ArticleThe Plant cell2012
The MORPH algorithm: ranking candidate genes for membership in Arabidopsis and tomato pathways.
Article in The Plant cell, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 24 citations in OpenAlex.
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- Arabidopsis as a model for translational research.The Plant cell · 2025Review
- OsMGD1-Mediated Membrane Lipid Remodeling Improves Salt Tolerance in Rice.Plants (Basel, Switzerland) · 2024Article
- GeneFishing to reconstruct context specific portraits of biological processes.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Changing Form and Function through Carotenoids and Synthetic Biology.Plant physiology · 2019Article
- MorphDB: Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants.Frontiers in plant science · 2018Article
- Missing gene identification using functional coherence scores.Scientific reports · 2016Article
- FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants.Plant physiology · 2016Article
- Learning from Co-expression Networks: Possibilities and Challenges.Frontiers in plant science · 2016Review
- Revealing shared and distinct gene network organization in Arabidopsis immune responses by integrative analysis.Plant physiology · 2015Article
- CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool.Frontiers in plant science · 2015Article
- Evaluation and integration of functional annotation pipelines for newly sequenced organisms: the potato genome as a test case.BMC plant biology · 2014Article
- Constructing module maps for integrated analysis of heterogeneous biological networks.Nucleic acids research · 2014Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Closing gaps in our current knowledge about biological pathways is a fundamental challenge. The development of novel computational methods along with high-throughput experimental data carries the promise to help in the challenge. We present an algorithm called MORPH (for module-guided ranking of candidate pathway genes) for revealing unknown genes in biological pathways. The method receives as input a set of known genes from the target pathway, a collection of expression profiles, and interaction and metabolic networks. Using machine learning techniques, MORPH selects the best combination of data and analysis method and outputs a ranking of candidate genes predicted to belong to the target pathway. We tested MORPH on 230 known pathways in Arabidopsis thaliana and 93 known pathways in tomato (Solanum lycopersicum) and obtained high-quality cross-validation results. In the photosynthesis light reactions, homogalacturonan biosynthesis, and chlorophyll biosynthetic pathways of Arabidopsis, genes ranked highly by MORPH were recently verified to be associated with these pathways. MORPH candidates ranked for the carotenoid pathway from Arabidopsis and tomato are derived from pathways that compete for common precursors or from pathways that are coregulated with or regulate the carotenoid biosynthetic pathway.
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Registered trials
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