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We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at http://nesg.org. It serves as the central hub for the Northeast Structural Genomics Consortium, allowing collaborative structural proteomics to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for key bits of information related to the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The core database comprises a set of standard relational tables and a data dictionary that form an initial ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE sits at the center of a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories) and (iii) international archival resources that SPINE links to and passes on information to (e.g. TargetDB at the PDB).

Background

Laboratories that produce protein reagents for research and development face the challenge of deciding whether to track batch-related data using simple file based storage mechanisms (e.g. spreadsheets and notebooks), or commit the time and effort to install, configure and maintain a more complex laboratory information management system (LIMS). Managing reagent data stored in files is challenging because files are often copied, moved, and reformatted. Furthermore, there is no simple way to query the data if/when questions arise. Commercial LIMS often include additional modules that may be paid for but not actually used, and often require software expertise to truly customize them for a given environment.

Findings

This web-application allows small to medium-sized protein production groups to track data related to plasmid DNA, conditioned media samples (supes), cell lines used for expression, and purified protein information, including method of purification and quality control results. In addition, a request system was added that includes a means of prioritizing requests to help manage the high demand of protein production resources at most organizations. ProteinTracker makes extensive use of existing open-source libraries and is designed to track essential data related to the production and purification of proteins.

Conclusions

ProteinTracker is an open-source web-based application that provides organizations with the ability to track key data involved in the production and purification of proteins and may be modified to meet the specific needs of an organization. The source code and database setup script can be downloaded from http://sourceforge.net/projects/proteintracker. This site also contains installation instructions and a user guide. A demonstration version of the application can be viewed at http://www.proteintracker.org.

Background

eCAT is an electronic lab notebook (ELN) developed by Axiope Limited. It is the first online ELN, the first ELN to be developed in close collaboration with lab scientists, and the first ELN to be targeted at researchers in non-commercial institutions. eCAT was developed in response to feedback from users of a predecessor product. By late 2006 the basic concept had been clarified: a highly scalable web-based collaboration tool that possessed the basic capabilities of commercial ELNs, i.e. a permissions system, controlled sharing, an audit trail, electronic signature and search, and a front end that looked like the electronic counterpart to a paper notebook.

Results

During the development of the beta version feedback was incorporated from many groups including the FDA's Center for Biologics Evaluation & Research, Uppsala University, Children's Hospital Boston, Alex Swarbrick's lab at the Garvan Institute in Sydney and Martin Spitaler at Imperial College. More than 100 individuals and groups worldwide then participated in the beta testing between September 2008 and June 2009. The generally positive response is reflected in the following quote about how one lab is making use of eCAT: "Everyone uses it as an electronic notebook, so they can compile the diverse collections of data that we generate as biologists, such as images and spreadsheets. We use to it to take minutes of meetings. We also use it to manage our common stocks of antibodies, plasmids and so on. Finally, perhaps the most important feature for us is the ability to link records, reagents and experiments."

Conclusion

By developing eCAT in close collaboration with lab scientists, Axiope has come up with a practical and easy-to-use product that meets the need of scientists to manage, store and share data online. eCAT is already being perceived as a product that labs can continue to use as their data management and sharing grows in scale and complexity.

As part of our effort to create an Integrated Academic Information Management System at Baylor College of Medicine, we are developing information technology to support the efforts of scientific work groups. Many of our ideas in this regard are embodied in a system called the Virtual Notebook which is intended to facilitate information sharing and management in such groups. Here we discuss the foundations of that system - a hypertext system that we have developed using a relational data base and the distributable interface the we have written in the X Window System.

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Laboratory directors are facing enormous challenges with respect to keeping their laboratories competitive and retaining customers in the face of shrinking budgets and rapidly changing technology. A well-designed Laboratory Information Management System (LIMS) can help meet these challenges and manage costs as the scale and complexity of data collection and related services increase. LIMS can also offer competitive advantages through increased automation and improved customer experiences.Implementing a LIMS strategy that will reduce data collection costs while improving competitiveness is a daunting proposition. LIMS are computerized data and information tracking systems that are highly variable with respect to their purpose, customization capabilities, and overall acquisition (initial purchase) and ownership (maintenance) costs. A simple LIMS can be built from a small number of spread sheets and track a few specific processes. Sophisticated LIMS rely on databases to manage multiple laboratory processes, capture and analyze different kinds of data, and provide decision support capabilities.In this presentation, I will share 20 years of academic and industrial LIMS experiences and perspectives that have been informed through 100’s of interactions with core, research, and manufacturing laboratories engaged in DNA sequencing, genotyping, and microarrays. We’ll explore the issues that need to be addressed with respect to either building a LIMS, or acquiring a LIMS product. A new model that allows laboratories to offer competitive services, utilizing cost-effective laboratory automation strategies and new technologies like next generation sequencing, will be presented. We’ll also compare different IT infrastructures and discuss their advantages and how investments can be made to protect against unexpected costs as new instruments, like the HiSeq 2000™ or SOLiD 4™, third generation sequencing, or other genetic analysis platforms are introduced.

Background

Research in plant science laboratories often involves usage of many different species, cultivars, ecotypes, mutants, alleles or transgenic lines. This creates a great challenge to keep track of the identity of experimental plants and stored samples or seeds.

Results

Here, we describe PlantDB – a Microsoft® Office Access database – with a user-friendly front-end for managing information relevant for experimental plants. PlantDB can hold information about plants of different species, cultivars or genetic composition. Introduction of a concise identifier system allows easy generation of pedigree trees. In addition, all information about any experimental plant – from growth conditions and dates over extracted samples such as RNA to files containing images of the plants – can be linked unequivocally.

Conclusion

We have been using PlantDB for several years in our laboratory and found that it greatly facilitates access to relevant information.

During the past several years, Baylor College of Medicine has made a substantial commitment to the use of information technology in support of its corporate and academic programs. The concept of an Integrated Academic Information Management System (IAIMS) has proved central in our planning, and the IAIMS activities that we have undertaken with funding from the National Library of Medicine have proved to be important extensions of our technology development. Here we describe our Virtual Notebook system, a conceptual and technologic framework for task coordination and information management in biomedical work groups. When fully developed and deployed, the Virtual Notebook will improve the functioning of basic and clinical research groups in the college, and it currently serves as a model for the longer-term development of our entire information management environment.

Objective: To describe the experiences, lessons, and implications of building a virtual network as part of a two-year community health research training program in a Canadian province.

Design: An action research field study in which 25 health professionals from 17 health regions participated in a seven-week training course on health policy, management, economics, research methods, data analysis, and computer technology. The participants then returned to their regions to apply the knowledge in different community health research projects. Ongoing faculty consultations and support were provided as needed. Each participant was given a notebook computer with the necessary software, Internet access, and technical support for two years, to access information resources, engage in group problem solving, share ideas and knowledge, and collaborate on projects.

Measurements: Data collected over two years consisted of program documents, records of interviews with participants and staff, meeting notes, computer usage statistics, automated online surveys, computer conference postings, program Web site, and course feedback. The analysis consisted of detailed review and comparison of the data from different sources. NUD*IST was then used to validate earlier study findings.

Results: The ten key lessons are that role clarity, technology vision, implementation staging, protected time, just-in-time training, ongoing facilitation, work integration, participatory design, relationship building, and the demonstration of results are essential ingredients for building a successful network.

Conclusion: This study provides a descriptive model of the processes involved in developing, in the community health setting, virtual networks that can be used as the basis for future research and as a practical guide for managers.

Sniffy the Virtual Rat Pro Version 2.0 is the most recent update to the Sniffy the Rat program modules. It has an extensive set of simulations related to Pavlovian and operant conditioning. Many of the standard conditioning paradigms and phenomena are contained within this program. Pavlovian effects such as blocking, overshadowing, and stimulus competition are demonstrated in the data output. Operant manipulations allow shaping the behavior of the virtual rat, observing cumulative records of interval and ratio schedules, as well as conducting operant discrimination procedures. In both Pavlovian and operant paradigms, one can generate histograms that predict the degree to which various stimuli control the virtual rat's behavior. On-screen presentations may keep most users interested, but working with the generated data files sometimes can prove difficult. Overall, this program has a strong potential for facilitating the instruction in undergraduate conditioning courses, serving as an addendum to traditional undergraduate conditioning laboratories and as a supplement to the use of live animals.

With massive amounts of data being generated in electronic format, there is a need in basic science laboratories to adopt new methods for tracking and analyzing data. An electronic laboratory notebook (ELN) is not just a replacement for a paper lab notebook, it is a new method of storing and organizing data while maintaining the data entry flexibility and legal recording functions of paper notebooks. Paper notebooks are regarded as highly flexible since the user can configure it to store almost anything that can be written or physically pasted onto the pages. However, data retrieval and data sharing from paper notebooks are labor intensive processes and notebooks can be misplaced, a single point of failure that loses all entries in the volume. Additional features provided by electronic notebooks include searchable indices, data sharing, automatic archiving for security against loss and ease of data duplication. Furthermore, ELNs can be tasked with additional functions not commonly found in paper notebooks such as inventory control. While ELNs have been on the market for some time now, adoption of an ELN in academic basic science laboratories has been lagging. Issues that have restrained development and adoption of ELN in research laboratories are the sheer variety and frequency of changes in protocols with a need for the user to control notebook configuration outside the framework of professional IT staff support. In this commentary, we will look at some of the issues and experiences in academic laboratories that have proved challenging in implementing an electronic lab notebook.

Currently most biomedical labs in universities and government funded research institutions use paper lab notebooks for recording experimental data and spreadsheets for managing sample data. One consequence is that sample management and documenting experiments are viewed as separate and distinct activities, notwithstanding that samples and aliquots are an integral part of a majority of the experiments carried out by these labs.

Various drivers are pushing labs towards integrated management of sample data and experimental data. These include the ever increasing amounts of both kinds of data, the increasing adoption of online collaborative tools, changing expectations about online communication, and the increasing affordability of electronic lab notebooks and sample management software. There is now an opportunity for smaller labs, which have been slow to move from paper to electronic record keeping, to leapfrog better resourced commercial labs and lead the way in adopting the new generation of tools which permit integrated management of samples and experimental data and a range of tangible benefits to conducting research, including:

1. Fewer lost and mislabelled samples

2. Clearer visualization of relationships between samples and experiments

3. Reduction of experimental error

4. More effective search

5. Productivity gains

6. More efficient use of freezers, leading to cost reduction and enhanced sustainability

7. Improved archiving and enhanced memory at the lab and institutional levels

OpusXpress is a semi-automated system for high throughput voltage clamp recording from Xenopus oocytes. We participated in the development process for this system and were the only laboratory to field test a prototype. Subsequently, we obtained an early production model that we have used on a regular basis for the last seven years, conducting many thousands of experiments, publishing extensively, and carrying out collaborative research in drug discovery. In this chapter, we relate our experience with the OpusXpress recording system and large volume oocyte handling. We provide our standard operating procedures and outline the organization of our successful team. Some of our advice is specific to researchers fortunate enough to have access to an OpusXpress system, but most of it is applicable to any group using Xenopus oocytes for the heterologous expression of ion channels.

Background

Today’s biological experiments often involve the collaboration of multidisciplinary researchers utilising several high throughput ‘omics platforms. There is a requirement for the details of the experiment to be adequately described using standardised ontologies to enable data preservation, the analysis of the data and to facilitate the export of the data to public repositories. However there are a bewildering number of ontologies, controlled vocabularies, and minimum standards available for use to describe experiments. There is a need for user-friendly software tools to aid laboratory scientists in capturing the experimental information.

Results

A web application called XperimentR has been developed for use by laboratory scientists, consisting of a browser-based interface and server-side components which provide an intuitive platform for capturing and sharing experimental metadata. Information recorded includes details about the biological samples, procedures, protocols, and experimental technologies, all of which can be easily annotated using the appropriate ontologies. Files and raw data can be imported and associated with the biological samples via the interface, from either users’ computers, or commonly used open-source data repositories. Experiments can be shared with other users, and experiments can be exported in the standard ISA-Tab format for deposition in public databases. XperimentR is freely available and can be installed natively or by using a provided pre-configured Virtual Machine. A guest system is also available for trial purposes.

Conclusion

We present a web based software application to aid the laboratory scientist to capture, describe and share details about their experiments.

Managing changes in source system terms and surveilling for associated deviations in HL7 reporting is an essential, but difficult aspect of a health information exchange. We analyzed the mapping records of the Indiana Network for Patient Care in order to characterize the evolution of radiology and laboratory system terms after initial implementation with regard to term mappings and changes in units of measure. Overall, we added half as many new post-implementation terms (9909) as we added for initial system implementations. As a group, INPC institutions have not slowed much in their rate of adding new terms after initial implementation. In general, we encountered unit-related exceptions less frequently than new, unknown terms. Our study highlights the ongoing effort required to keep up with evolving source system terms in a regional HIE and the need to willingly embrace change along the way.

Background

Much effort is currently made to develop the Gene Ontology (GO). Due to the dynamic nature of information it addresses, GO undergoes constant updates whose results are released at regular intervals as separate versions. Although there are a large number of computational tools to aid the development of GO, they are operating on a particular version of GO, making it difficult for GO curators to anticipate the full impact of particular changes along the time axis on a larger scale. We present a method for tapping into such an evolutionary aspect of GO, by making it possible to keep track of important temporal changes to any of the terms and relations of GO and by consequently making it possible to recognize associated trends.

Results

We have developed visualization methods for viewing the changes between two different versions of GO by constructing a colour-coded layered graph. The graph shows both versions of GO with highlights to those GO terms that are added, removed and modified between the two versions. Focusing on a specific GO term or terms of interest over a period, we demonstrate the utility of our system that can be used to make useful hypotheses about the cause of the evolution and to provide new insights into more complex changes.

Conclusions

GO undergoes fast evolutionary changes. A snapshot of GO, as presented by each version of GO alone, overlooks such evolutionary aspects, and consequently limits the utilities of GO. The method that highlights the differences of consecutive versions or two different versions of an evolving ontology with colour-coding enhances the utility of GO for users as well as for developers. To the best of our knowledge, this is the first proposal to visualize the evolutionary aspect of GO.

Introduction

Critical care physicians may benefit from immediate access to medical reference material. We evaluated the feasibility and potential benefits of a handheld computer based knowledge access system linking a central academic intensive care unit (ICU) to multiple community-based ICUs.

Methods

Four community hospital ICUs with 17 physicians participated in this prospective interventional study. Following training in the use of an internet-linked, updateable handheld computer knowledge access system, the physicians used the handheld devices in their clinical environment for a 12-month intervention period. Feasibility of the system was evaluated by tracking use of the handheld computer and by conducting surveys and focus group discussions. Before and after the intervention period, participants underwent simulated patient care scenarios designed to evaluate the information sources they accessed, as well as the speed and quality of their decision making. Participants generated admission orders during each scenario, which were scored by blinded evaluators.

Results

Ten physicians (59%) used the system regularly, predominantly for nonmedical applications (median 32.8/month, interquartile range [IQR] 28.3–126.8), with medical software accessed less often (median 9/month, IQR 3.7–13.7). Eight out of 13 physicians (62%) who completed the final scenarios chose to use the handheld computer for information access. The median time to access information on the handheld handheld computer was 19 s (IQR 15–40 s). This group exhibited a significant improvement in admission order score as compared with those who used other resources (P = 0.018). Benefits and barriers to use of this technology were identified.

Conclusion

An updateable handheld computer system is feasible as a means of point-of-care access to medical reference material and may improve clinical decision making. However, during the study, acceptance of the system was variable. Improved training and new technology may overcome some of the barriers we identified.

Hospital personnel are exploring ways to increase both production and clinical efficiency in the delivery of health care. Because laboratory information systems (LISs) will play such a critical role in this quest, these systems must perform optimally. The author discusses whether the persistence of older LISs and manual data processing systems within hospital clinical laboratories is related to the “competency trap.” A competency trap occurs when continuing favorable performance with an inferior procedure leads an organization to accumulate more experience with it, thus avoiding experience with a superior procedure or keeping such experience at a low level.

Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers’ time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment.

Background

In recent years, the genome biology community has expended considerable effort to confront the challenges of managing heterogeneous data in a structured and organized way and developed laboratory information management systems (LIMS) for both raw and processed data. On the other hand, electronic notebooks were developed to record and manage scientific data, and facilitate data-sharing. Software which enables both, management of large datasets and digital recording of laboratory procedures would serve a real need in laboratories using medium and high-throughput techniques.

Results

We have developed iLAP (Laboratory data management, Analysis, and Protocol development), a workflow-driven information management system specifically designed to create and manage experimental protocols, and to analyze and share laboratory data. The system combines experimental protocol development, wizard-based data acquisition, and high-throughput data analysis into a single, integrated system. We demonstrate the power and the flexibility of the platform using a microscopy case study based on a combinatorial multiple fluorescence in situ hybridization (m-FISH) protocol and 3D-image reconstruction. iLAP is freely available under the open source license AGPL from http://genome.tugraz.at/iLAP/.

Conclusion

iLAP is a flexible and versatile information management system, which has the potential to close the gap between electronic notebooks and LIMS and can therefore be of great value for a broad scientific community.

Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than with those at an easier reading level. Pruning TOCs to use categories that consumers favor further increases relevancy and correctness while reducing structural complexity.

Students entering Duke Medical School in August, 1987 were introduced to several computer-related activities within the context of the Medical Physiology course as part of the Medical Center's effort to test a model for achieving an Integrated Academic Information Management System (IAIMS). A questionnaire was administered that sought to measure the extent of prior computer experience, the perceived impact of two physiological computer simulation laboratories, and the desired content of future computer training. The survey showed that 85% had some prior experience: for example, 50% had studied programming, 79% have used word-processing software, 24% own a personal computer, and an additional 25% had access to one. Many students expressed the desire for further training in standard applications and in simulation programs. After lab, about 40% reported improved physiologic understanding but no objective effect of the computer laboratories on exam performance was found.

IMGT/GeneInfo is a user-friendly online information system that provides information on data resulting from the complex mechanisms of immunoglobulin (IG) and T cell receptor (TR) V(D)J recombinations. For the first time, it is possible to visualize all the rearrangement parameters on a single page. IMGT/GeneInfo is part of the international ImMunoGeneTics information system® (IMGT), a high-quality integrated knowledge resource specializing in IG, TR, major histocompatibility complex (MHC), and related proteins of the immune system of human and other vertebrate species. The IMGT/GeneInfo system was developed by the TIMC and ICH laboratories (with the collaboration of LIGM), and is the first example of an external system being incorporated into IMGT. In this paper, we report the first part of this work. IMGT/GeneInfo_TR deals with the human and mouse TRA/TRD and TRB loci of the TR. Data handling and visualization are complementary to the current data and tools in IMGT, and will subsequently allow the modelling of V(D)J gene use, and thus, to predict non-standard recombination profiles which may eventually be found in conditions such as leukaemias or lymphomas. Access to IMGT/GeneInfo is free and can be found at http://imgt.cines.fr/GeneInfo.

Recent advances in speech recognition technology have allowed development of computer systems for real-time radiologist-driven generation of reports. The transition to a speech recognition system is a technically complex process with many potential pitfalls that can decrease efficiency and disrupt workflow. In our recent experience with installation of such a system in an academic radiology department, factors that have worked against optimal performance have included environmental logistics, hardware incompatibilities, radiology information system interface problems, lack of suitable training, and inadequate technical support. Communication of our experience is intended to allow radiologists to anticipate complications of these systems and make informed decisions regarding the feasibility of such a system in their practices. With this information, potential buyers should be able to carefully scrutinize specifications for prospective systems and, by avoiding many of the possible pitfalls, make an easier transition to a speech recognition environment.

This paper describes an approach that provides Internet-based support for a genome center to map human chromosome 12, as a collaboration between laboratories at the Albert Einstein College of Medicine in Bronx, New York, and the Yale University School of Medicine in New Haven, Connecticut. Informatics is well established as an important enabling technology within the genome mapping community. The goal of this paper is to use the chromosome 12 project as a case study to introduce a medical informatics audience to certain issues involved in genome informatics and in the Internet-based support of collaborative bioscience research. Central to the approach described is a shared database (DB/12) with Macintosh clients in the participating laboratories running the 4th Dimension database program as a user-friendly front end, and a Sun SPARCstation-2 server running Sybase. The central component of the database stores information about yeast artificial chromosomes (YACs), each containing a segment of human DNA from chromosome 12 to which genome markers have been mapped, such that an overlapping set of YACs (called a "contig") can be identified, along with an ordering of the markers. The approach also includes 1) a map assembly tool developed to help biologists interpret their data, proposing a ranked set of candidate maps, 2) the integration of DB/12 with external databases and tools, and 3) the dissemination of the results. This paper discusses several of the lessons learned that apply to many other areas of bioscience, and the potential role for the field of medical informatics in helping to provide such support.

This paper describes the development of TEXEMS, a statewide information system for two state agencies and over a thousand emergency medical service providers in Texas. The system automates collection, transfer, and analysis of hundreds of variables of information concerning calls for emergency medical care and responses of pre-hospital medical providers. The software incorporates subroutines that provide internal quality control for data entry, automated information transfer via modem and telephone lines, and user-friendly reporting for system management at local, regional, or state levels. Four unusual elements of the TEXEMS system include: (a) a minimum data set to provide a basis for standardized local record keeping and data collection; (b) software to allow local customized databases with subsequent output of standardized files to be included in the state system; (c) automated data transfer into a statewide database; and (d) portability of software within diverse MS-DOS, Macintosh, and Unix micro- and mini-computer operating systems.