Modeling structure property relationships with Kernel recursive least squares

Motivation: Modeling structure property relationships accurately is a challenging task and newly developed kernel based methods may provide the accuracy for building these relationships. Method: Kernelized variant of traditional recursive least squares algorithm is used to model two QSPR datasets. Results: All the datasets showed a good correlation between actual and predicted values of boiling points with root mean squared errors (RMSEs) comparable to other conventional methods. For the datasets from Espinosa et al., KRLS showed good prediction statistics with R value in the range of 0.97-0.99 and S value in the range 5.5- 8 as compared to multiple linear regression (MLR) with R value in the range 0.85-0.88 and S value in the range 22-26. For the dataset from Trinajstiu et al., KRLS performed consistently well with R values lying in the range of 0.95-0.99 and S in the range of 5-10 as compared to MLR with R values in the range of 0.7-0.85 and S in the range of 25-30. Conclusions: The KRLS method works better when more number of variables from the dataset are included as against other methods such as support vector learning or lazy learning technique which works better for smaller number of reduced relevant variables from the dataset

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Not AvailableIn the view of endemic avian influenza H9N2 infection in poultry, its zoonotic potential and emergence of antiviral resistance, two herbal plants, Ocimum sanctum and Acacia arabica, which are easily available throughout various geographical locations in India were taken up to study their antiviral activity against H9N2 virus. We evaluated antiviral efficacy of three different extracts each from leaves of O. sanctum (crude extract, terpenoid and polyphenol) and A. arabica (crude extract, flavonoid and polyphenol) against H9N2 virus using in ovo model. METHODS: The antiviral efficacy of different leaves extracts was systematically studied in three experimental protocols viz. virucidal (dose-dependent), therapeutic (time-dependent) and prophylactic (dose-dependent) activity employing in ovo model. The maximum non-toxic concentration of each herbal extracts of O. sanctum and A. arabica in the specific pathogen free embryonated chicken eggs was estimated and their antiviral efficacy was determined in terms of reduction in viral titres, measured by Haemagglutination (HA) and real time quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays. RESULTS: All the extracts of O. sanctum (crude extract, terpenoid and polyphenol) and A. arabica (crude extract, flavonoid and polyphenol) showed significant virucidal activity, however, crude extract ocimum and terpenoid ocimum showed highly significant to significant (p < 0.001-0.01) decrease in virus genome copy numbers with lowest dose tested. Similarly, therapeutic effect was observed in all three extracts of O. sanctum in comparison to the virus control, nevertheless, crude extract ocimum and terpenoid ocimum maintained this effect for longer period of time (up to 72 h post-incubation). None of the leaves extracts of A. arabica had therapeutic effect at 24 and 48 h post-incubation, however, only the crude extract acacia and polyphenol acacia showed delayed therapeutic effect (72 h post-inoculation). Prophylactic potential was observed in polyphenol acacia with highly significant antiviral activity compared to virus control (p < 0.001). CONCLUSIONS: The crude extract and terpenoid isolated from the leaves of O. sanctum and polyphenol from A. arabica has shown promising antiviral properties against H9N2 virus. Future investigations are necessary to formulate combinations of these compounds for the broader antiviral activity against H9N2 viruses and evaluate them in chickensNot Availabl