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At least 19 recordsLinked to original sources
PubMed2026

From the establishment of a national bioinformatics society to the development of a national bioinformatics infrastructure.

We describe the evolution of a bioinformatics national capacity from scattered professionals into a collaborative organisation, and advancements in the adoption of the bioinformatics infrastructure philosophy by the national community. The Romanian Society of Bioinformatics (RSBI), a national professional society, was founded in 2019 to accelerate the development of Romanian bioinformatics. Incrementally, RSBI expanded its role to include: i) developing a community and engaging the public and stakeholders, ii) a national training approach, including through increased interactions with European training resources, and iii) advocating national participation in European bioinformatics infrastructures. In a next step RSBI led the development of the national bioinformatics infrastructure, the Romanian Bioinformatics Cluster (CRB) with the mission to act as an ELIXIR National Node. In this paper we report both the successful projects in training, public engagement, and policy projects, as well as initiatives related to data federation that, while not successful, can serve as valuable learning experiences for future implementations. We explain CRB's structure and the role such an entity can play in the national bioinformatics infrastructure for data, tools, and training. Finally, we offer insights into the evolving role of the bioinformatics professional society and the synergies and interactions with the forthcoming National ELIXIR Node.

Computational Biology↗
PubMed2003

Evolving from bioinformatics in-the-small to bioinformatics in-the-large.

We argue the significance of a fundamental shift in bioinformatics, from in-the-small to in-the-large. Adopting a large-scale perspective is a way to manage the problems endemic to the world of the small-constellations of incompatible tools for which the effort required to assemble an integrated system exceeds the perceived benefit of the integration. Where bioinformatics in-the-small is about data and tools, bioinformatics in-the-large is about metadata and dependencies. Dependencies represent the complexities of large-scale integration, including the requirements and assumptions governing the composition of tools. The popular make utility is a very effective system for defining and maintaining simple dependencies, and it offers a number of insights about the essence of bioinformatics in-the-large. Keeping an in-the-large perspective has been very useful to us in large bioinformatics projects. We give two fairly different examples, and extract lessons from them showing how it has helped. These examples both suggest the benefit of explicitly defining and managing knowledge flows and knowledge maps (which represent metadata regarding types, flows, and dependencies), and also suggest approaches for developing bioinformatics database systems. Generally, we argue that large-scale engineering principles can be successfully adapted from disciplines such as software engineering and data management, and that having an in-the-large perspective will be a key advantage in the next phase of bioinformatics development.

Computational Biology↗
PubMed2006

The Online Bioinformatics Resources Collection at the University of Pittsburgh Health Sciences Library System--a one-stop gateway to online bioinformatics databases and software tools.

To bridge the gap between the rising information needs of biological and medical researchers and the rapidly growing number of online bioinformatics resources, we have created the Online Bioinformatics Resources Collection (OBRC) at the Health Sciences Library System (HSLS) at the University of Pittsburgh. The OBRC, containing 1542 major online bioinformatics databases and software tools, was constructed using the HSLS content management system built on the Zope Web application server. To enhance the output of search results, we further implemented the Vivísimo Clustering Engine, which automatically organizes the search results into categories created dynamically based on the textual information of the retrieved records. As the largest online collection of its kind and the only one with advanced search results clustering, OBRC is aimed at becoming a one-stop guided information gateway to the major bioinformatics databases and software tools on the Web. OBRC is available at the University of Pittsburgh's HSLS Web site (http://www.hsls.pitt.edu/guides/genetics/obrc).

Computational Biology↗
PubMed2004

The Helmholtz Network for Bioinformatics: an integrative web portal for bioinformatics resources.

SUMMARY: The Helmholtz Network for Bioinformatics (HNB) is a joint venture of eleven German bioinformatics research groups that offers convenient access to numerous bioinformatics resources through a single web portal. The 'Guided Solution Finder' which is available through the HNB portal helps users to locate the appropriate resources to answer their queries by employing a detailed, tree-like questionnaire. Furthermore, automated complex tool cascades ('tasks'), involving resources located on different servers, have been implemented, allowing users to perform comprehensive data analyses without the requirement of further manual intervention for data transfer and re-formatting. Currently, automated cascades for the analysis of regulatory DNA segments as well as for the prediction of protein functional properties are provided. AVAILABILITY: The HNB portal is available at http://www.hnbioinfo.de

Algorithms↗
PubMed2006

Development of computations in bioscience and bioinformatics and its application: review of the Symposium of Computations in Bioinformatics and Bioscience (SCBB06).

The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21-22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.

Biological Science Disciplines↗
PubMed2006

Bioinformatics and its impact on clinical research methods. Findings from the Section on Bioinformatics.

OBJECTIVES: To summarize current excellent research in the field of bioinformatics. METHOD: Synopsis of the articles selected for the IMIA Yearbook 2006. RESULTS: Current research in the field of bioinformatics clearly shows ongoing unification of experimental findings and clinical outcomes. Microarray data, gene sequences and clinical data are more and more perceived as different but related facets of one entity. Significant work is done in the area of text and data mining in order to bring together patient data and biochemical phenomena by means of ontologies. A strong trend in the clinical field is performance of exhaustive studies on DNA material derived from patients that suffer from diseases that are already known to be inherited. Examination of appropriate methods covers data and text mining, ontologies as well as machine learning and classification. CONCLUSIONS: The best paper selection of articles on bioinformatics shows examples of excellent research on methods used for studying inherited diseases and their underlying genetic dispositions. Clinical studies, inclusion of experimental findings like microarray data, and of knowledge representation formats all lead to a better understanding the linkage between gene sequences, biological functions and clinical findings in the form of healthy state or physiological disorders.

Awards and Prizes↗
PubMed2005

5th HUPO BPP Bioinformatics Meeting at the European Bioinformatics Institute in Hinxton, UK--Setting the analysis frame.

The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On July 7, 2005 the members came together for the 5th time at the European Bioinformatics Institute (EBI) in Hinxton, UK, hosted by Rolf Apweiler. As a main result, the parameter set of the semi-automated data re-analysis of MS/MS spectra has been elaborated and the subsequent work steps have been defined.

Computational Biology↗
PubMed2005

New bioinformatics tools for viral genome analyses at Viral Bioinformatics--Canada.

Viruses are much smaller than prokaryotes and eukaryotes, and it is now practical to sequence closely related members of virus families, strains, or even different isolates recovered during the course of an outbreak. However, comparative analysis of viral genomes requires the development of novel bioinformatics tools that allow us to align, edit, compare and interact with these genomes at all levels, from whole genome, to gene family, to single nucleotide polymorphisms. Comparative viral genomics can lead to the identification of the core characteristics that define a virus family, as well as the unique properties of viral species or isolates that contribute to variations in pathogenesis. This paper describes a number of tools, mainly developed for Viral Bioinformatics--Canada, that can be used for annotation and comparative genomic analysis of poxviruses. Nonetheless, these tools are also broadly applicable to other virus families.

Base Sequence↗
PubMed2003

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.

Computational Biology↗
PubMed2005

Clinical bioinformatics.

Clinical bioinformatics provides biological and medical information to allow for individualized healthcare. In this review, we describe the uses of clinical bioinformatics. After the analysis of the complete human genome sequences, clinical bioinformatics enables researchers to search online biological databases and use the biological information in their medical practices. The data obtained from using microarray is extremely complicated. In clinical bioinformatics, selecting appropriate software to analyze the microarray data for medical decision making is crucial. Proteomics strategy tools usually focus on similarity searches, structure prediction, and protein modeling. In clinical bioinformatics, the proteomic data only have meaning if they are integrated with clinical data. In pharmacogenomics, clinical bioinformatics includes elaborate studies of bioinformatics tools and various facets of proteomics related to drug target identification and clinical validation. Using clinical bioinformatics, researchers apply computational and high-throughput experimental techniques to cancer research and systems biology. Meanwhile, researchers of bioinformatics and medical information have incorporated clinical bioinformatics to improve health care, using biological and medical information. Using the high volume of biological information from clinical bioinformatics will contribute to changes in practice standards in the healthcare system. We believe that clinical bioinformatics provides benefits of improving healthcare, disease prevention and health maintenance as we move toward the era of personalized medicine.

Computational Biology↗
PubMed2006

Developing library bioinformatics services in context: the Purdue University Libraries bioinformationist program.

SETTING: Purdue University is a major agricultural, engineering, biomedical, and applied life science research institution with an increasing focus on bioinformatics research that spans multiple disciplines and campus academic units. The Purdue University Libraries (PUL) hired a molecular biosciences specialist to discover, engage, and support bioinformatics needs across the campus. PROGRAM COMPONENTS: After an extended period of information needs assessment and environmental scanning, the specialist developed a week of focused bioinformatics instruction (Bioinformatics Week) to launch system-wide, library-based bioinformatics services. EVALUATION MECHANISMS: The specialist employed a two-tiered approach to assess user information requirements and expectations. The first phase involved careful observation and collection of information needs in-context throughout the campus, attending laboratory meetings, interviewing department chairs and individual researchers, and engaging in strategic planning efforts. Based on the information gathered during the integration phase, several survey instruments were developed to facilitate more critical user assessment and the recovery of quantifiable data prior to planning. NEXT STEPS/FUTURE DIRECTIONS: Given information gathered while working with clients and through formal needs assessments, as well as the success of instructional approaches used in Bioinformatics Week, the specialist is developing bioinformatics support services for the Purdue community. The specialist is also engaged in training PUL faculty librarians in bioinformatics to provide a sustaining culture of library-based bioinformatics support and understanding of Purdue's bioinformatics-related decision and policy making.

Computational Biology↗