Moving Average Analysis Research Articles

Models for anti-inflammatory activity of 8-substituted-4-anilino-6-aminoquinoline-3-carbonitriles

An in silico approach through decision tree (DT) and moving average analysis (MAA) has been employed for development of models for prediction of anti-inflammatory activity. A data set consisting of 44 analogues of 8-substituted-4-anilino-6-aminoquinoline-3-carbonitriles was selected for this study. These compounds act as anti-inflammatory agents through inhibition of tumor progression loci-2 (Tpl2) kinase and tumor necrosis factor-α (TNF-α) production. A total of 44 descriptors of diverse nature, from a large pool of molecular descriptors calculated through E-Dragon software (version 1.0) and an in-house computer program were selected for further analysis. DT was used to determine the importance of molecular descriptors. DT identified two topological indices as most important and classified the analogues involved in the data set with an accuracy of ~91% in training set and ~66% in 10 fold cross validated set. Three independent models were also developed through MAA. Accuracy of prediction of these models varied from 87.5 to 92.5%. The statistical significance of proposed models was assessed through intercorrelation analysis, sensitivity, specificity, and Matthew’s correlation coefficient. The proposed models offer a vast potential for providing lead structures for development of potent anti-inflammatory drugs.

Models for antitubercular activity of 5â-O-[(N-Acyl)sulfamoyl]adenosines.

The relationship between topological indices and antitubercular activity of 5′-O-[(N-Acyl)sulfamoyl]adenosines has been investigated. A data set consisting of 31 analogues of 5′-O-[(N-Acyl)sulfamoyl]adenosines was selected for the present study. The values of numerous topostructural and topochemical indices for each of 31 differently substituted analogues of the data set were computed using an in-house computer program. Resulting data was analyzed and suitable models were developed through decision tree, random forest and moving average analysis (MAA). The goodness of the models was assessed by calculating overall accuracy of prediction, sensitivity, specificity and Mathews correlation coefficient. Pendentic eccentricity index – a novel highly discriminating, non-correlating pendenticity based topochemical descriptor – was also conceptualized and successfully utilized for the development of a model for antitubercular activity of 5′-O-[(N-Acyl)sulfamoyl]adenosines. The proposed index exhibited not only high sensitivity towards both the presence as well as relative position(s) of pendent/heteroatom(s) but also led to significant reduction in degeneracy. Random forest correctly classified the analogues into active and inactive with an accuracy of 67.74%. A decision tree was also employed for determining the importance of molecular descriptors. The decision tree learned the information from the input data with an accuracy of 100% and correctly predicted the cross-validated (10 fold) data with accuracy up to 77.4%. Statistical significance of proposed models was also investigated using intercorrelation analysis. Accuracy of prediction of proposed MAA models ranged from 90.4 to 91.6%.

Trend-surface analysis in geochemical prospecting data, Arouca-Castro Daire region, northern Portugal

The mineral potential of the Arouca-Castro Daire area in the north of Portugal was studied, using geochemical prospecting techniques, with the particular objective of discovering new occurrences of Sb which, in general, are associated with Au. Regional geochemical prospecting of the area was carried out by means of systematic sampling of stream sediments and subsequent analysis for Sb. Detailed geochemical studies made later in an anomalous area and including soil sampling, confirmed its potential interest in terms of possible Sb mineralization. The geochemical data obtained were treated by univariate statistical-mathematical techniques (mainly computer-orientated), which proved to be of great importance in terms of prospecting in making a reliable interpretation of the results obtained. Particular emphasis is given to the application of trend-surface and moving-average analysis in the interpretation of the geochemical data previously obtained.

Gold distribution related to the sedimentology of a Precambrian Witwatersrand conglomerate, South Africa, as outlined by moving-average analysis

Gold distribution related to the sedimentology of a Precambrian Witwatersrand conglomerate, South Africa, as outlined by moving-average analysis

Effect of Drought on Stream Quality in New Jersey

Five consecutive years of drought (1961-66) have had a pronounced effect on the water quality of New Jersey's streams. This is illustrated by comparison of cumulative departures of precipitation and streamflow and of 12-month moving-average analysis of systematically collected water-quality information at stream-sampling sites in the major river systems in the State. The deficiencies of precipitation and streamflow during the drought are shown to have a definite relation to several water-quality parameters. Abnormally high dissolved-solids content, coliform-bacteria counts, and biochemical oxygen demand are shown to occur, as are abnormally low dissolved oxygen and suspended-sediment content, and further intrusion than normal of saline waters into estuarine areas. In general, the maximum deterioration of the water-quality parameters described was observed in late 1965 and early 1966.