96 research outputs found

    INDIAN Bank Base Rate:An Overview

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    The paper deals about the issues arising out of implementing base rate for Indian banks. With effect from July 1st, 2010, all banks are supposed to lend at base rate or minimum level of interest rate to customers. The net impact of this for retail customer will not be much as cost of funds for banks are not going to change much and cost of funds determine base rate. Big corporates will be biggest losers as they had advantage of getting loans at sub-base rates. Biggest gainers will be small and medium firms who were getting raw deal earlier from banks. Banks may lose market share in short term but there is going to be greater transparency and trickling down of policies made by RBI across banks due to base-rate system. Game theory has been applied to explain the base rate transition scenario in the paper.Base Rate, Private Bank, BPLR, Game Theory, Net Income Margin(NIM)

    INDIAN Bank Base Rate:An Overview

    Get PDF
    The paper deals about the issues arising out of implementing base rate for Indian banks. With effect from July 1st, 2010, all banks are supposed to lend at base rate or minimum level of interest rate to customers. The net impact of this for retail customer will not be much as cost of funds for banks are not going to change much and cost of funds determine base rate. Big corporates will be biggest losers as they had advantage of getting loans at sub-base rates. Biggest gainers will be small and medium firms who were getting raw deal earlier from banks. Banks may lose market share in short term but there is going to be greater transparency and trickling down of policies made by RBI across banks due to base-rate system. Game theory has been applied to explain the base rate transition scenario in the paper

    Capital Markets- Utility for Micro-finance

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    The Paper deals with the situation for efficient use of Capital Markets for financing Micro-finance Institutions. In order to sustain the growth in the microfinance industry, it is necessary to shifting the loan financing for MFIs from traditional lenders to capital markets. This can primarily be achieved through securitization and CDOs. Both have different advantages to offer which can be tapped separately and also customized on a case‐by‐case basis. Apart from the domestic commercial investors, foreign market debt can also be tapped for the funding needs of the MFIs but for that to function properly, the FXR has to be managed which can be effectively done through the creation of a “global local currency fund” which basically works on the principle of diversification

    A web server for predicting inhibitors against bacterial target GlmU protein

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    Background: The emergence of drug resistant tuberculosis poses a serious concern globally and researchers are in rigorous search for new drugs to fight against these dreadful bacteria. Recently, the bacterial GlmU protein, involved in peptidoglycan, lipopolysaccharide and techoic acid synthesis, has been identified as an important drug target. A unique C-terminal disordered tail, essential for survival and the absence of gene in host makes GlmU a suitable target for inhibitor design. Results: This study describes the models developed for predicting inhibitory activity (IC50) of chemical compounds against GlmU protein using QSAR and docking techniques. These models were trained on 84 diverse compounds (GlmU inhibitors) taken from PubChem BioAssay (AID 1376). These inhibitors were docked in the active site of the C-terminal domain of GlmU protein (2OI6) using the AutoDock. A QSAR model was developed using docking energies as descriptors and achieved maximum correlation of 0.35/0.12 (r/r2) between actual and predicted pIC50. Secondly, QSAR models were developed using molecular descriptors calculated using various software packages and achieved maximum correlation of 0.77/0.60 (r/r2). Finally, hybrid models were developed using various types of descriptors and achieved high correlation of 0.83/0.70 (r/r2) between predicted and actual pIC50. It was observed that some molecular descriptors used in this study had high correlation with pIC50. We screened chemical libraries using models developed in this study and predicted 40 potential GlmU inhibitors. These inhibitors could be used to develop drugs against Mycobacterium tuberculosis. Conclusion: These results demonstrate that docking energies can be used as descriptors for developing QSAR models. The current work suggests that docking energies based descriptors could be used along with commonly used molecular descriptors for predicting inhibitory activity (IC50) of molecules against GlmU. Based on this study an open source platform, http://crdd.osdd.net/raghava/gdoq, has been developed for predicting inhibitors GlmU

    Minimization of Harmonics Noise Using Wavelet Transformation Technology

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    The field programmable gate array technology can design high performance system at low cost for wavelet analysis. Wavelet transform has gained the reputation of being a very effective signal analysis tool for much practical application. Implementation of transform needs the meeting of real-time processing for most application. The objectives of this paper are to compare the Haar and Daubeches technology and to calculate the bit error rate (BER) between the input audio signal and reconstructed output signal. It is seen that the BER using Daubechies wavelet technology is less than Haar wavelet. The design procedure is explained using the stat of art electronic design. Automation tools for system design on FPGA, simulation, synthesis and implementation on the FPGA technology has been carried out. The power hovmoller, cross wavelet spectra and coherence are described. A Practical step-up-step guide to wavelet analysis is given with examples taken from time series. The guide includes a comparison to the windowed Fourier transform. New statistical significance test for wavelet power spectra are developed by deriving theoretical wavelet spectra for white and red noise. Empirical formula is given for the effect of smoothing on significance levels and filtering. The notion of orthogonal no separable trivet wavelet packets, which is the generation of orthogonal university wavelet packets is introduced. A de-noising method based on wavelet packet shrinkage is developed. The principle of wavelet packet shrinkage for de-noising and the section of thresholds and threshold function are analyzed

    Recognition and analysis of protein-coding genes in severe acute respiratory syndrome associated coronavirus

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    Motivation: The recent outbreak of severe acute respiratory syndrome (SARS) caused by SARS coronavirus (SARS-CoV) has necessitated an in-depth molecular understanding of the virus to identify new drug targets. The availability of complete genome sequence of several strains of SARS virus provides the possibility of identification of protein-coding genes and defining their functions. Computational approach to identify protein-coding genes and their putative functions will help in designing experimental protocols. Results: In this paper, a novel analysis of SARS genome using gene prediction method GeneDecipher developed in our laboratory has been presented. Each of the 18 newly sequenced SARS-CoV genomes has been analyzed using GeneDecipher. In addition to polyprotein 1ab*, polyprotein 1a and the four genes coding for major structural proteins spike (S), small envelope (E), membrane (M) and nucleocapsid (N), six to eight additional proteins have been predicted depending upon the strain analyzed. Their lengths range between 61 and 274 amino acids. Our method also suggests that polyprotein 1ab, polyprotein 1a, S, M and N are proteins of viral origin and others are of prokaryotic. Putative functions of all predicted protein-coding genes have been suggested using conserved peptides present in their open reading frames

    In-silico structural modelling of cytochrome complex proteins of white turmeric (Curcuma zedoaria)

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    Curcuma zedoaria (Christm.) Roscoe (white turmeric) is a perennial herbaceous plant of family Zingiberaceae and mainly found in the wild areas of tropical and subtropical regions worldwide. The cytochrome proteins in plants play important roles in promoting their growth and development, as well as protecting them from stresses and diseases. Cytochrome proteins like psbF, psbE, petB, petD, petN, petG, and ccsA play important roles in degradation of mis-folded proteins, ATP formation, cyclic electron flow and biogenesis of c-type cytochrome of C. zedoaria. However, due to lack of structural availability of these C. zedoaria cytochrome proteins in structural databases, the physiochemical parameters of sequences were estimated using Expasy ProtParam web tool. Self-Optimized Prediction Method with Alignment (SOPMA) server and MODELLER version 9.23 were used for modelling along with Qualitative Model Energy Analysis (QMEAN) and Protein Structure Analysis (ProSA) servers were implemented for validating the secondary and tertiary structures of these proteins. The obtained QMEAN4 values of the modelled cytochrome proteins were -2.04, -1.20, -3.01, -1.57, -2.11, -1.74 and -12.87. The Z-scores obtained from ProSA server were 0.5, -0.83, -1.5, -0.58, -0.02, 0.14 and -3.73. All seven modelled structures have been submitted to protein model database (PMDB). The derived results will be helpful in further investigations towards determining the crystal structure of the hypothetical proteins, structural motifs, physiochemical properties, and also protein-protein interaction studies of various cytochrome proteins

    Transcriptome and venom proteome of the box jellyfish Chironex fleckeri

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    Background: The box jellyfish, Chironex fleckeri, is the largest and most dangerous cubozoan jellyfish to humans. It produces potent and rapid-acting venom and its sting causes severe localized and systemic effects that are potentially life-threatening. In this study, a combined transcriptomic and proteomic approach was used to identify C. fleckeri proteins that elicit toxic effects in envenoming. Results: More than 40,000,000 Illumina reads were used to de novo assemble ~34,000 contiguous cDNA sequences and ~20,000 proteins were predicted based on homology searches, protein motifs, gene ontology and biological pathway mapping. More than 170 potential toxin proteins were identified from the transcriptome on the basis of homology to known toxins in publicly available sequence databases. MS/MS analysis of C. fleckeri venom identified over 250 proteins, including a subset of the toxins predicted from analysis of the transcriptome. Potential toxins identified using MS/MS included metalloproteinases, an alpha-macroglobulin domain containing protein, two CRISP proteins and a turripeptide-like protease inhibitor. Nine novel examples of a taxonomically restricted family of potent cnidarian pore-forming toxins were also identified. Members of this toxin family are potently haemolytic and cause pain, inflammation, dermonecrosis, cardiovascular collapse and death in experimental animals, suggesting that these toxins are responsible for many of the symptoms of C. fleckeri envenomation. Conclusions: This study provides the first overview of a box jellyfish transcriptome which, coupled with venom proteomics data, enhances our current understanding of box jellyfish venom composition and the molecular structure and function of cnidarian toxins. The generated data represent a useful resource to guide future comparative studies, novel protein/peptide discovery and the development of more effective treatments for jellyfish stings in humans. (Length: 300)
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