ArticleJournal of industrial microbiology & biotechnology2014
Protein-protein interaction network of the marine microalga Tetraselmis subcordiformis: prediction and application for starch metabolism analysis.
Article in Journal of industrial microbiology & biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- Article
- Review
- Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction.Current genomics · 2020Review
- Comparative analysis of differential proteome-wide protein-protein interaction network ofBiochemistry and biophysics reports · 2019Article
- Nutritional Potential and Toxicological Evaluation ofMolecules (Basel, Switzerland) · 2019Article
- Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.Proteomes · 2018Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Under stressful conditions, the non-model marine microalga Tetraselmis subcordiformis can accumulate a substantial amount of starch, making it a potential feedstock for the production of fuel ethanol. Investigating the interactions of the enzymes and the regulatory factors involved in starch metabolism will provide potential genetic manipulation targets for optimising the starch productivity of T. subcordiformis. For this reason, the proteome of T. subcordiformis was utilised to predict the first protein-protein interaction (PPI) network for this marine alga based on orthologous interactions, mainly from the general PPI repositories. Different methods were introduced to evaluate the credibility of the predicted interactome, including the confidence value of each PPI pair and Pfam-based and subcellular location-based enrichment analysis. Functional subnetworks analysis suggested that the two enzymes involved in starch metabolism, starch phosphorylase and trehalose-phosphate synthase may be the potential ideal genetic engineering targets.
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