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Computational plant models or 'virtual plants' are increasingly seen as a useful tool for comprehending complex relationships between gene function, plant physiology, plant development, and the resulting plant form.
AMAP (Botany and Computational Plant Architecture) is a joint research unit which associates CIRAD (UMR51), CNRS (UMR5120), INRA (UMR931), IRD (2M123), and Montpellier 2 University (UM27); http://amap.cirad.fr/.fr/
Computational plant growth modeling [ 3, 4] enables a deeper understanding and more accurate predictions for a wide range of plant physiological problems.
Specifically, in the studies of the key biological pathways responsive to bioitic or abotic stresses, probably the only way to capture the exact changes in plant growth rate (which may reflect how these pathways control photosynthesis activity or energy distribution) is to develop a precise and more efficient computational plant growth model.
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Although the use of this data is convenient due to the reduced computational requirements in plant optimization, it may result in a simplistic prediction of plant operations that does not reflect the real plant performance by neglecting the impact of short-term variability in solar irradiance and the variations in weather and available solar energy for different years.
He pioneered computational simulation in plant systems biology to analyze the photosynthetic metabolism of C3 plants, and his work revealed that metabolic pathways are synchronized and coordinated when under environmental perturbations (Luo et al., 2009).
We here present a novel computational method for plant QTL candidate gene prioritization.
Computational identification of plant miRNA-target is possible due the perfect or near-perfect match between miRNA/target in complementary sites [ 44].
Computational mapping and plant GO-slim annotation were performed using BLAST2GO PRO software (Conesa et al. 2005; Conesa and Gotz 2008) with default parameters for 25.574 CDS of the C. canephora reference.
A recent computational study of plant Hb folding showed that one of the folding modules of rice 3/3 NsHb overlaps the 2/2 fold of Mycobacterium tuberculosis HbO (class 2) suggesting that it is an ancient structural feature of globins [ 97].
Therefore, we adopted one of these computational methods named Plant-mPloc (http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/; Chou and Shen, 2010) to predict the subcellular localization of each protein in our interactome.
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