ArticleBioinformatics (Oxford, England)2018
GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation for Saccharomyces cerevisiae.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.Biomolecules · 2022Review
- Unveiling Forkhead-mediated regulation of yeast cell cycle and metabolic networks.Computational and structural biotechnology journal · 2022Article
- ChIP-exo analysis highlights Fkh1 and Fkh2 transcription factors as hubs that integrate multi-scale networks in budding yeast.Nucleic acids research · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Multi-scale modeling of biological systems requires integration of various information about genes and proteins that are connected together in networks. Spatial, temporal and functional information is available; however, it is still a challenge to retrieve and explore this knowledge in an integrated, quick and user-friendly manner. Results: We present GEMMER (GEnome-wide tool for Multi-scale Modeling data Extraction and Representation), a web-based data-integration tool that facilitates high quality visualization of physical, regulatory and genetic interactions between proteins/genes in Saccharomyces cerevisiae. GEMMER creates network visualizations that integrate information on function, temporal expression, localization and abundance from various existing databases. GEMMER supports modeling efforts by effortlessly gathering this information and providing convenient export options for images and their underlying data. Availability and implementation: GEMMER is freely available at http://gemmer.barberislab.com. Source code, written in Python, JavaScript library D3js, PHP and JSON, is freely available at https://github.com/barberislab/GEMMER. Supplementary information: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.