Theological Dogmas in Karunambara Pathigam of Veermamunivar

It is not exaggeration that Veermamunivar was very much proficient to start learning completely a different and new language after the age of thirty and to produce grammar, Literature and dictionaries in that Language. In his 36 years of life in Tamilnadu from 1711 till 1747 as a refined Tamilian. He has rendered great service in various disciplines such as making of sathuragarathi, production of grammar, Reformation in shapes of Literature, Writing Epics, creation of short-story, The advent of prose, outburst of minor literature, The bond between Tamil and Latin, The attempt to make Thirukural as Universal book. This essay attempts to explain various features such as Nature of God, His uniqueness, creations, and greatness of sacred feet, incomparable leadership, omnipotence, gracious benevolence. These features are found in one of his minor Literatures callerd Karunambara Pathigam

From sequence to enzyme mechanism using multi-label machine learning

Background: In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling. Results: In this study, we evaluate whether sequence identity, InterPro or Catalytic Site Atlas sequence signatures provide enough information for bulk prediction of enzyme mechanism. By splitting MACiE (Mechanism, Annotation and Classification in Enzymes database) mechanism labels to a finer granularity, which includes the role of the protein chain in the overall enzyme complex, the method can predict at 96% accuracy (and 96% micro-averaged precision, 99.9% macro-averaged recall) the MACiE mechanism definitions of 248 proteins available in the MACiE, EzCatDb (Database of Enzyme Catalytic Mechanisms) and SFLD (Structure Function Linkage Database) databases using an off-theshelf K-Nearest Neighbours multi-label algorithm. Conclusion: We find that InterPro signatures are critical for accurate prediction of enzyme mechanism. We also find that incorporating Catalytic Site Atlas attributes does not seem to provide additional accuracy. The software code (ml2db), data and results are available online at http://sourceforge.net/projects/ml2db/ and as supplementary files.Publisher PDFPeer reviewe

Effect of Rosiglitazone Versus Insulin on the Pancreatic {beta}-Cell Function of Subjects With Type 2 Diabetes

doi:10.1152/ajpendo.00104.2002 You might find this additional information useful... This article cites 18 articles, 13 of which you can access free at