BioCyc database collection

The BioCyc database collection is an assortment of organism specific Pathway/ Genome Databases (PGDBs). They provide reference to genome and metabolic pathways of few thousand organisms.[1] As of June 23, 2014, there are 3563 databases within BioCyc. The list of databases can be found here. SRI International,[2] based in Menlo Park, California, maintains the BioCyc database family.

Categories of Databases within BioCyc:

Based on the manual curation done, BioCyc database family is divided into 3 tiers:

Tier 1: Databases which have received at least one year literature based manual curation. Currently there are seven databases in Tier 1. Out of the seven, MetaCyc is a major database that contains metabolic pathways for 2063 organisms.[1][3] The other important Tier 1 database is HumanCyc which contains around 250 metabolic pathways found in humans.[4] The remaining five databases include, EcoCyc (E. coli),[5] AraCyc (Arabidopsis thaliana), YeastCyc (Saccharomyces cerevisiae), LeishCyc (Leishmania major Friedlin) and TrypanoCyc (Trypanosoma brucei).

Tier 2: Databases which are computationally predicted by PathoLogic but have received moderate manual curation (most with 1–4 months curation). Tier 2 Databases are available for manual curation by scientists who are interested in any particular organism. Tier 2 databases currently contain 36 different organism databases.

Tier 3: Databases which are computationally predicted by PathoLogic and received no manual curation. As with Tier 2, Tier 3 databases are also available for curation for interested scientists.

Software Tools within BioCyc:

The BioCyc website contains a variety of software tools for searching, visualizing, comparing, and analyzing genome and pathway information. It includes a genome browser, and browsers for metabolic and regulatory networks. The website also includes tools for painting large-scale ("omics") datasets onto metabolic and regulatory networks, and onto the genome.

Pathway Tools Software:

The Pathway Tools is a comprehensive systems biology software that allows:[6][7][8]

The Pathway Tools software had four main components:[9]

  1. PathoLogic: Algorithm that takes Genbank entry as input and creates the new PGDB containing the predicted metabolic pathways of an organism.
  2. Pathway/Genome Navigator: Allows query, visualization, and analysis of PGDBs.
  3. MetaFlux: Allows development of metabolic flux models.
  4. Pathway/Genome Editors: Provides interactive editing capabilities for PGDBs.

BioCyc databases rely on a software system called Pathway Tools for their initial generation, subsequent updating, and for querying their content. The databases can also be installed locally.

All BioCyc databases share the same database schema, which facilitates comparisons across the databases.

Use of BioCyc Database Collection in Research:

Since BioCyc Database family comprises a long list of organism specific databases and also data at different systems level in a living system, the usage in research has been in a wide variety of context. Here, two studies are highlighted which show two different varieties of uses, one on a genome scale and other on identifying specific SNPs (Single Nucleotide Polymorphisms) within a genome.

AlgaGEM

AlgaGEM is a genome scale metabolic network model for a compartmentalized algae cell developed by Gomes de Oliveira Dal’Molin et al.[10] based on Chlamydomonas reinhardtii genome. It has 866 unique ORFs, 1862 metabolites, 2499 gene-enzyme-reaction-association entries, and 1725 unique reactions. One of the Pathway databases used for reconstruction is MetaCyc.

SNPs

The study by Shimul Chowdhury et al.[11] showed association differed between maternal SNPs and metabolites involved in homocysteine, folate, and transsulfuration pathways in cases with Congenital Heart Defects (CHDs) as opposed to controls. The study used HumanCyc to select candidate genes and SNPs.

References

  1. 1 2 Caspi, R.; Altman, T.; Dreher, K.; Fulcher, C. A.; Subhraveti, P.; Keseler, I. M.; Kothari, A.; Krummenacker, M.; Latendresse, M.; Mueller, L. A.; Ong, Q.; Paley, S.; Pujar, A.; Shearer, A. G.; Travers, M.; Weerasinghe, D.; Zhang, P.; Karp, P. D. (2011). "The Meta Cyc database of metabolic pathways and enzymes and the Bio Cyc collection of pathway/genome databases". Nucleic Acids Research 40 (Database issue): D742–53. doi:10.1093/nar/gkr1014. PMC 3245006. PMID 22102576.
  2. ↑ Home page of the SRI International
  3. ↑ Karp, Peter D.; Caspi, Ron (2011). "A survey of metabolic databases emphasizing the Meta Cyc family". Archives of Toxicology 85 (9): 1015–33. doi:10.1007/s00204-011-0705-2. PMC 3352032. PMID 21523460.
  4. ↑ Romero, Pedro; Wagg, Jonathan; Green, Michelle L; Kaiser, Dale; Krummenacker, Markus; Karp, Peter D (2004). "Computational prediction of human metabolic pathways from the complete human genome". Genome Biology 6 (1): R2. doi:10.1186/gb-2004-6-1-r2. PMC 549063. PMID 15642094.
  5. ↑ 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. (2010). "Eco Cyc: A comprehensive database of Escherichia coli biology". Nucleic Acids Research 39 (Database issue): D583–90. doi:10.1093/nar/gkq1143. PMC 3013716. PMID 21097882.
  6. ↑ Karp, P. D.; Paley, S. M.; Krummenacker, M; Latendresse, M; Dale, J. M.; Lee, T. J.; 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 (1): 40–79. doi:10.1093/bib/bbp043. PMC 2810111. PMID 19955237.
  7. ↑ Karp, P. D.; Paley, S; Romero, P (2002). "The Pathway Tools software". Bioinformatics (Oxford, England). 18 Suppl 1: S225–32. doi:10.1093/bioinformatics/18.suppl_1.s225. PMID 12169551.
  8. ↑ Karp, P. D.; Paley, S (1996). "Integrated access to metabolic and genomic data". Journal of computational biology : a journal of computational molecular cell biology 3 (1): 191–212. doi:10.1089/cmb.1996.3.191. PMID 8697237.
  9. ↑ Krummenacker, M; Paley, S; Mueller, L; Yan, T; Karp, P. D. (2005). "Querying and Computing with Bio Cyc Databases". Bioinformatics 21 (16): 3454–3455. doi:10.1093/bioinformatics/bti546. PMC 1450015. PMID 15961440.
  10. ↑ Dal'Molin, C. G.; Quek, L. E.; Palfreyman, R. W.; Nielsen, L. K. (2011). "AlgaGEM--a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome". BMC Genomics. 12 Suppl 4: S5. doi:10.1186/1471-2164-12-S4-S5. PMC 3287588. PMID 22369158.
  11. ↑ Chowdhury, S; Hobbs, C. A.; MacLeod, S. L.; Cleves, M. A.; Melnyk, S; James, S. J.; Hu, P; Erickson, S. W. (2012). "Associations between maternal genotypes and metabolites implicated in congenital heart defects". Molecular Genetics and Metabolism 107 (3): 596–604. doi:10.1016/j.ymgme.2012.09.022. PMC 3523122. PMID 23059056.

External links

This article is issued from Wikipedia - version of the Wednesday, January 06, 2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.