# The MetaCyc & BioCyc Pathway/Genome Databases

> **NIH NIH R01** · SRI INTERNATIONAL · 2020 · $1,005,713

## Abstract

7 Project Summary
The project objective is to develop a bioinformatics foundation for deciphering and modeling the metabolic networks of organisms with fully sequenced genomes, in support of drug discovery, metabolic engineering, systems
biology, and basic science. Our approach is based on a gold-standard metabolic DB, MetaCyc, which is curated by
Ph.D.-level biologists, from the experimental literature. A second objective is to further develop BioCyc, an evolving
collection of Pathway/Genome Databases for 14,560 sequenced prokaryotic genomes. BioCyc is a premier prokaryotic genome web portal because of its comprehensive coverage of prokaryotic genomes; its integration of multiple
information sources; its extensive and user-friendly bioinformatics search, visualization, and analysis tools; and its
distribution of data via multiple access channels.
 We have four specific aims. (1) To expand MetaCyc, a highly curated multi-organism database of metabolic
pathways and enzymes that serves as an encyclopedic reference of metabolic information. MetaCyc can be used
to predict the metabolic pathway complement of an organism from its sequenced genome, and is a foundation
for metabolic modeling. Information about experimentally determined metabolic pathways and enzymes will
be curated into MetaCyc from the biomedical literature, with a focus on prokaryotic pathways. (2) To computationally generate extended versions of BioCyc, a collection of organism-specific Pathway/Genome Databases for
completely sequenced prokaryotes and model organisms that includes predicted metabolic pathways, predicted
metabolic pathway hole fillers, and predicted operons. We will curate the human metabolic database within BioCyc, as well as databases for important organisms in the human microbiome. (3) To enhance the PTools software
that supports the querying, visualization, and analysis of MetaCyc and BioCyc data to include a more accurate
metabolic pathway prediction algorithm, a new visualization of genome-scale metabolic networks, and a new set
of comparative operations. We will also enhance the scalability of the software, and modernize its graphics. (4) To
make MetaCyc and BioCyc available to the scientific community through a web portal and via downloadable data
files and software.

## Key facts

- **NIH application ID:** 10021432
- **Project number:** 5R01GM080746-14
- **Recipient organization:** SRI INTERNATIONAL
- **Principal Investigator:** Ron Caspi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,005,713
- **Award type:** 5
- **Project period:** 2007-06-19 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10021432

## Citation

> US National Institutes of Health, RePORTER application 10021432, The MetaCyc & BioCyc Pathway/Genome Databases (5R01GM080746-14). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10021432. Licensed CC0.

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