Ankita Agarwal

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Morphological analysis is an important part of Natural Language Processing. With this, the task of Machine translation becomes very easy. Morphological analyzer can be implemented effectively for the language which is rich in morphemes. Hindi is morphologically rich language. In this paper we focus on the design of a morphological analyzer for Hindi(More)
In recent years the DNA minor groove has attracted much attention for the development of anti-malarial agents. In view of this we have attempted to discover novel DNA minor groove binders through in-silico and in-vitro workflow. A rigorously validated pharmacophore model comprising of two positive ionizable (PI), one hydrophobic (HY) and one ring aromatic(More)
In view of the role of DHFR in design and development of antimicrobials, we have attempted to develop a rigorously validated structure-based pharmacophore model comprising of two hydrogen bond donors, one hydrogen bond acceptor and two hydrophobic features. The model was used as a query to screen the National Cancer Institute and Maybridge database leading(More)
Whenever an image is reconstructed, the quality of reconstructed image is calculated in terms of various quality parameters. MSE is considered as one of the most reliable and widely used quality parameter; however, we are using a new universal image quality index Q, which proves to be better than MSE. An improvisation of the same has also been proposed in(More)
Chemotherapy of protozoal disease has lagged far behind due to less commercial returns because of prevalence of this disease in developing countries. In view of this and with an aim to optimize the existing anti-giardial compounds, statistical molecular modeling studies were undertaken on a set of 5-nitroimidazole derivatives. The compounds in the selected(More)
Dihydrofolate reductase enzyme has been an attractive biological target for the design and development of antimicrobials. Considering this, we have attempted to identify novel dihydrofolate reductase inhibitors through our well-defined in silico and in vitro work flow. An accurate and predictive pharmacophore model comprising of one hydrogen bond acceptor,(More)
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