1
|
Ahmed AE, Heldenbrand J, Asmann Y, Fadlelmola FM, Katz DS, Kendig K, Kendzior MC, Li T, Ren Y, Rodriguez E, Weber MR, Wozniak JM, Zermeno J, Mainzer LS. Managing genomic variant calling workflows with Swift/T. PLoS One 2019; 14:e0211608. [PMID: 31287816 PMCID: PMC6615596 DOI: 10.1371/journal.pone.0211608] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 06/08/2019] [Indexed: 12/30/2022] Open
Abstract
Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures. The code for our implementation of a variant calling workflow using Swift/T can be found on GitHub at https://github.com/ncsa/Swift-T-Variant-Calling, with full documentation provided at http://swift-t-variant-calling.readthedocs.io/en/latest/.
Collapse
Affiliation(s)
- Azza E. Ahmed
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Khartoum, Khartoum, Sudan
| | - Jacob Heldenbrand
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Yan Asmann
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Faisal M. Fadlelmola
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Daniel S. Katz
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Katherine Kendig
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Matthew C. Kendzior
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Tiffany Li
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Yingxue Ren
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Elliott Rodriguez
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Matthew R. Weber
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Justin M. Wozniak
- Argonne National Laboratory, Argonne, Illinois, United States of America
| | - Jennie Zermeno
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Liudmila S. Mainzer
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
- * E-mail:
| |
Collapse
|
2
|
Samperi R, Capriotti AL, Cavaliere C, Colapicchioni V, Chiozzi RZ, Laganà A. Food Proteins and Peptides. ADVANCED MASS SPECTROMETRY FOR FOOD SAFETY AND QUALITY 2015. [DOI: 10.1016/b978-0-444-63340-8.00006-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
|
3
|
Simonyan V, Mazumder R. High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis. Genes (Basel) 2014; 5:957-81. [PMID: 25271953 PMCID: PMC4276921 DOI: 10.3390/genes5040957] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Revised: 09/22/2014] [Accepted: 09/22/2014] [Indexed: 12/30/2022] Open
Abstract
The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.
Collapse
Affiliation(s)
- Vahan Simonyan
- Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD 20993, USA.
| | - Raja Mazumder
- Department of Biochemistry and Molecular Medicine, George Washington University, Washington, DC 20037, USA.
| |
Collapse
|
4
|
Gan Z, Wang J, Salomonis N, Stowe JC, Haddad GG, McCulloch AD, Altintas I, Zambon AC. MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data. BMC Bioinformatics 2014; 15:69. [PMID: 24621103 PMCID: PMC3975178 DOI: 10.1186/1471-2105-15-69] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2013] [Accepted: 02/27/2014] [Indexed: 12/16/2022] Open
Abstract
Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | - Alexander C Zambon
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA.
| |
Collapse
|
5
|
Liu X, Wu J, Wang J, Liu X, Zhao S, Li Z, Kong L, Gu X, Luo J, Gao G. WebLab: a data-centric, knowledge-sharing bioinformatic platform. Nucleic Acids Res 2009; 37:W33-9. [PMID: 19465388 PMCID: PMC2703900 DOI: 10.1093/nar/gkp428] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
With the rapid progress of biological research, great demands are proposed for integrative knowledge-sharing systems to efficiently support collaboration of biological researchers from various fields. To fulfill such requirements, we have developed a data-centric knowledge-sharing platform WebLab for biologists to fetch, analyze, manipulate and share data under an intuitive web interface. Dedicated space is provided for users to store their input data and analysis results. Users can upload local data or fetch public data from remote databases, and then perform analysis using more than 260 integrated bioinformatic tools. These tools can be further organized as customized analysis workflows to accomplish complex tasks automatically. In addition to conventional biological data, WebLab also provides rich supports for scientific literatures, such as searching against full text of uploaded literatures and exporting citations into various well-known citation managers such as EndNote and BibTex. To facilitate team work among colleagues, WebLab provides a powerful and flexible sharing mechanism, which allows users to share input data, analysis results, scientific literatures and customized workflows to specified users or groups with sophisticated privilege settings. WebLab is publicly available at http://weblab.cbi.pku.edu.cn, with all source code released as Free Software.
Collapse
Affiliation(s)
- Xiaoqiao Liu
- Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, China
| | | | | | | | | | | | | | | | | | | |
Collapse
|
6
|
Aravindhan G, Kumar GR, Kumar RS, Subha K. AJAX Interface: A Breakthrough in Bioinformatics Web Applications. PROTEOMICS INSIGHTS 2009. [DOI: 10.4137/pri.s2261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Bioinformatics applications are generally multi-server dependants and will have to communicate several information repositories to carry out any analyses. These applications remain computationally intensive and time consuming as they engage lots of data transfer. Hence they face a major bottleneck when ported as web applications. Browser based web applications normally feature the classical request-response approach. If the response becomes late, as it is expected to happen in the case of long running Bioinformatics programs, Apache will get tired and a request timeout error might occur. Alternate approaches like “Client-Pull” models that involve polling strategy with the unpredictable amount of page refreshes, only tend to intensify the network traffic. Hence a technology that is intelligent enough to support the varied exhaustive Bioinformatics processes becomes highly essential. In this review, we propose how AJAX can afford a laconic framework within the Bioinformatics applications to completely reduce the page refresh nuisance and provide a better user experience.
Collapse
Affiliation(s)
- G. Aravindhan
- Bioinformatics Division, AU-KBC Research Centre, MIT Campus, Anna University, Chennai-600 044, India
| | - G. Ramesh Kumar
- Bioinformatics Division, AU-KBC Research Centre, MIT Campus, Anna University, Chennai-600 044, India
| | - R. Sathish Kumar
- NRCFOSS, AU-KBC Research Centre, MIT Campus, Anna University, Chennai-600 044, India
| | - K. Subha
- Bioinformatics Division, AU-KBC Research Centre, MIT Campus, Anna University, Chennai-600 044, India
| |
Collapse
|
7
|
Abstract
The development of affordable, high-throughput sequencing technology has led to a flood of publicly available bacterial genome-sequence data. The availability of multiple genome sequences presents both an opportunity and a challenge for microbiologists, and new computational approaches are needed to extract the knowledge that is required to address specific biological problems and to analyse genomic data. The field of e-Science is maturing, and Grid-based technologies can help address this challenge.
Collapse
|
8
|
Sagotsky JA, Zhang L, Wang Z, Martin S, Deisboeck TS. Life Sciences and the web: a new era for collaboration. Mol Syst Biol 2008; 4:201. [PMID: 18594519 PMCID: PMC2516361 DOI: 10.1038/msb.2008.39] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2008] [Accepted: 05/21/2008] [Indexed: 11/09/2022] Open
Abstract
The World Wide Web has revolutionized how researchers from various disciplines collaborate over long distances. This is nowhere more important than in the Life Sciences, where interdisciplinary approaches are becoming increasingly powerful as a driver of both integration and discovery. Data access, data quality, identity, and provenance are all critical ingredients to facilitate and accelerate these collaborative enterprises and it is here where Semantic Web technologies promise to have a profound impact. This paper reviews the need for, and explores advantages of as well as challenges with these novel Internet information tools as illustrated with examples from the biomedical community.
Collapse
Affiliation(s)
- Jonathan A Sagotsky
- Complex Biosystems Modeling Laboratory, Harvard-MIT (HST) Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | | | | | | | | |
Collapse
|
9
|
Navas-Delgado I, Montañez R, Pino-Angeles A, Moya-García AA, Urdiales JL, Sánchez-Jiménez F, Aldana-Montes JF. AMMO-Prot: amine system project 3D-model finder. BMC Bioinformatics 2008; 9 Suppl 4:S5. [PMID: 18460178 PMCID: PMC2367632 DOI: 10.1186/1471-2105-9-s4-s5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Background Amines are biogenic amino acid derivatives, which play pleiotropic and very important yet complex roles in animal physiology. For many other relevant biomolecules, biochemical and molecular data are being accumulated, which need to be integrated in order to be effective in the advance of biological knowledge in the field. For this purpose, a multidisciplinary group has started an ontology-based system named the Amine System Project (ASP) for which amine-related information is the validation bench. Results In this paper, we describe the Ontology-Based Mediator developed in the Amine System Project () using the infrastructure of Semantic Directories, and how this system has been used to solve a case related to amine metabolism-related protein structures. Conclusions This infrastructure is used to publish and manage not only ontologies and their relationships, but also metadata relating to the resources committed with the ontologies. The system developed is available at .
Collapse
Affiliation(s)
- Ismael Navas-Delgado
- Computer Languages and Computing Science Department, University of Málaga, Málaga, 29071, Spain.
| | | | | | | | | | | | | |
Collapse
|
10
|
Fiers MWEJ, van der Burgt A, Datema E, de Groot JCW, van Ham RCHJ. High-throughput bioinformatics with the Cyrille2 pipeline system. BMC Bioinformatics 2008; 9:96. [PMID: 18269742 PMCID: PMC2268656 DOI: 10.1186/1471-2105-9-96] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2007] [Accepted: 02/12/2008] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. RESULTS We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1) a web based, graphical user interface (GUI) that enables a pipeline operator to manage the system; 2) the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3) the Executor, which searches for scheduled jobs and executes these on a compute cluster. CONCLUSION The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.
Collapse
Affiliation(s)
- Mark W E J Fiers
- Applied Bioinformatics, Plant Research International, PO Box 16, 6700AA Wageningen, The Netherlands.
| | | | | | | | | |
Collapse
|
11
|
Hauth AM, Burger G. Methodology for Constructing Problem Definitions in Bioinformatics. Bioinform Biol Insights 2008; 2:239-51. [PMID: 19812779 PMCID: PMC2735962 DOI: 10.4137/bbi.s706] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Motivation A recurrent criticism is that certain bioinformatics tools do not account for crucial biology and therefore fail answering the targeted biological question. We posit that the single most important reason for such shortcomings is an inaccurate formulation of the computational problem. Results Our paper describes how to define a bioinformatics problem so that it captures both the underlying biology and the computational constraints for a particular problem. The proposed model delineates comprehensively the biological problem and conducts an item-by-item bioinformatics transformation resulting in a germane computational problem. This methodology not only facilitates interdisciplinary information flow but also accommodates emerging knowledge and technologies.
Collapse
Affiliation(s)
- Amy M. Hauth
- Robert Cedergren Center for Bioinformatics and Genomics, Département de Biochimie, Université de Montréal, 2900 Boulevard Edouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
| | - Gertraud Burger
- Robert Cedergren Center for Bioinformatics and Genomics, Département de Biochimie, Université de Montréal, 2900 Boulevard Edouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
| |
Collapse
|
12
|
Bartocci E, Corradini F, Merelli E, Scortichini L. BioWMS: a web-based Workflow Management System for bioinformatics. BMC Bioinformatics 2007; 8 Suppl 1:S2. [PMID: 17430564 PMCID: PMC1885849 DOI: 10.1186/1471-2105-8-s1-s2] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background An in-silico experiment can be naturally specified as a workflow of activities implementing, in a standardized environment, the process of data and control analysis. A workflow has the advantage to be reproducible, traceable and compositional by reusing other workflows. In order to support the daily work of a bioscientist, several Workflow Management Systems (WMSs) have been proposed in bioinformatics. Generally, these systems centralize the workflow enactment and do not exploit standard process definition languages to describe, in order to be reusable, workflows. While almost all WMSs require heavy stand-alone applications to specify new workflows, only few of them provide a web-based process definition tool. Results We have developed BioWMS, a Workflow Management System that supports, through a web-based interface, the definition, the execution and the results management of an in-silico experiment. BioWMS has been implemented over an agent-based middleware. It dynamically generates, from a user workflow specification, a domain-specific, agent-based workflow engine. Our approach exploits the proactiveness and mobility of the agent-based technology to embed, inside agents behaviour, the application domain features. Agents are workflow executors and the resulting workflow engine is a multiagent system – a distributed, concurrent system – typically open, flexible, and adaptative. A demo is available at . Conclusion BioWMS, supported by Hermes mobile computing middleware, guarantees the flexibility, scalability and fault tolerance required to a workflow enactment over distributed and heterogeneous environment. BioWMS is funded by the FIRB project LITBIO (Laboratory for Interdisciplinary Technologies in Bioinformatics).
Collapse
Affiliation(s)
- Ezio Bartocci
- Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n.9, Camerino(MC), I-62032, Italy
| | - Flavio Corradini
- Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n.9, Camerino(MC), I-62032, Italy
| | - Emanuela Merelli
- Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n.9, Camerino(MC), I-62032, Italy
| | - Lorenzo Scortichini
- Dipartimento di Matematica e Informatica, Università di Camerino, Via Madonna delle Carceri n.9, Camerino(MC), I-62032, Italy
| |
Collapse
|
13
|
Swertz MA, Jansen RC. Beyond standardization: dynamic software infrastructures for systems biology. Nat Rev Genet 2007; 8:235-43. [PMID: 17297480 DOI: 10.1038/nrg2048] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Progress in systems biology is seriously hindered by slow production of suitable software infrastructures. Biologists need infrastructure that easily connects to work that is done in other laboratories, for which standardization is helpful. However, the infrastructure must also accommodate the specifics of their biological system, but appropriate mechanisms to support variation are currently lacking. We argue that a minimal computer language, and a software tool called a generator, can be used to quickly produce customized software infrastructures that 'systems biologists really want to have'.
Collapse
Affiliation(s)
- Morris A Swertz
- Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, NL-9751 NN Haren, The Netherlands
| | | |
Collapse
|
14
|
Conceptual-level workflow modeling of scientific experiments using NMR as a case study. BMC Bioinformatics 2007; 8:31. [PMID: 17263870 PMCID: PMC1796901 DOI: 10.1186/1471-2105-8-31] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2006] [Accepted: 01/30/2007] [Indexed: 11/29/2022] Open
Abstract
Background Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. Results We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Conclusion Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment.
Collapse
|
15
|
Abstract
Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.
Collapse
Affiliation(s)
- Alexander Garcia Castro
- ARC Centre in Bioinformatics, and Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | | | | |
Collapse
|
16
|
Abstract
UNLABELLED Emerging web-services technology allows interoperability between multiple distributed architectures. Here, we present REMORA, a web server implemented according to the BioMoby web-service specifications, providing life science researchers with an easy-to-use workflow generator and launcher, a repository of predefined workflows and a survey system. CONTACT Jerome.Gouzy@toulouse.inra.fr AVAILABILITY The REMORA web server is freely available at http://bioinfo.genopole-toulouse.prd.fr/remora, sources are available upon request from the authors.
Collapse
Affiliation(s)
- Sébastien Carrere
- INRA-CNRS Laboratoire des Interactions Plantes Micro-organismes (LIPM) BP 52627, 31326 Castanet Tolosan Cedex, France
| | | |
Collapse
|
17
|
Lehtovuori PT, Nyrönen TH. SOMA − Workflow for Small Molecule Property Calculations on a Multiplatform Computing Grid. J Chem Inf Model 2006; 46:620-5. [PMID: 16562991 DOI: 10.1021/ci050388n] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We present the concept of the SOMA workflow developed at the Finnish IT Center for Science CSC. The SOMA workflow unites multiplatform UNIX/LINUX computing resources and third-party software for calculating molecular structure and properties. The presented workflow components consist of the computing program XML descriptions, the core workflow program Grape, the toolkit for parsing program input and output, and the extranet interface. The program Grape and the developed XML descriptions of scientific programs allow researchers to link molecular modeling software into highly sophisticated computational workflows. SOMA collects the calculated data produced by the workflow and stores the computed information in the Chemical Markup Language (CML) format. The extranet interface is used for user authentication, building of the program interfaces and the workflows, and for sorting, filtering, and visualizing the results.
Collapse
Affiliation(s)
- Pekka T Lehtovuori
- The Finnish IT Center for Science CSC, P.O. Box 405, FI-02101 Espoo, Finland.
| | | |
Collapse
|