International Journal of Computational Bioinformatics and In Silico Modeling
ABSTRACT: Cadmium is one of the main heavy metal pollutants with accumulation properties in both soil and water and the bio-accumulation approach in living organisms exert deleterious effects on the environment. Plants have numerous molecules for cadmium resistance. For investigation main classes of molecules in cadmium toxicity base previous research, numerous article about cadmium were processed by the text mining software and the cadmium interaction network was constructed based on gene induction, transporter and molecule synthesis. The primary data were more analyzed based on description of the function and topology analysis of network. The results showed, cadmium interacted with more than 40 different molecules as enzymes, transcription factors, signaling molecules, transporters and small molecules that were classified based on function in six groups as glutathione related enzymes, oxido/reductase related molecules, heavy metal concentration management (cadmium scavenger and transporters), signaling and phytohormone molecules, protein refinery and breaking (proteinases and heat shock protein) and first/ secondary metabolite (sugar, amino acid and phytoalexin). Topology and navigation network analysis showed glutathione, metallothionein, MAPK (mitogen activating protein kinase), ROS (reactive oxygen species), MMP (matrix metalloproteinases) and many heavy metals (with unknown relation) are critical hubs in cadmium network. Then, ion concentration homeostasis, signaling molecules and redox potential have the highest ranking between all categories. In this case, cadmium has a close relationship with other heavy metals in mechanisms or network similarity in the cell. This result can produce observation about cadmium mechanisms and it’s critical nods and hotspots to increase it’s resistance and phytoremediation in the future.
KeyWords: Cadmium, Critical Point, Mechanisms, Text mining.
How to cite: Seyed Ahmad Shafiei et al. In Silico Review Analysis of Critical Points in Cadmium Mechanisms. Int J Comput Bioinfo In Silico Model. 5(4) 2016: 819-827
ABSTRACT: Abscisic acid (ABA) is an endogenous growth inhibitor and regulator that controls adaptive response in plants to stress conditions such as drought and salinity. Recent advancements in ABA signaling pathway have significantly improved our understanding on molecular basis of ABA response in plants. However, genome-wide comparative analysis of ABA signaling components, PYL (ABA receptor), PP2C (type 2C protein phosphatases) and SnRK2 (protein kinases) in legume species has not been clearly demonstrated. The objectives of the study were to identify ABA signaling components from legume species, Glycine max, Medicago truncatula, and Phaseolus vulgaris based on the variability of functional motifs and to determine their evolutionary patterns using phylogenetic study. Genome-wide analysis indicates that ABA signaling protein family members (60% PYL, 51% PP2C, and 56% SnRK2) increased in G. max as compared to those in M. truncatula and P. vulgaris which ranged from 14-26 % for PYL, 22-27% PP2C, and 13-31% SnRK2. Most PYL, SnRK2, and PP2C proteins were hydrophilic and biochemically stable. Some PYL (14.3%) and PP2C (22.8%) components were localized in chloroplast, mitochondria, or secretory vessels, but all of SnRK2s were in subcellular locations, including cytosol and nucleus. Among three ABA gene families, SnRK2 and PYL/PYR had found with 97% and 98% phase 0 introns, respectively, whereas PP2C had observed less with 61% phase 0 intron. This shows that variability exists in the members of PP2C, but relatively conserved pattern is present among SnRK2 and PYL/PYR. Based on our study, we believe that a regulatory gene PP2C action could be inhibited by the ABA receptor complex such as PYL, resulting in the phosphorylation of SnRK2 kinases. SnRK2-mediated phosphorylation of transcription factors subsequently promote ABA-responsive gene expression. Phylogenetic analysis of ABA signaling components among three legumes designates that PP2C had developed more sophisticated stress tolerance system through genomic evolution including the expansion of gene families implicated in ABA signaling than PYL and SnRK2.
KeyWords: Abscisic acid, Drought, PYL, PP2C, SnRK2, Legume.
How to cite: Madhuri Inupakutika et al. Genome-wide comparative analysis of genes encoding core components of ABA signaling pathway in legume family. Int J Comput Bioinfo In Silico Model. 5(4) 2016: 828-843
ABSTRACT: The stereotype logistic (SL) model is one among ordinal logistic regression models which is used for ordinal response variable when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not have the procedure developed to directly estimate the model. This article is an extension of previous research work of the comparison of logistic regression models, on analyzing the predictors of health of adolescences, having multinomial response in Jimma Zone South West Ethiopia. The purpose of this article was to compare the results of fitting the PO model and the SL model. The proportional odds model was an improved fit as compared to the stereotype logistic regression model for any combination of variables in the dataset. Being literate and using protected water had a positive contribution for a better health of adolescents and boys were less likely than girls to report a deteriorate state of health.
KeyWords: Polytomous logistic (PL) model, Stereotype logistic (SL) model, Proportional odds (PO) model, Akakie Information Criteria (AIC)..
How to cite: Girma Tefera. Stereotype logistic regression model for ordinal outcome variable. Int J Comput Bioinfo In Silico Model. 5(4) 2016: 844-848