Time filter

Source Type

Lachhmangarh Sikar, India

Located in the midst of swathes of desert, Mody University has established itself as a serene snuggery of scientific education for young women. Established in 1998 by Mr R Wikipedia.

Vijendra S.,Mody Institute of Technology and Science
Information Technology Journal | Year: 2011

Finding clusters in a high dimensional data space is challenging because a high dimensional data space has hundreds of attributes and hundreds of data tuples and the average density of data points is very low. The distance functions used by many conventional algorithms fail in this scenario. Clustering relies on computing the distance between objects and thus, the complexity of the similarity models has a severe influence on the efficiency of the clustering algorithms. Especially for density-based clustering, range queries must be supported efficiently to reduce the runtime of clustering. The density-based clustering is also influenced by the density divergence problem that affects the accuracy of clustering. If clusters do not exist in the original high dimensional data space, it may be possible that clusters exist in some subspaces of the original data space. Subspace clustering algorithms localize the search for relevant dimensions allowing them to find clusters that exist in multiple, possibly overlapping subspaces. Subspace clustering algorithms identifies such subspace clusters. But for clustering based on relative region densities in the subspaces, density based subspace clustering algorithms are applied where the clusters are regarded as regions whose densities are relatively high as compared to the region densities in a subspace. This study presents a review of various subspaces based clustering algorithms and density based clustering algorithms with their efficiencies on different data sets. © 2011 Asian Network for Scientific Information. Source

Sharma K.P.,Mody Institute of Technology and Science | John P.J.,University of Rajasthan
Process Biochemistry | Year: 2011

Tannase of Enterobacter sp. was purified and characterized at molecular level. It was found to be 90 kDa in molecular weight. The purified enzyme showed maximum activity at 40 °C. The enzyme was also found to be active in acidic range of pH. The nucleotide and amino acid sequence of tannase exhibited resemblance with the other reported tannase sequences of bacteria, fungi and plants. Probably, this is the first report of tannase gene in Enterobacter sp. The investigation suggests that the purified enzyme can be useful to synthesize molecules of pharmaceutical interest. In addition to above, the enzyme tannase and the organism itself can also be employed to protect grazing animals and environment against the toxic effects caused by tannins in them. © 2010 Elsevier Ltd. All rights reserved. Source

Choudhary D.K.,Mody Institute of Technology and Science
Applied Microbiology and Biotechnology | Year: 2012

Habitat-imposed abiotic and biotic stress is a serious condition and is also a land-degradation problem in arid and semi-arid regions, causing major problem for crop productivity. Most of the cultivable and a least half of irrigated lands around the world are severely affected by environmental stresses. However, in these conditions, there are plant populations successfully adapted and evolutionarily different in their strategy of stress tolerance. Vascular plants do not function as autonomous individuals, but house diverse communities of symbiotic microbes. The role of these microbes can no longer be ignored. Microbial interactions are critical not only for host but also for fungal survival in stressed environments. Plants benefit extensively by harboring these associated microbes; they promote plant growth and confer enhanced resistance to various pathogens by producing antibiotics. To date, improvements in plant quality, production, abiotic and biotic stress resistance, nutrient, and water use have relied largely on manipulating plant genomes by breeding and genetic modification. Increasing evidence indicates that the function of symbiotic microbes seems to parallel more than one of these characteristics. © Springer-Verlag Berlin Heidelberg 2012. Source

Charcoal rot disease, caused by the fungus Macrophomina phaseolina, leads to significant yield losses of soybean crops. One strategy to control charcoal rot is the use of antagonistic, root-colonizing bacteria. Rhizobacteria A 5F and FPT 721 and Pseudomonas sp. strain GRP 3 were characterized for their plant growth-promotion activities against the pathogen. Rhizobacterium FPT 721 exhibited higher antagonistic activity against the pathogen on dual plate assay compared to strain A 5F and GRP 3. FPT 721 and GRP 3 gave decreased disease intensity in terms of average number of pathogen-infested plants. Lipoxygenase (LOX), phenylalanine ammonia-lyase (PAL), and peroxidase (POD) activities were estimated in extracts of plants grown from seeds that were treated with rhizobacteria, and inoculated with spore suspension of M. phaseolina. The activity of these enzymes after challenge with the test pathogen increased. Strains FPT 721 and GRP 3 exhibited maximum increases in LOX, PAL and POD activity (U mg -1 fresh leaf wt) compared to strain A 5F. © 2011 Springer Science+Business Media B.V. Source

Nair S.S.K.,Manipal University India | Subba Reddy N.V.,Mody Institute of Technology and Science | Hareesha K.S.,Manipal University India
BMC Bioinformatics | Year: 2011

Background: Prediction of short stretches in protein sequences capable of forming amyloid-like fibrils is important in understanding the underlying cause of amyloid illnesses thereby aiding in the discovery of sequence-targeted anti-aggregation pharmaceuticals. Due to the constraints of experimental molecular techniques in identifying such motif segments, it is highly desirable to develop computational methods to provide better and affordable in silico predictions.Results: Accurate in silico prediction techniques of amyloidogenic peptide regions rely on the cooperation between informative features and classifier design. In this research article, we propose one such efficient fibril prediction implementation exploiting heterogeneous features based on bio-physio-chemical (BPC) properties, auto-correlation function of carefully selected amino acid indices and atomic composition within a protein fragment of amino acids in a window. In an attempt to get an optimal number of BPC features, an evolutionary Support Vector Machine (SVM) integrating a novel implementation of hybrid Genetic Algorithm termed Memetic Algorithm and SVM is utilized. Five prediction modules designed using Artificial Neural Network (ANN) models are trained with independent and integrated features in order to validate the fibril forming motifs. The results provide evidence that incorporating new feature namely auto-correlation function besides BPC, attempt to strengthen the sequence interaction effect in forming the feature vector thereby obtaining better prediction quality in terms of sensitivity, specificity, Mathews Correlation Coefficient and Area under the Receiver Operating Characteristics curve.Conclusion: A significant improvement in performance is observed by introducing features like auto-correlation function that maintains sequence order effect, in addition to the conventional BPC properties selected through a novel optimization strategy to predict the peptide status - amyloidogenic or non-amyloidogenic. The proposed approach achieves acceptable results, comparable to most online predictors. Besides, it compensates the lacuna in existing amyloid fibril prediction tools by maintaining equilibrium between sensitivity and specificity. © 2011 Nair et al; licensee BioMed Central Ltd. Source

Discover hidden collaborations