The BioCyc web portal from SRI International contains integrated genome and metabolic-pathway databases for more than 20,000 sequenced organisms, including 60 curated databases. BioCyc encyclopedias are unique in integrating a diverse range of data and providing a high level of curation. BioCyc Pathway/Genome Databases (PGDBs) are organized into tiers according to the amount of manual updating they have received:
For a list of available databases, click here.
PGDBs describe the genome of an organism, as well as its biochemical pathways; for a small fraction of organisms regulatory networks are also present. New releases occur three times per year, often including new databases as well as updated data. Two members of the BioCyc collection, the EcoCyc and MetaCyc databases, are derived from more than three decades of literature-based curation of genome and pathway data. Other members of the BioCyc database collection include HumanCyc and BsubCyc.
The Pathway Tools software combine unparalleled breadth and user friendliness and include a unique set of visualization tools to speed comprehension of extensive PGDB data. For a full list of analysis and visualization tools please refer to the Pathway Tools Data Sheet or view the BioCyc overview video.
BioCyc has 20,000 databases including 60 plus curated databases. For a listing of databases, click here.
Each BioCyc PGDB describes the genome of an organism, as well as its biochemical pathways and, for a small fraction of organisms, its regulatory network.
All PGDBs include the genome, predicted metabolic pathways, and predicted pathway hole ﬁllers (genes coding for missing enzymes in metabolic pathways). Bacterial PGDBs include predicted operons. The exact types of data present in different databases will vary. Many databases also include:
For an overview of BioCyc, visit http://bioinformatics.ai.sri.com/ptools/webinars/2020webinars/2020INTROBIOCYC01.mp4
A sample of the most popular BioCyc informatics tools:
BioCyc curators summarize and synthesize information from thousands of publications, saving scientists time in literature research, and integrating data for large-scale computational analyses.
BioCyc provides a powerful and comprehensive set of features for querying, visualization, and analysis of BioCyc data and user data. Some of our more popular tools are listed here.
Genome browser depiction of a region of the E. coli chromosome.
Gene colors indicate operon organization. Promoters and terminators are depicted when known. Pseudogenes are marked with X’s.
Aligns genome regions around orthologous genes.
The Regulatory Overview depicts the transcriptional regulatory network in a PGDB. Here, the E. coli regulatory network is highlighted to show genes that regulate the gntR gene (blue lines), and the genes that are regulated by gntR (purple lines). The inner two rings are populated by transcription factors and sigma factors; the outer ring contains other genes.
The BioCyc Cellular Omics Viewer enables the user to paint omics datasets onto 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; compound nodes can be colored with metabolomics data. Multi-omics data can be analyzed by coloring data onto reactions and metabolites simultaneously. Omics pop-ups graph omics data values using bar graphs, heat maps, or X-Y plots.
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.
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