iBIOMES Lite: summarizing biomolecular simulation data in limited settings.

As the amount of data generated by biomolecular simulations dramatically increases, new tools need to be developed to help manage this data at the individual investigator or small research group level. In this paper, we introduce iBIOMES Lite, a lightweight tool for biomolecular simulation data indexing and summarization. The main goal of iBIOMES Lite is to provide a simple interface to summarize computational experiments in a setting where the user might have limited privileges and limited access to IT resources. A command-line interface allows the user to summarize, publish, and search local simulation data sets. Published data sets are accessible via static hypertext markup language (HTML) pages that summarize the simulation protocols and also display data analysis graphically. The publication process is customized via extensible markup language (XML) descriptors while the HTML summary template is customized through extensible stylesheet language (XSL). iBIOMES Lite was tested on different platforms and at several national computing centers using various data sets generated through classical and quantum molecular dynamics, quantum chemistry, and QM/MM. The associated parsers currently support AMBER, GROMACS, Gaussian, and NWChem data set publication. The code is available at https://github.com/jcvthibault/ibiomes .

Data model, dictionaries, and desiderata for biomolecular simulation data indexing and sharing.

BACKGROUND: Few environments have been developed or deployed to widely share biomolecular simulation data or to enable collaborative networks to facilitate data exploration and reuse. As the amount and complexity of data generated by these simulations is dramatically increasing and the methods are being more widely applied, the need for new tools to manage and share this data has become obvious. In this paper we present the results of a process aimed at assessing the needs of the community for data representation standards to guide the implementation of future repositories for biomolecular simulations. RESULTS: We introduce a list of common data elements, inspired by previous work, and updated according to feedback from the community collected through a survey and personal interviews. These data elements integrate the concepts for multiple types of computational methods, including quantum chemistry and molecular dynamics. The identified core data elements were organized into a logical model to guide the design of new databases and application programming interfaces. Finally a set of dictionaries was implemented to be used via SQL queries or locally via a Java API built upon the Apache Lucene text-search engine. CONCLUSIONS: The model and its associated dictionaries provide a simple yet rich representation of the concepts related to biomolecular simulations, which should guide future developments of repositories and more complex terminologies and ontologies. The model still remains extensible through the decomposition of virtual experiments into tasks and parameter sets, and via the use of extended attributes. The benefits of a common logical model for biomolecular simulations was illustrated through various use cases, including data storage, indexing, and presentation. All the models and dictionaries introduced in this paper are available for download at http://ibiomes.chpc.utah.edu/mediawiki/index.php/Downloads.

Biomedical Terminology Mapper for UML projects.

As the biomedical community collects and generates more and more data, the need to describe these datasets for exchange and interoperability becomes crucial. This paper presents a mapping algorithm that can help developers expose local implementations described with UML through standard terminologies. The input UML class or attribute name is first normalized and tokenized, then lookups in a UMLS-based dictionary are performed. For the evaluation of the algorithm 142 UML projects were extracted from caGrid and automatically mapped to National Cancer Institute (NCI) terminology concepts. Resulting mappings at the UML class and attribute levels were compared to the manually curated annotations provided in caGrid. Results are promising and show that this type of algorithm could speed-up the tedious process of mapping local implementations to standard biomedical terminologies.

iBIOMES: managing and sharing biomolecular simulation data in a distributed environment.

Biomolecular simulations, which were once batch queue or compute limited, have now become data analysis and management limited. In this paper we introduce a new management system for large biomolecular simulation and computational chemistry data sets. The system can be easily deployed on distributed servers to create a mini-grid at the researcher's site. The system not only offers a simple data deposition mechanism but also a way to register data into the system without moving the data from their original location. Any registered data set can be searched and downloaded using a set of defined metadata for molecular dynamics and quantum mechanics and visualized through a dynamic Web interface.