Pathway Studio Plant
Pathway Studio Plant's onboard knowledgebase is based on proprietary Elsevier technology that finds and extracts facts within reference materials, and converts those facts into structured relationship evidence. Maintained by Elsevier and updated regularly as part of the subscription agreement, the Pathway Studio knowledgebase and pathway collections encompassing Arabidopsis, Maize, and Rice, centralize key information, and summarize the state of current research for those model organisms, streamlining the investigative process.
- More than 133,000 molecular relationships
- Arabidopsis, Maize, and Rice proteins, genes, microRNA, enzyme classes, metabolites, plant diseases, and cellular processes
- Protein-protein and protein-cellular interactions including regulation, binding, and microRNA effects for Arabidopsis, Maize, and Rice
- Over 60,000 full text plant-specific articles from Elsevier and other key publishers
- 1250+ Arabidopsis, Maize, and Rice metabolic pathways and signaling pathways mapped to species-specific reference identifiers
- 400,000+ viewable sentences that allow researchers to verify independently the extracted relationships
Researchers can link out from Pathway Studio Plant through curated identifiers and ontologies to reference sources. Resultant analysis interactions include substantiating sentences from the literature, with links to the original articles. This information allows researchers to assess the applicability of each fact to their research, and use them to develop or verify a hypothesis.
Wizard-based analyses automate report generation for researcher-supplied experimental data and gene or protein lists, which saves time and provides results that cover four major investigative areas. Each summary Analysis Tool automatically runs metabolomics or expression data, or the imported gene list, across 1250+ metabolic and signaling pathways and finds the most similar pathways, cellular processes, and regulated genes in the dataset.
Four different summary reports are generated, providing researchers with the top biological changes in their experimental data to help them contextualize their findings and determine if additional analysis is needed. Both of these tools speed up daily analysis routines and provide the essential information needed to develop mechanistic-based hypotheses. Multiple advanced features provide greater flexibility for visualizing and exploring your research findings.
Designed to advance basic research as well as commercial applications, Pathway Studio Plant provides researchers with a platform to explore well-studied model plant mechanisms of action, interpret reference and experimental facts, extrapolate findings to plant organisms of interest, and build new metabolic and signaling pathways for trait association, yield maximization, and disease resistance research.
Use Pathway Studio Plant to:
- Search for relationship evidence on genes or proteins
- Filter results by species or trait
- Import experimental data, examine in knowledgebase context, and extrapolate findings to new organisms under study
- Build and visualize mechanistic models to explore causal interactions of disease traits, disease resistance, and crop yield.
Pathway Studio Plant is available either as an online(web) or enterprise-level solution.
Pathway Studio Web Plant helps plant scientists quickly assemble information, extrapolate meaning, and build pathways using well-studied model organisms: Arabidopsis, Maize, and Rice. More rapid than conventional approaches, this informatics solution helps plant biologists find regulatory genes for desired crop traits, and aids in novel discoveries that support essential crop production and protection research worldwide.
Pathway Studio Plant enterprise provides additional analytical support to extrapolate functionality of new plant organism proteins, and creates hundreds of metabolic and signaling pathways inferred from Arabidopsis, Maize, and Rice. In addition, customer proprietary data can be added to the core knowledgebase to increase specific information on key projects as well as to create new and unique organism-specific databases.