skip to main content
10.1145/2506583.2506621acmconferencesArticle/Chapter ViewAbstractPublication PagesbcbConference Proceedingsconference-collections
tutorial

PathCase-MAW: An Online Metabolic Network Analysis Workbench

Authors Info & Claims
Published:22 September 2013Publication History

ABSTRACT

Metabolic networks have become one of the centers of attention in life sciences research with the advancements in the metabolomics field. A vast array of studies analyzes metabolites and their interrelations to seek explanations for various biological questions, and numerous genome-scale metabolic networks have been assembled to serve for this purpose. The increasing focus on this topic comes with the need for software systems that store, query, browse, analyze, and visualize metabolic networks. PathCase Metabolomics Analysis Workbench (PathCaseMAW) is built, released, and running on a manually created generic mammalian metabolic network. The PathCaseMAW system provides a database-enabled framework and web-based computational tools for browsing, querying, analyzing, and visualizing stored metabolic networks. PathCaseMAW editor, with its user-friendly interface, can be used to create a new metabolic network and/or update an existing metabolic network. The network can also be created from an existing genome-scale reconstructed network using the PathCaseMAW SBML parser. The metabolic network can be accessed through a web interface or an iPad application. For metabolomics analysis, Steady-State Metabolic Network Dynamics Analysis (SMDA) algorithm is implemented and integrated with the system. SMDA tool is accessible through both the web-based interface and the iPad application for metabolomics analysis based on a metabolic profile. PathCaseMAW is a comprehensive system with various data input and data access sub-systems. It is easy to work with by design, and is a promising tool for metabolomics research and for educational purposes.

References

  1. Fell, D. A. 1997. Understanding the control of metabolism. Portland Press, London, UK.Google ScholarGoogle Scholar
  2. Schilling, C.H., Schuster, S., Palsson, B.O., Heinrich, R. 1999. Metabolic Pathway Analysis: basic concepts and scientific applications in the post-genomic era. Biotechnol Prog. 15, 296--303.Google ScholarGoogle ScholarCross RefCross Ref
  3. Feist, A.M., Palsson, B.O. 2008. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. Nat Biotechnol 26, 6, 659--667.Google ScholarGoogle ScholarCross RefCross Ref
  4. Zelezniak, A., Pers, T.H., Soares, S., Patti, M.E., Patil, K.R. 2010. Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes. PLoS Comput Biol, 6, 4, e1000729.Google ScholarGoogle ScholarCross RefCross Ref
  5. Patil, K.R., Nielsen, J. 2005. Uncovering transcriptional regulation of metabolism by using metabolic network topology. Proc Natl Acad Sci USA 102, 2685--2689.Google ScholarGoogle ScholarCross RefCross Ref
  6. David, H., Hofmann, G., Oliveira, A.P., Jarmer, H., Nielsen, J. 2006. Metabolic network driven analysis of genome-wide transcription data from Aspergillus nidulans. Genome Biol 7, R108.Google ScholarGoogle ScholarCross RefCross Ref
  7. Cicek, A.E., Bederman, I., Henderson, L., Drumm, M.L., Ozsoyoglu, G. 2013. ADEMA: An Algorithm to Determine Expected Metabolite Level Alterations Using Mutual Information PLoS Comput Biol, 9, 1, e1002859. doi:10.1371/journal.pcbi.1002859.Google ScholarGoogle Scholar
  8. Duarte, N.C., Becker, S.A., Jamshidi, N., Thiele, I., Mo, M.L., Vo, T.D., Srivas, R., Palsson, B.O. 2007. Global reconstruction of the human metabolic network based on genomic and bibliomic data. PNAS 104, 6, 1777--1782.Google ScholarGoogle ScholarCross RefCross Ref
  9. Salway, J.G. 2006. Metabolism at a Glance Third Edition. Blackwell Publishing, Malden, MI.Google ScholarGoogle Scholar
  10. PathCase-RCMN {http://nashua.case.edu/PathCaseRCMN/Web/}Google ScholarGoogle Scholar
  11. Cakmak, A., Qi, X., Cicek, A.E., Bederman, I., Henderson, L., Drumm, M.L., Ozsoyoglu, G. 2012. A New Metabolomics Analysis Technique: Steady-State Metabolic Network Dynamics Analysis. J Bioinform Comput Biol 10, 1, 36.Google ScholarGoogle ScholarCross RefCross Ref
  12. Cicek, A.E., Ozsoyoglu, G. 2012. Observation Conflict Resolution in Steady-State Metabolic Network Dynamics Analysis. J Bioinform Comput Biol 10, 1, 25.Google ScholarGoogle ScholarCross RefCross Ref
  13. Cakmak, A., Ozsoyoglu, G., Hanson, R.W. 2012. Querying Metabolism under Different Physiological Constraints. J Bioinform Comput Biol, 8, 2, 247--293.Google ScholarGoogle ScholarCross RefCross Ref
  14. Cakmak, A., Ozsoyoglu, G., Hanson, R.W. 2012. Managing and Querying Mammalian Metabolic Networks: A Metabolism Query Language and Its Query Processing. In Proceedings of 8th International Conference on Computational Systems Bioinformatics (Stanford, CA, August 10-13, 2009). CSB '09.Google ScholarGoogle Scholar
  15. Wishart, D.S., Knox, C., Guo, A.C., Eisner, R., Young, N., Gautam, B., Hau, D.D., Psychogios, N., Dong, E., Bouatra, S., Mandal, R., Sinelnikov, I., Xia, J., Jia, L., Cruz, J.A., Lim, E., Sobsey, C.A., Shrivastava, S., Huang, P., Liu, P., Fang, L., Peng, J., Fradette, R., Cheng, D., Tzur, D., Clements, M., Lewis, A., De Souza, A., Zuniga, A., et. al. 2009. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37(Database issue), D603--610.Google ScholarGoogle Scholar
  16. Apple Press Info {http://www.apple.com/pr/library/2011/07/19Apple-Reports-Third-Quarter-Results.html}Google ScholarGoogle Scholar
  17. Apple Education {http://www.apple.com/education/ipad/}Google ScholarGoogle Scholar
  18. Sabah Newspaper: Turkish Ministry of National Education distributes tablets in schools {http://english.sabah.com.tr/National/2012/02/01/distribution-of-free-tablets-to-students-has-begun}Google ScholarGoogle Scholar
  19. Hucka, M., Finney, A.M., Hoops, S., Keating, S.M., Le Novere, N. 2007. Systems Biology Markup Language (SBML) Level 2: Structures and Facilities for Model definitions. Sept. 26, 2007.Google ScholarGoogle Scholar
  20. Das, M. 2009. Parsing BioModels and CellML Models and insertion of data. Masters Project. Case Western Reserve University, Electrical Engineering and Computer Science Department.Google ScholarGoogle Scholar
  21. PathCase-Systems Biology Web Site {http://nashua.case.edu/PathwaysSB/Web}Google ScholarGoogle Scholar
  22. Cakmak, A., Qi, X., Coskun, S.A., Das, M., Cheng, E., Cicek AE, Lai N, Ozsoyoglu ZM, Ozsoyoglu G: PathCase-SB Architecture and Database Design. BMC Systems Biology 2011, 5:188.Google ScholarGoogle Scholar
  23. Elliott, B., Kirac, M., Cakmak, A., Yavas, G., Mayes, S., Cheng, E., Wang, Y., Gupta, C., Ozsoyoglu, G., Ozsoyoglu, Z.M. 2006 PathCase: pathways database system. Bioinformatics, 24: 2526--2533. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Le Novère, N., Bornstein, B., Broicher, A., Courtot, M., Donizelli, M., Dharuri, H., Li, L., Sauro, H., Schilstra, M., Shapiro, B., Snoep, J.L., Hucka, M. 2006. BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Research, 34(Database-Issue), 689--691.Google ScholarGoogle Scholar
  25. Bornstein, B.J., Keating, S.M., Jouraku, A., Hucka, M. 2008 LibSBML: an API Library for SBML. Bioinformatics, 24, 6, 880--881. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. KEGG (Kyoto Encyplopedia of Genes and Genomes) Pathways {http://www.genome.jp/KEGG/pathway.html}Google ScholarGoogle Scholar
  27. Kanehisa, M., Goto, S. 2000. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res, 28, 27--30.Google ScholarGoogle ScholarCross RefCross Ref
  28. Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., Hirakawa, M. 2006. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res, 34, D354--357.Google ScholarGoogle ScholarCross RefCross Ref
  29. Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., Hirakawa, M. 2010. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res, 38, D355-D360.Google ScholarGoogle ScholarCross RefCross Ref
  30. PathCase-KEGG {http://nashua.case.edu/PathwaysKegg/Web/Google ScholarGoogle Scholar
  31. Johnson, S.R., Qi, X., Cicek, A.E., Ozsoyoglu, G. 2013 iPathCaseKEGG: an iPad interface for KEGG metabolic pathways. Health Inf Sci Syst, 1, 4.Google ScholarGoogle ScholarCross RefCross Ref
  32. Caspi, R., Altman, T., Dale, J.M., Dreher, K., Fulcher, C.A., Gilham, F., Kaipa, P., Karthikeyan, A.S., Kothari, A., Krummenacker, M., Latendresse, M., Mueller, L.A., Paley, S., Popescu, L., Pujar, A., Shearer, A.G., Zhang, P., Karp, P.D. 2010. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research, 38, D473--9.Google ScholarGoogle ScholarCross RefCross Ref
  33. Paley, S.M., Karp, P.D. 2002. Evaluation of computational metabolic-pathway predictions for H. pylori. Bioinformatics 18, 715--24.Google ScholarGoogle ScholarCross RefCross Ref
  34. Karp, P.D., Paley, S.M., Krummenacker, M., Latendresse, M., Dale, J.M., Lee, T., Kaipa, P., Gilham, F., Spaulding, A., Popescu, L., Altman, T., Paulsen, I., Keseler, I.M., Caspi, R. 2010. Pathway Tools version 13.0: Integrated Software for Pathway/Genome Informatics and Systems Biology. Briefings in Bioinformatics, 11, 40--79.Google ScholarGoogle ScholarCross RefCross Ref
  35. Keseler, I.M., Collado-Vides, J., Santos-Zavaleta, A., Peralta-Gil, M., Gama-Castro, S., Muniz-Rascado, L., Bonavides-Martinez, C., Paley, S., Krummenacker, M., Altman, T., Kaipa, P., Spaulding, A., Pacheco, J., Latendresse, M., Fulcher, C., Sarker, M., Shearer, A.G., Mackie, A., Paulsen, I., Gunsalus, R.P., Karp, P.D. 2011. EcoCyc: a comprehensive database of Escherichia coli biology. Nucleic Acids Research, 39, D583--590.Google ScholarGoogle ScholarCross RefCross Ref
  36. Matthews, L., Gopinath, G., Gillespie, M., Caudy, M., Croft, D., de Bono, B., Garapati, P., Hemish, J., Hermjakob, H., Jassal, B., Kanapin, A., Lewis, S., Mahajan, S., May, B., Schmidt, E., Vastrik, I., Wu, G., Birney, E., Stein, L., D'Eustachio, P. 2008. Reactome knowledgebase of biological pathways and processes. Nucleic Acids Res, 37(Database issue), D619--22.Google ScholarGoogle Scholar
  37. Matthews, L., D'Eustachio, P., Gillespie, M., Croft, D., de Bono, B., Gopinath, G., Jassal, B., Lewis, S., Schmidt, E., Vastrik, I., Wu, G., Birney, E., Stein, L. 2007. An Introduction to the Reactome Knowledgebase of Human Biological Pathways and Processes. Bioinformatics Primer, NCI/Nature Pathway Interaction Database. doi:10.1038/pid.2007.3Google ScholarGoogle Scholar
  38. Vastrik, I., D'Eustachio, P., Schmidt, E., Joshi-Tope, G., Gopinath, G., Croft, D., de Bono, B., Gillespie, M., Jassal, B., Lewis, S., Matthews, L., Wu, G., Birney, E., Stein, L. 2007. Reactome: a knowledge base of biologic pathways and processes. Genome Biology, 8, R39.Google ScholarGoogle ScholarCross RefCross Ref
  39. Joshi-Tope, G., Vastrik, I., Gopinathrao, G., Matthews, L., Schmidt, E., Gillespie, M., D'Eustachio, P., Jassal, B., Lewis, S., Wu, G., Birney, E., Stein, L. 2003. The Genome Knowledgebase: A Resource for Biologists and Bioinformaticists. Cold Spring Harb Symp Quant Biol., 68, 237--43.Google ScholarGoogle Scholar
  40. Pabinger, S., Rader, R., Agren, R., Nielsen, J., Trajanoski, Z. 2011 MEMOSys: Bioinformatics platform for genome-scale metabolic models. BMC Syst Biol, 5, 20.Google ScholarGoogle ScholarCross RefCross Ref
  41. Ma, H., Sorokin, A., Mazein, A., Selkov, A., Selkov, E., Demin, O., Goryanin, I. 2007. The edinburgh human metabolic network reconstruction and its functional analysis. Mol Syst Biol, 3, 135.Google ScholarGoogle ScholarCross RefCross Ref
  42. Alshalwi S 2012. PathCase-RCMN: ReconstruCted Metabolic Networks of organisms. Masters Project. Case Western Reserve University, Electrical Engineering and Computer Science Department.Google ScholarGoogle Scholar

Index Terms

  1. PathCase-MAW: An Online Metabolic Network Analysis Workbench

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in
              • Published in

                cover image ACM Conferences
                BCB'13: Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
                September 2013
                987 pages
                ISBN:9781450324342
                DOI:10.1145/2506583

                Copyright © 2013 ACM

                Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 22 September 2013

                Permissions

                Request permissions about this article.

                Request Permissions

                Check for updates

                Qualifiers

                • tutorial
                • Research
                • Refereed limited

                Acceptance Rates

                BCB'13 Paper Acceptance Rate43of148submissions,29%Overall Acceptance Rate254of885submissions,29%
              • Article Metrics

                • Downloads (Last 12 months)1
                • Downloads (Last 6 weeks)0

                Other Metrics

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader