics gradually connect various sub-topics that are relatively independent at first. Third, only a small part of topics we have obtained involves a number of computational methods, and the other topics focus more on biological aspects. Fourth, the proportion of computing-related topics hit a trough in the 1980s. During this period, the use of traditional calculation methods such as mathematical model declined in a large proportion while the new calculation methods such as machine learning have not been applied in a large scale. This proportion began to increase gradually after the 1990s. Fifth, although the proportion of computing-related topics is only slightly higher than the original, the connection between other topics and computing-related topics has become closer, which means the support of computational methods is becoming increasingly important for the research of bioinformatics.

Conclusions

The results of our analysis imply that research on bioinformatics is becoming more diversified and the ranking of computational methods in bioinformatics research is also gradually improving.