Data Mining has become an important technique for the exploration and extraction of data in numerous and various research projects in different fields (technology, information technology, business, the environment, ec...Data Mining has become an important technique for the exploration and extraction of data in numerous and various research projects in different fields (technology, information technology, business, the environment, economics, etc.). In the context of the analysis and visualisation of large amounts of data extracted using Data Mining on a temporary basis (time-series), free software such as R has appeared in the international context as a perfect inexpensive and efficient tool of exploitation and visualisation of time series. This has allowed the development of models, which help to extract the most relevant information from large volumes of data. In this regard, a script has been developed with the goal of implementing ARIMA models, showing these as useful and quick mechanisms for the extraction, analysis and visualisation of large data volumes, in addition to presenting the great advantage of being applied in multiple branches of knowledge from economy, demography, physics, mathematics and fisheries among others. Therefore, ARIMA models appear as a Data Mining technique, offering reliable, robust and high-quality results, to help validate and sustain the research carried out.展开更多
Background:Coumarins are secondary metabolites from the phenylpropanoid-type biosynthesis in higher plants.A plethora of potential phytopharmacological activities have been described for derivatives of the coumarin sc...Background:Coumarins are secondary metabolites from the phenylpropanoid-type biosynthesis in higher plants.A plethora of potential phytopharmacological activities have been described for derivatives of the coumarin scaffold:hepatoprotective,antineoplastic,antimicrobial,antituberculosis,antiviral,anti-inflammatory anticoagulant,or antithrombotic effects.Objective:A computer-based quantitative structure–activity relationships(QSAR)study for a series of 4‑chloro-3-formylcoumarins was carried out.Methods:To this end we generated the 3D models of 17 published coumarin structures,calculated their physicochemical properties(descriptors)to correlate them to their experimentally known biological activities measured as inhibition concentrations to block the target enzyme activity.Our proposed approach used free molecular modeling software and applies our scripts written in the programming language R.Results:The final multiple regression models achieved satisfactory results with a small number of descriptors–all of which were statistically significant and meaningful in the field of pharmacodynamics to develop new 3-formylcoumarins with enhanced activities targeting the human thymidine phosphorylase enzyme.Conclusion:On theoretical grounds,our in silico research contributes in a crucial step in the field of complementary phyto-medicine.This step is located between in vivo pharmacological observations of plant extracts on ethnopharmacological,preclinical or controlled clinical levels and the need to identify–at an atomic scale–all those plant ingredients responsible for the biological actions under scrutiny.Our simulations shed light on the modification of phyto-medicine’s physicochemical properties to enhance the interaction with their biomolecular target in the patient’s body.展开更多
文摘Data Mining has become an important technique for the exploration and extraction of data in numerous and various research projects in different fields (technology, information technology, business, the environment, economics, etc.). In the context of the analysis and visualisation of large amounts of data extracted using Data Mining on a temporary basis (time-series), free software such as R has appeared in the international context as a perfect inexpensive and efficient tool of exploitation and visualisation of time series. This has allowed the development of models, which help to extract the most relevant information from large volumes of data. In this regard, a script has been developed with the goal of implementing ARIMA models, showing these as useful and quick mechanisms for the extraction, analysis and visualisation of large data volumes, in addition to presenting the great advantage of being applied in multiple branches of knowledge from economy, demography, physics, mathematics and fisheries among others. Therefore, ARIMA models appear as a Data Mining technique, offering reliable, robust and high-quality results, to help validate and sustain the research carried out.
文摘Background:Coumarins are secondary metabolites from the phenylpropanoid-type biosynthesis in higher plants.A plethora of potential phytopharmacological activities have been described for derivatives of the coumarin scaffold:hepatoprotective,antineoplastic,antimicrobial,antituberculosis,antiviral,anti-inflammatory anticoagulant,or antithrombotic effects.Objective:A computer-based quantitative structure–activity relationships(QSAR)study for a series of 4‑chloro-3-formylcoumarins was carried out.Methods:To this end we generated the 3D models of 17 published coumarin structures,calculated their physicochemical properties(descriptors)to correlate them to their experimentally known biological activities measured as inhibition concentrations to block the target enzyme activity.Our proposed approach used free molecular modeling software and applies our scripts written in the programming language R.Results:The final multiple regression models achieved satisfactory results with a small number of descriptors–all of which were statistically significant and meaningful in the field of pharmacodynamics to develop new 3-formylcoumarins with enhanced activities targeting the human thymidine phosphorylase enzyme.Conclusion:On theoretical grounds,our in silico research contributes in a crucial step in the field of complementary phyto-medicine.This step is located between in vivo pharmacological observations of plant extracts on ethnopharmacological,preclinical or controlled clinical levels and the need to identify–at an atomic scale–all those plant ingredients responsible for the biological actions under scrutiny.Our simulations shed light on the modification of phyto-medicine’s physicochemical properties to enhance the interaction with their biomolecular target in the patient’s body.
