The effects of electronic banking development on Iranian banks’ profitability (2005-2010)

In this research, it has been attempted to answer what effects electronic banking development has had on Iranian banks’ profitability.  This research is based on analyzing Iranian Banks activities in Electronic Banking development during several years. Regarding the fact that the most serious actions in the field of e-banking in Iran are installing ATMs, various e-banking services (by telephone, internet, and cell phone), issuing different e-cards (debit card, credit card, purchase/gift card, and e-money), and installing sales terminals and branch terminals, the issue which was pointed out in the present study  was the effect of each of the mentioned parameters and equipment on Iranian banks’ profitability. The model used in this research is based on the structure-behavior-action hypothesis in which the Return on Assets (ROA) is considered as the dependant variables and the number of cards to ATMs ratio, facilities to the number of branches ratio, Herfindahl- Hirschman Index (HHI), inflammation rate, and both the virtual variables including business and government aspects of banks or their being private and specialized were defined as independent variables. The model estimation was performed through 17 banks data during the years 2005 to 2010 and based on the panel data method. The research results show that number of cards to ATM ratio increase has a positive and meaningful effect on banks profitability. Based on this, it can be concluded that Electronic Banking development has a positive and considerable effect on Iranian banks profitability. Also, the number of loans, and given facilities have positive and meaningful effects on Iranian banks profitability

The effects of electronic banking development on Iranian banks’ profitability (2005-2010)

In this research, it has been attempted to answer what effects electronic banking development has had on Iranian banks’ profitability.  This research is based on analyzing Iranian Banks activities in Electronic Banking development during several years. Regarding the fact that the most serious actions in the field of e-banking in Iran are installing ATMs, various e-banking services (by telephone, internet, and cell phone), issuing different e-cards (debit card, credit card, purchase/gift card, and e-money), and installing sales terminals and branch terminals, the issue which was pointed out in the present study  was the effect of each of the mentioned parameters and equipment on Iranian banks’ profitability. The model used in this research is based on the structure-behavior-action hypothesis in which the Return on Assets (ROA) is considered as the dependant variables and the number of cards to ATMs ratio, facilities to the number of branches ratio, Herfindahl- Hirschman Index (HHI), inflammation rate, and both the virtual variables including business and government aspects of banks or their being private and specialized were defined as independent variables. The model estimation was performed through 17 banks data during the years 2005 to 2010 and based on the panel data method. The research results show that number of cards to ATM ratio increase has a positive and meaningful effect on banks profitability. Based on this, it can be concluded that Electronic Banking development has a positive and considerable effect on Iranian banks profitability. Also, the number of loans, and given facilities have positive and meaningful effects on Iranian banks profitability

Comparative shotgun proteomic analysis of Clostridium acetobutylicum from butanol fermentation using glucose and xylose

<p>Abstract</p> <p>Background</p> <p>Butanol is a second generation biofuel produced by <it>Clostridium acetobutylicum </it>through acetone-butanol-ethanol (ABE) fermentation process. Shotgun proteomics provides a direct approach to study the whole proteome of an organism in depth. This paper focuses on shotgun proteomic profiling of <it>C. acetobutylicum </it>from ABE fermentation using glucose and xylose to understand the functional mechanisms of <it>C. acetobutylicum </it>proteins involved in butanol production.</p> <p>Results</p> <p>We identified 894 different proteins in <it>C. acetobutylicum </it>from ABE fermentation process by two dimensional - liquid chromatography - tandem mass spectrometry (2D-LC-MS/MS) method. This includes 717 proteins from glucose and 826 proteins from the xylose substrate. A total of 649 proteins were found to be common and 22 significantly differentially expressed proteins were identified between glucose and xylose substrates.</p> <p>Conclusion</p> <p>Our results demonstrate that flagellar proteins are highly up-regulated with glucose compared to xylose substrate during ABE fermentation. Chemotactic activity was also found to be lost with the xylose substrate due to the absence of CheW and CheV proteins. This is the first report on the shotgun proteomic analysis of <it>C. acetobutylicum </it>ATCC 824 in ABE fermentation between glucose and xylose substrate from a single time data point and the number of proteins identified here is more than any other study performed on this organism up to this report.</p

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant’s sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes use of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. The resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance

Determination of Peptide and Protein Ion Charge States by Fourier Transformation of Isotope-Resolved Mass Spectra

We report an automated method for determining charge states from high-resolution mass spectra. Fourier transforms of isotope packets from high-resolution mass spectra are compared to Fourier transforms of modeled isotopic peak packets for a range of charge states. The charge state for the experimental ion packet is determined by the model isotope packet that yields the best match in the comparison of the Fourier transforms. This strategy is demonstrated for determining peptide ion charge states from “zoom scan” data from a linear quadrupole ion trap mass spectrometer, enabling the subsequent automated identification of singly- through quadruply-charged peptide ions, while reducing the numbers of conflicting identifications from ambiguous charge state assignments. We also apply this technique to determine the charges of intact protein ions from LC-FTICR data, demonstrating that it is more sensitive under these experimental conditions than two existing algorithms. The strategy outlined in this paper should be generally applicable to mass spectra obtained from any instrument capable of isotopic resolution

Wavelet-Based Genomic Signal Processing for Centromere Identification and Hypothesis Generation

Various ‘omics data types have been generated for Populus trichocarpa, each providing a layer of information which can be represented as a density signal across a chromosome. We make use of genome sequence data, variants data across a population as well as methylation data across 10 different tissues, combined with wavelet-based signal processing to perform a comprehensive analysis of the signature of the centromere in these different data signals, and successfully identify putative centromeric regions in P. trichocarpa from these signals. Furthermore, using SNP (single nucleotide polymorphism) correlations across a natural population of P. trichocarpa, we find evidence for the co-evolution of the centromeric histone CENH3 with the sequence of the newly identified centromeric regions, and identify a new CENH3 candidate in P. trichocarpa

Finding New Cell Wall Regulatory Genes in Populus trichocarpa Using Multiple Lines of Evidence.

Understanding the regulatory network controlling cell wall biosynthesis is of great interest in Populus trichocarpa, both because of its status as a model woody perennial and its importance for lignocellulosic products. We searched for genes with putatively unknown roles in regulating cell wall biosynthesis using an extended network-based Lines of Evidence (LOE) pipeline to combine multiple omics data sets in P. trichocarpa, including gene coexpression, gene comethylation, population level pairwise SNP correlations, and two distinct SNP-metabolite Genome Wide Association Study (GWAS) layers. By incorporating validation, ranking, and filtering approaches we produced a list of nine high priority gene candidates for involvement in the regulation of cell wall biosynthesis. We subsequently performed a detailed investigation of candidate gene GROWTH-REGULATING FACTOR 9 (PtGRF9). To investigate the role of PtGRF9 in regulating cell wall biosynthesis, we assessed the genome-wide connections of PtGRF9 and a paralog across data layers with functional enrichment analyses, predictive transcription factor binding site analysis, and an independent comparison to eQTN data. Our findings indicate that PtGRF9 likely affects the cell wall by directly repressing genes involved in cell wall biosynthesis, such as PtCCoAOMT and PtMYB.41, and indirectly by regulating homeobox genes. Furthermore, evidence suggests that PtGRF9 paralogs may act as transcriptional co-regulators that direct the global energy usage of the plant. Using our extended pipeline, we show multiple lines of evidence implicating the involvement of these genes in cell wall regulatory functions and demonstrate the value of this method for prioritizing candidate genes for experimental validation