The BioCyc web portal from SRI International contains integrated genome and metabolic-pathway databases for more than 20,000 sequenced organisms including 68 curated databases. BioCyc databases integrate a diverse range of data and provide a high level of curation. BioCyc includes an extensive suite of bioinformatics tools including a genome browser, metabolic network browser, metabolomics data analysis, transcriptomics data analysis, and metabolic route search.
BioCyc Pathway/Genome Databases (PGDBs) describe the genome of an organism, as well as its biochemical pathways; for a fraction of organisms regulatory networks are also present. New releases occur three times per year. BioCyc contains databases for humans, model eukaryotes, and for many bacteria.
For a full description of BioCyc bioinformatics tools please refer to the BioCyc Data Sheet or view the BioCyc overview video.
BioCyc contains 20,000 Pathway/Genome Databases (PGDBs) including 68 curated databases.
PGDB generation combines an annotated genome with computationally inferred metabolic pathways, protein complexes, orthologs, Pfam domains, and operons (for bacteria). Additional information imported from other databases can include:
Tier 3 (uncurated) eukaryotic databases in BioCyc include Rattus norvegicus, Mus musculus, Caenorhabditis elegans, Drosophila melanogaster, and Arabidopsis thaliana.
Click for a full list of the Tier 1 and Tier 2 curated databases, which include the following.
BioCyc provides a powerful and comprehensive set of features for querying, visualization, and analysis of BioCyc data and user data. Tools include sequence retrieval, BLAST search, sequence pattern search, multiple-sequence alignment, and the following.
The genome browser depicts a region of the E. coli K-12 chromosome; gene colors indicate operon organization. Promoters and terminators are depicted when known. Pseudogenes are marked with X's.
Aligns genome regions from user-selected organisms at orthologous genes.
The Regulatory Overview depicts the transcriptional regulatory network in a PGDB; red arrows show user-requested regulatory relationships. The inner two rings are populated by transcription factors and sigma factors; the outer ring contains other, non-regulatory genes.
Pathway informatics tools include the following.
Tools for exploring transcriptomics data include enrichment analysis of gene sets for pathways, Gene Ontology biological processes, and regulators, and the following unique tools.
The BioCyc Cellular Omics Viewer enables the user to paint transcriptomics datasets onto zoomable organism-specific metabolic network diagrams. Scientists can interpret high-throughput datasets in a pathway context, including animation of time-course or comparative datasets. Reaction lines can be colored with gene expression, proteomics, or reaction flux data. Omics pop-ups graph omics data values using bar graphs, heat maps, or X-Y plots.
Add metabolomics data to a diagram by additionally painting metabolomics data onto metabolites.
The BioCyc Omics Dashboard enables the user to rapidly survey how all cellular systems are responding to a given stimulus. Scientists can quickly view the response of genes within one or more specific systems of interest, and can gauge the relative activity levels of different cellular systems. The Dashboard also enables comparison of expression levels of a cellular system with those of its known regulators. The Dashboard consists of a set of panels, each representing a system of cellular function. Each panel shows a graph depicting omics data for each of a set of subsystems. Multiple timepoints or experimental conditions are plotted as separate data series within the graphs. Clicking on a panel drills down into its component subsystems.
Tools for exploring metabolomics data include enrichment analysis of metabolite sets for pathways, search by chemical formula and monoisotopic mass, computation of metabolite-covering sets, and the following unique tools.
The BioCyc Cellular Omics Viewer enables the user to paint metabolomics datasets onto zoomable organism-specific metabolic network diagrams. Scientists can interpret high-throughput datasets in a pathway context, including animation of time-course or comparative datasets. Metabolite nodes in the diagram can be colored with metabolomics measurements. Omics pop-ups graph data values using bar graphs, heat maps, or X-Y plots.
Add transcriptomics data to the diagram by additionally painting transcriptomics data onto reaction lines.
The BioCyc Omics Dashboard enables the user to rapidly survey how all cellular systems are responding to a given stimulus. Scientists can quickly view the metabolite abundances within one or more specific systems of interest, and to gauge the relative activity levels of different cellular systems. The Dashboard consists of a set of panels, each representing a system of cellular function. Each panel shows a graph depicting omics data for each of a set of subsystems. Multiple timepoints or experimental conditions are plotted as separate data series within the graphs. Clicking on a panel drills down into its component subsystems.
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