Search

In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.

The Cochrane Collaboration was established in 1993, following the opening of the UK Cochrane Centre in 1992, at a time when searching for studies for inclusion in systematic reviews was not well-developed. Review authors largely conducted their own searches or depended on medical librarians, who often possessed limited awareness and experience of systematic reviews. Guidance on the conduct and reporting of searches was limited. When work began to identify reports of randomized controlled trials (RCTs) for inclusion in Cochrane Reviews in 1992, there were only approximately 20,000 reports indexed as RCTs in MEDLINE and none indexed as RCTs in Embase. No search filters had been developed with the aim of identifying all RCTs in MEDLINE or other major databases. This presented The Cochrane Collaboration with a considerable challenge in identifying relevant studies.Over time, the number of studies indexed as RCTs in the major databases has grown considerably and the Cochrane Central Register of Controlled Trials (CENTRAL) has become the best single source of published controlled trials, with approximately 700,000 records, including records identified by the Collaboration from Embase and MEDLINE. Search filters for various study types, including systematic reviews and the Cochrane Highly Sensitive Search Strategies for RCTs, have been developed. There have been considerable advances in the evidence base for methodological aspects of information retrieval. The Cochrane Handbook for Systematic Reviews of Interventions now provides detailed guidance on the conduct and reporting of searches. Initiatives across The Cochrane Collaboration to improve the quality inter alia of information retrieval include: the recently introduced Methodological Expectations for Cochrane Intervention Reviews (MECIR) programme, which stipulates 'mandatory' and 'highly desirable' standards for various aspects of review conduct and reporting including searching, the development of Standard Training Materials for Cochrane Reviews and work on peer review of electronic search strategies. Almost all Cochrane Review Groups and some Cochrane Centres and Fields now have a Trials Search Co-ordinator responsible for study identification and medical librarians and other information specialists are increasingly experienced in searching for studies for systematic reviews.Prospective registration of clinical trials is increasing and searching trials registers is now mandatory for Cochrane Reviews, where relevant. Portals such as the WHO International Clinical Trials Registry Platform (ICTRP) are likely to become increasingly attractive, given concerns about the number of trials which may not be registered and/or published. The importance of access to information from regulatory and reimbursement agencies is likely to increase. Cross-database searching, gateways or portals and improved access to full-text databases will impact on how searches are conducted and reported, as will services such as Google Scholar, Scopus and Web of Science. Technologies such as textual analysis, semantic analysis, text mining and data linkage will have a major impact on the search process but efficient and effective updating of reviews may remain a challenge.In twenty years' time, we envisage that the impact of universal social networking, as well as national and international legislation, will mean that all trials involving humans will be registered at inception and detailed trial results will be routinely available to all. Challenges will remain, however, to ensure the discoverability of relevant information in diverse and often complex sources and the availability of metadata to provide the most efficient access to information. We envisage an ongoing role for information professionals as experts in identifying new resources, researching efficient ways to link or mine them for relevant data and managing their content for the efficient production of systematic reviews.

In a world with ever decreasing natural reserves, researchers are striving to find sustainable methods of producing components for technology. Bioinspired, biokleptic and biomimetic materials can be used to form a wide range of technologically relevant materials under environmentally friendly conditions. Here we investigate a range of biotemplated and bioinspired materials that can be used to develop components for devices, such as optics, photonics, photovoltaics, circuits and data storage., (Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

With world wide data predicted to exceed 40 trillion gigabytes by 2020, big data storage is a very real and escalating problem. Herein, we discuss the utility of synthetic DNA as a robust and eco-friendly archival data storage solution of the future.

The Protein Data Bank (PDB) was established in 1971 as a repository for the three dimensional structures of biological macromolecules. Since then, more than 85000 biological macromolecule structures have been determined and made available in the PDB archive. Through analysis of the corpus of data, it is possible to identify trends that can be used to inform us abou the future of structural biology and to plan the best ways to improve the management of the ever-growing amount of PDB data., (Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.)

Much of what is currently documented in the electronic health record is in response toincreasingly complex and prescriptive medicolegal, reimbursement, and regulatory requirements. These requirements often result in redundant data capture and cumbersome documentation processes. AMIA's 2011 Health Policy Meeting examined key issues in this arena and envisioned changes to help move toward an ideal future state of clinical data capture and documentation. The consensus of the meeting was that, in the move to a technology-enabled healthcare environment, the main purpose of documentation should be to support patient care and improved outcomes for individuals and populations and that documentation for other purposes should be generated as a byproduct of care delivery. This paper summarizes meeting deliberations, and highlights policy recommendations and research priorities. The authors recommend development of a national strategy to review and amend public policies to better support technology-enabled data capture and documentation practices.

This work aims at understanding the state of the art in the broad contextual research area of "medical concept representation". Our data support the general understanding that the focus of research has moved toward medical ontologies, which we interpret as a paradigm shift. Both the opinion of socially active groups of researchers and changes in bibliometric data since 1988 support this opinion. Socially active researchers mention the OBO foundry, SNOMED CT, and the UMLS as anchor activities.

Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein-ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Quantum information processors have the potential to drastically change the way we communicate and process information. Nuclear magnetic resonance (NMR) has been one of the first experimental implementations of quantum information processing (QIP) and continues to be an excellent testbed to develop new QIP techniques. We review the recent progress made in NMR QIP, focusing on decoupling, pulse engineering and indirect nuclear control. These advances have enhanced the capabilities of NMR QIP, and have useful applications in both traditional NMR and other QIP architectures.

Steering quantum dynamics such that the target states solve classically hard problems is paramount to quantum simulation and computation. And beyond, quantum control is also essential to pave the way to quantum technologies. Here, important control techniques are reviewed and presented in a unified frame covering quantum computational gate synthesis and spectroscopic state transfer alike. We emphasize that it does not matter whether the quantum states of interest are pure or not. While pure states underly the design of quantum circuits, ensemble mixtures of quantum states can be exploited in a more recent class of algorithms: it is illustrated by characterizing the Jones polynomial in order to distinguish between different (classes of) knots. Further applications include Josephson elements, cavity grids, ion traps and nitrogen vacancy centres in scenarios of closed as well as open quantum systems.

We briefly describe the use of gradient ascent pulse engineering (GRAPE) pulses to implement quantum logic gates in nuclear magnetic resonance quantum computers, and discuss a range of simple extensions to the core technique. We then consider a range of difficulties that can arise in practical implementations of GRAPE sequences, reflecting non-idealities in the experimental systems used.

Background: Online psychiatric texts are natural language texts expressing depressive problems, published by Internet users via community-based web services such as web forums, message boards and blogs. Understanding the cause-effect relations embedded in these psychiatric texts can provide insight into the authors' problems, thus increasing the effectiveness of online psychiatric services., Methods: Previous studies have proposed the use of word pairs extracted from a set of sentence pairs to identify cause-effect relations between sentences. A word pair is made up of two words, with one coming from the cause text span and the other from the effect text span. Analysis of the relationship between these words can be used to capture individual word associations between cause and effect sentences. For instance, (broke up, life) and (boyfriend, meaningless) are two word pairs extracted from the sentence pair: "I broke up with my boyfriend. Life is now meaningless to me". The major limitation of word pairs is that individual words in sentences usually cannot reflect the exact meaning of the cause and effect events, and thus may produce semantically incomplete word pairs, as the previous examples show. Therefore, this study proposes the use of inter-sentential language patterns such as ≪broke up, boyfriend>,

High-throughput genome research has long been associated with bioinformatics, as it assists genome sequencing and annotation projects. Along with databases, to store, properly manage, and retrieve biological data, a large number of computational tools have been developed to decode biological information from this data. However, with the advent of next-generation sequencing (NGS) technology the sequence data starts generating at a pace never before seen. Consequently researchers are facing a threat as they are experiencing a potential shortage of storage space and tools to analyze the data. Moreover, the voluminous data increases traffic in the network by uploading and downloading large data sets, and thus consume much of the network's available bandwidth. All of these obstacles have led to the solution in the form of cloud computing.

This is the second in a series of articles exploring international trends in health science librarianship in the first decade of the 21st century. The invited authors were asked to reflect on developments in their country - viz. Australia, Canada, New Zealand and the United States. Future issues will track trends in Northern Europe, the Nordic countries, Southern Europe and Latin America. JM., (© 2012 The authors. Health Information and Libraries Journal © 2012 Health Libraries Group.)

Because of competing priorities as well as cost, security, and implementation concerns, cloud-based storage development has gotten off to a slow start in healthcare. CIOs, CTOs, and other healthcare IT leaders are adopting a variety of strategies in this area, based on their organizations' needs, resources, and priorities.

The unintended and often promiscous inhibition of the cardiac human Ether-à-go-go related gene (hERG) potassium channel is a common cause for either delay or removal of therapeutic compounds from development and withdrawal of marketed drugs. The clinical manifestion is prolongation of the duration between QRS complex and T-wave measured by surface electrocardiogram (ECG)-hence Long QT Syndrome. There are several useful online resources documenting hERG inhibition by known drugs and bioactives. However, their utilities remain somewhat limited because they are biased toward well-studied compounds and their number of data points tends to be much smaller than many commercial compound libraries. The hERGCentral ( www.hergcentral.org ) is mainly based on experimental data obtained from a primary screen by electrophysiology against more than 300,000 structurally diverse compounds. The system is aimed to display and combine three resources: primary electrophysiological data, literature, as well as online reports and chemical library collections. Currently, hERGCentral has annotated datasets of more than 300,000 compounds including structures and chemophysiological properties of compounds, raw traces, and biophysical properties. The system enables a variety of query formats, including searches for hERG effects according to either chemical structure or properties, and alternatively according to the specific biophysical properties of current changes caused by a compound. Therefore, the hERGCentral, as a unique and evolving resource, will facilitate investigation of chemically induced hERG inhibition and therefore drug development., (© MARY ANN LIEBERT, INC.)

Quick Response (QR) Codes are standard in supply management and seen with increasing frequency in advertisements. They are now present regularly in healthcare informatics and education. These 2-dimensional square bar codes, originally designed by the Toyota car company, are free of license and have a published international standard. The codes can be generated by free online software and the resulting images incorporated into presentations. The images can be scanned by "smart" phones and tablets using either the iOS or Android platforms, which link the device with the information represented by the QR code (uniform resource locator or URL, online video, text, v-calendar entries, short message service [SMS] and formatted text). Once linked to the device, the information can be viewed at any time after the original presentation, saved in the device or to a Web-based "cloud" repository, printed, or shared with others via email or Bluetooth file transfer. This paper describes how we use QR codes in our tumor board presentations, discusses the benefits, the different QR codes from Web links and how QR codes facilitate the distribution of educational content.

The development of digital technologies in all activities sectors of our society leads to a growing number of digital documents. A significant part of these documents needs to be durably preserved. This long term preservation has to face the short life expectancy of the technologies and the digital storage media. Large national organizations have already take this problem into account and set up teams, skills and means to face this challenge. At the opposite, the small structures, doctor's offices, individuals, students, etc. are not generally aware of the problem or are stripped to face there. A certain number of simple actions, not requiring specific skills in data processing can nevertheless be undertaken. Without important expenditure, they increase to a significant degree, the security level of the documents over the long term., (© 2011 médecine/sciences - Inserm / SRMS.)

Picture Archiving and Communication System (PACS), which was originally designed as a tool for facilitating radiologists in interpreting images more efficiently, is evolving into a hospital-integrated system storing diagnostic imaging information that often reaches far beyond Radiology. The continuous evolution of PACS technology has led to a gradual broadening of its applications, ranging from teleradiology to CAD (Computer-Assisted Diagnosis) and multidimensional imaging, and is moving into the direction of providing access to image data outside the Radiology department, so to reach all the branches of the healthcare enterprise. New perspectives have been created thanks to new technologies (such as holographic media and GRID computing) that are likely due to expand PACS-based applications even further, improving patient care and enhancing overall productivity., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

Radiological Picture Archiving and Communication Systems (PACS) have only relatively recently become abundant. Many hospitals have made the transition to PACS about a decade ago. During that decade requirements and available technology have changed considerably. In this paper we look at factors that influence the design of tomorrow's systems, especially those in larger multidisciplinary hospitals. We discuss their impact on PACS architecture (a technological perspective) as well as their impact on radiology (a management perspective). We emphasize that many of these influencing factors originate outside radiology and that radiology has little impact on these factors. That makes it the more important for managers in radiology to be aware of architectural aspects and it may change cooperation of radiology with, among others, the hospital's central IT department., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

Background: The assumption behind the presented work is that the information people search for on the internet reflects the disease status in society. By having access to this source of information, epidemiologists can get a valuable complement to the traditional surveillance and potentially get new and timely epidemiological insights. For this purpose, the Swedish Institute for Infectious Disease Control collaborates with a medical web site in Sweden., Methods: We built an application consisting of two conceptual parts. One part allows for trends, based on user specified requests, to be extracted from anonymous web query data from a Swedish medical web site. The second conceptual part permits tailored analyses of particular diseases, where more complex statistical methods are applied to the data. To evaluate the epidemiological relevance of the output, we compared Google search data and search data from the medical web site., Results: In the paper, we give concrete examples of the output from the web query-based system. We also present results from the comparison between data from the search engine Google and search data from the national medical web site., Conclusions: The application is in regular use at the Swedish Institute for Infectious Disease Control. A system based on web queries is flexible in that it can be adapted to any disease; we get information on other individuals than those who seek medical care; and the data do not suffer from reporting delays. Although Google data are based on a substantially larger search volume, search patterns obtained from the medical web site may still convey more information from an epidemiological perspective. Furthermore we can see advantages with having full access to the raw data.

Diagnostic radiology requires accurate interpretation of complex signals in medical images. Content-based image retrieval (CBIR) techniques could be valuable to radiologists in assessing medical images by identifying similar images in large archives that could assist with decision support. Many advances have occurred in CBIR, and a variety of systems have appeared in nonmedical domains; however, permeation of these methods into radiology has been limited. Our goal in this review is to survey CBIR methods and systems from the perspective of application to radiology and to identify approaches developed in nonmedical applications that could be translated to radiology. Radiology images pose specific challenges compared with images in the consumer domain; they contain varied, rich, and often subtle features that need to be recognized in assessing image similarity. Radiology images also provide rich opportunities for CBIR: rich metadata about image semantics are provided by radiologists, and this information is not yet being used to its fullest advantage in CBIR systems. By integrating pixel-based and metadata-based image feature analysis, substantial advances of CBIR in medicine could ensue, with CBIR systems becoming an important tool in radiology practice.

The Internet provides a quick access to a plethora of the medical literature, in the form of journals, databases, dictionaries, textbooks, indexes, and e-journals, thereby allowing access to more varied, individualized, and systematic educational opportunities. Web search engine is a tool designed to search for information on the World Wide Web, which may be in the form of web pages, images, information, and other types of files. Search engines for internet-based search of medical literature include Google, Google scholar, Yahoo search engine, etc., and databases include MEDLINE, PubMed, MEDLARS, etc. Commercial web resources (Medscape, MedConnect, MedicineNet) add to the list of resource databases providing some of their content for open access. Several web-libraries (Medical matrix, Emory libraries) have been developed as meta-sites, providing useful links to health resources globally. Availability of specific dermatology-related websites (DermIs, DermNet, and Genamics Jornalseek) is useful addition to the ever growing list of web-based resources. A researcher must keep in mind the strengths and limitations of a particular search engine/database while searching for a particular type of data. Knowledge about types of literature and levels of detail available, user interface, ease of access, reputable content, and period of time covered allow their optimal use and maximal utility in the field of medicine.

Many of the challenges in genomics derive from the informatics needed to store and analyze the raw sequencing data that is available from highly multiplexed sequencing technologies. Because single week-long sequencing runs today can produce as much data as did entire genome centers a few years ago, the need to process terabytes of information has become de rigueur for many labs engaged in genomic research. The availability of deep (and large) genomic data sets raises concerns over information access, data security, and subject/patient privacy that must be addressed for the field to continue its rapid advances.

On-going molecular biological researches are characterized by exponential increase in the amount of experimental data which dictates the necessity to develop relevant information technologies. The knowledge-based approach appears to be a most promising and flexible tool for analytical processing biomedical information that allows new relationships between study objects to be established. In this article we analyze the work of researchers based at the Institute of Biomedical Chemistry with the materials of the PubMed biomedical library. A list of publication IDs for a half-year period has been compiled to elucidate individual profiles of research activities. Statistical analysis of medical subject headings (MeSH) reveals typical profiles of research of interest for separate divisions of the Institute. The proposed approach may be recommended as a means for improving the efficiency and coordination of biomedical research.

Objective: To develop a model based upon factors able to predict the time spent answering drug-related queries to Norwegian drug information centres (DICs)., Setting and Method: Drug-related queries received at 5 DICs in Norway from March to May 2007 were randomly assigned to 20 employees until each of them had answered a minimum of five queries. The employees reported the number of drugs involved, the type of literature search performed, and whether the queries were considered judgmental or not, using a specifically developed scoring system., Main Outcome Measures: The scores of these three factors were added together to define a workload score for each query. Workload and its individual factors were subsequently related to the measured time spent answering the queries by simple or multiple linear regression analyses., Results: Ninety-six query/answer pairs were analyzed. Workload significantly predicted the time spent answering the queries (adjusted R (2) = 0.22, P < 0.001). Literature search was the individual factor best predicting the time spent answering the queries (adjusted R(2) = 0.17, P < 0.001), and this variable also contributed the most in the multiple regression analyses., Conclusion: The most important workload factor predicting the time spent handling the queries in this study was the type of literature search that had to be performed. The categorisation of queries as judgmental or not, also affected the time spent answering the queries. The number of drugs involved did not significantly influence the time spent answering drug information queries.

Cheminformatics is at a turning point, the pharmaceutical industry benefits from using the various methods developed over the last twenty years, but in our opinion we need to see greater development of novel approaches that non-experts can use. This will be achieved by more collaborations between software companies, academics and the evolving pharmaceutical industry. We suggest that cheminformatics should also be looking to other industries that use high performance computing technologies for inspiration. We describe the needs and opportunities which may benefit from the development of open cheminformatics technologies, mobile computing, the movement of software to the cloud and precompetitive initiatives.

The biomedical literature holds our understanding of pharmacogenomics, but it is dispersed across many journals. In order to integrate our knowledge, connect important facts across publications and generate new hypotheses we must organize and encode the contents of the literature. By creating databases of structured pharmocogenomic knowledge, we can make the value of the literature much greater than the sum of the individual reports. We can, for example, generate candidate gene lists or interpret surprising hits in genome-wide association studies. Text mining automatically adds structure to the unstructured knowledge embedded in millions of publications, and recent years have seen a surge in work on biomedical text mining, some specific to pharmacogenomics literature. These methods enable extraction of specific types of information and can also provide answers to general, systemic queries. In this article, we describe the main tasks of text mining in the context of pharmacogenomics, summarize recent applications and anticipate the next phase of text mining applications.

This contribution is aimed at presenting a sort of "state of the art" of Open Access on the occasion of the 2010 international Open Access Week, to be held from October 18 to October 24. We shall see facts and figures about open archives and the mandates to deposit; about Open Access journals; about impact and citation advantages for the researchers, and about economic sustainability.

Data sharing is important in the biological sciences to prevent duplication of effort, to promote scientific integrity, and to facilitate and disseminate scientific discovery. Sharing requires centralized repositories, and submission to and utility of these resources require common data formats. This is particularly challenging for multidimensional microscopy image data, which are acquired from a variety of platforms with a myriad of proprietary file formats (PFFs). In this paper, we describe an open standard format that we have developed for microscopy image data. We call on the community to use open image data standards and to insist that all imaging platforms support these file formats. This will build the foundation for an open image data repository.