BioCyc database collection

From Wikipedia, the free encyclopedia
Jump to: navigation, search

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, 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][2] The other important Tier 1 database is HumanCyc which contains around 250 metabolic pathways found in humans.[3] The remaining five databases include, EcoCyc (E. coli),[4] 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:[5][6][7]

  • Development of Organism specific databases
  • Scientific Visualization, web publishing, and dissemination of organism-specific databases
  • Development of metabolic-flux models
  • Visual analysis of omics datasets
  • Computational inferences
  • Comparative analyses of organism-specific databases
  • Analysis of biological networks

The Pathway Tools software had four main components:[8]

  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 is a genome scale metabolic network model for a compartmentalized algae cell developed by Gomes de Oliveira Dal’Molin et al.[9] 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.


The study by Shimul Chowdhury et al.[10] 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.


  1. ^ a b Caspi R, Altman T, Dreher K, Fulcher CA, Subhraveti P, Keseler IM, Kothari A, Krummenacker M, Latendresse M, Mueller LA,Ong Q, Paley S, Pujar A, Shearer AG, Travers M, Weerasinghe D, Zhang P,Karp PD. "The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases," Nucleic Acids Research 40:D742-53 2011
  2. ^ Karp, PD, and Caspi, R. "A survey of metabolic databases emphasizing the MetaCyc family" Archives of Toxicology 85:1015-33 2011
  3. ^ P. Romero, J. Wagg, M.L. Green, D. Kaiser, M. Krummenacker, and P.D. Karp "Computational prediction of human metabolic pathways from the complete human genome", Genome Biology 6:R2 R2.1-17 2004
  4. ^ 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., and Karp, P.D. "EcoCyc: a comprehensive database of Escherichia coli biology" Nucleic Acids Research 39:D583-590 2011
  5. ^ P.D. Karp, S.M. Paley, M. Krummenacker, et al. "Pathway Tools version 13.0: Integrated Software for Pathway/Genome Informatics and Systems Biology" Briefings in Bioinformatics 11:40-79 2010
  6. ^ Peter D. Karp, Suzanne Paley and Pedro Romero. "The pathway tools software" Bioinformatics Vol. 18 Suppl. 1 2002
  7. ^ P. Karp and S. Paley. "Integrated access to metabolic and genomic data" Journal of Computational Biology, 3(1):191-212 1996
  8. ^ M. Krummenacker, S. Paley, L. Mueller, T. Yan, and P.D. Karp. "Querying and Computing with BioCyc Databases" Bioinformatics 21:3454-5 2005
  9. ^ Cristiana Gomes de Oliveira Dal’Molin, Lake-Ee Quek, Robin W Palfreyman, Lars K Nielsen. "AlgaGEM – a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome" BMC Genomics 12(Suppl 4):S5 2011
  10. ^ Shimul Chowdhury, Charlotte A. Hobbs, Stewart L. MacLeod, Mario A. Cleves, Stepan Melnyk, S. Jill James, Ping Hu, and Stephen W. Erickson. "Associations between maternal genotypes and metabolites implicated in congenital heart defects" Molecular Genetics and Metabolism 107(3): 596–604 2012

External links[edit]