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Search Results: 1 - 10 of 191419 matches for " Sorana D. Bolboac? "
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Assessment of Random Assignment in Training and Test Sets using Generalized Cluster Analysis Technique
Sorana D. BOLBOAC
Applied Medical Informatics , 2011,
Abstract: Aim: The properness of random assignment of compounds in training and validation sets was assessed using the generalized cluster technique. Material and Method: A quantitative Structure-Activity Relationship model using Molecular Descriptors Family on Vertices was evaluated in terms of assignment of carboquinone derivatives in training and test sets during the leave-many-out analysis. Assignment of compounds was investigated using five variables: observed anticancer activity and four structure descriptors. Generalized cluster analysis with K-means algorithm was applied in order to investigate if the assignment of compounds was or not proper. The Euclidian distance and maximization of the initial distance using a cross-validation with a v-fold of 10 was applied. Results: All five variables included in analysis proved to have statistically significant contribution in identification of clusters. Three clusters were identified, each of them containing both carboquinone derivatives belonging to training as well as to test sets. The observed activity of carboquinone derivatives proved to be normal distributed on every. The presence of training and test sets in all clusters identified using generalized cluster analysis with K-means algorithm and the distribution of observed activity within clusters sustain a proper assignment of compounds in training and test set. Conclusion: Generalized cluster analysis using the K-means algorithm proved to be a valid method in assessment of random assignment of carboquinone derivatives in training and test sets.
The Effect of Negative Air Ionization Exposure on Ontogenetic Development of Chicken
Valeria LAZA,Sorana D. BOLBOAC
Leonardo Electronic Journal of Practices and Technologies , 2008,
Abstract: Most of the benefic effects of negative air ions (NAI) quoted in the literature until the end of the 20th century were obtained with high doses of NAI, but at these doses a phased action was noted: favorable at the beginning, then unfavorable on extended exposures. In Romania, experimental studies on animal or human subjects were made mostly with moderate doses of air ions, close to those in the nature, and the duration of ionization was limited. In order to clear out some methodological issues regarding the air ionization use, we proposed to make a stepped set of investigations, on the hen egg submitted to incubation.The first goal of our study follows to evaluate the role of NAI on the development of the chicken embryo, in average concentration, but with extended exposure. The second goal is to detect the effects of negative air ionization in high doses on the incubated eggs, as well as to accentuate the periods of chicken eggs’ ontogenetic development periods, when air ionization acts stronger, or with more benefits.In the first experiment, the eggs were submitted to moderate air ionization day and night (in continuous application), during all the incubation period (21days). In the second experiment the eggs were ionized with high doses of negative air ions, in different period of ontogenetic development.Continuous ionization (day and night) with moderate doses of NAI, during entire period of eggs incubation (21 days), supports the idea of phased action of air ions in moderate doses: favorable at the beginning and unfavorable later, if the exposure to air ions is extended. The application of higher doses of air ions appeared to be positive in the eggs development and hatching, but only if the exposure was made in the second half of incubation, after the chicken development was finished.
Design of Experiments: Useful Orthogonal Arrays for Number of Experiments from 4 to 16
Sorana D. Bolboac,Lorentz J?ntschi
Entropy , 2007, DOI: 10.3390/e9040198
Abstract: A methodology for the design of an experiment is proposed in order to find asmany schemes as possible with the maximum number of factors with different levels for thesmallest number of experimental runs. An algorithm was developed and homemadesoftware was implemented. The abilities in generation of the largest groups of orthogonalarrays were analyzed for experimental runs of 4, 6, 8, 9, 10, 12, 14, 15, and 16. The resultsshow that the proposed method permits the construction of the largest groups of orthogonalarrays with the maximum number of factors.
Informational Entropy of B-ary Trees after a Vertex Cut
Lorentz J?ntschi,Sorana D. Bolboac
Entropy , 2008, DOI: 10.3390/e10040576
Abstract: Together with stars and paths, b-ary trees are one of the most studied acyclic graph structures. As any other structure, a b-ary tree can be seen as containing information. The aim of the present research was to assess through informational entropy the structural information changes in b-ary trees after removal of an arbitrary vertex.
Mapping Cigarettes Similarities using Cluster Analysis Methods
Sorana D. Bolboac,Lorentz J?ntschi
International Journal of Environmental Research and Public Health , 2007, DOI: 10.3390/ijerph2007030007
Abstract: The aim of the research was to investigate the relationship and/or occurrences in and between chemical composition information (tar, nicotine, carbon monoxide), market information (brand, manufacturer, price), and public health information (class, health warning) as well as clustering of a sample of cigarette data. A number of thirty cigarette brands have been analyzed. Six categorical (cigarette brand, manufacturer, health warnings, class) and four continuous (tar, nicotine, carbon monoxide concentrations and package price) variables were collected for investigation of chemical composition, market information and public health information. Multiple linear regression and two clusterization techniques have been applied. The study revealed interesting remarks. The carbon monoxide concentration proved to be linked with tar and nicotine concentration. The applied clusterization methods identified groups of cigarette brands that shown similar characteristics. The tar and carbon monoxide concentrations were the main criteria used in clusterization. An analysis of a largest sample could reveal more relevant and useful information regarding the similarities between cigarette brands.
Predictivity Approach for Quantitative Structure-Property Models. Application for Blood-Brain Barrier Permeation of Diverse Drug-Like Compounds
Sorana D. Bolboac,Lorentz J?ntschi
International Journal of Molecular Sciences , 2011, DOI: 10.3390/ijms12074348
Abstract: The goal of the present research was to present a predictivity statistical approach applied on structure-based prediction models. The approach was applied to the domain of blood-brain barrier (BBB) permeation of diverse drug-like compounds. For this purpose, 15 statistical parameters and associated 95% confidence intervals computed on a 2 × 2 contingency table were defined as measures of predictivity for binary quantitative structure-property models. The predictivity approach was applied on a set of compounds comprised of 437 diverse molecules, 122 with measured BBB permeability and 315 classified as active or inactive. A training set of 81 compounds (~2/3 of 122 compounds assigned randomly) was used to identify the model and a test set of 41 compounds was used as the internal validation set. The molecular descriptor family on vertices cutting was the computation tool used to generate and calculate structural descriptors for all compounds. The identified model was assessed using the predictivity approach and compared to one model previously reported. The best-identified classification model proved to have an accuracy of 69% in the training set (95%CI [58.53–78.37]) and of 73% in the test set (95%CI [58.32–84.77]). The predictive accuracy obtained on the external set proved to be of 73% (95%CI [67.58–77.39]). The classification model proved to have better abilities in the classification of inactive compounds (specificity of ~74% [59.20–85.15]) compared to abilities in the classification of active compounds (sensitivity of ~64% [48.47–77.70]) in the training and external sets. The overall accuracy of the previously reported model seems not to be statistically significantly better compared to the identified model (~81% [71.45–87.80] in the training set, ~93% [78.12–98.17] in the test set and ~79% [70.19–86.58] in the external set). In conclusion, our predictivity approach allowed us to characterize the model obtained on the investigated set of compounds as well as compare it with a previously reported model. According to the obtained results, the reported model should be chosen if a correct classification of inactive compounds is desired and the previously reported model should be chosen if a correct classification of active compounds is most wanted.
A Structural Modelling Study on Marine Sediments Toxicity
Lorentz J?ntschi,Sorana D. Bolboac
Marine Drugs , 2008, DOI: 10.3390/md6020372
Abstract: Quantitative structure-activity relationship models were obtained by applying the Molecular Descriptor Family approach to eight ordnance compounds with different toxicity on five marine species (arbacia punctulata, dinophilus gyrociliatus, sciaenops ocellatus, opossum shrimp, and ulva fasciata). The selection of the best among molecular descriptors generated and calculated from the ordnance compounds structures lead to accurate monovariate models. The resulting models obtained for six endpoints proved to be accurate in estimation (the squared correlation coefficient varied from 0.8186 to 0.9997) and prediction (the correlation coefficient obtained in leave-one-out analysis varied from 0.7263 to 0.9984).
Observation vs. Observable: Maximum Likelihood Estimations according to the Assumption of Generalized Gauss and Laplace Distributions
Lorentz J?NTSCHI,Sorana D. BOLBOAC
Leonardo Electronic Journal of Practices and Technologies , 2009,
Abstract: Aim: The paper aims to investigate the use of maximum likelihood estimation to infer measurement types with their distribution shape. Material and Methods: A series of twenty-eight sets of observed data (different properties and activities) were studied. The following analyses were applied in order to meet the aim of the research: precision, normality (Chi-square, Kolmogorov-Smirnov, and Anderson-Darling tests), the presence of outliers (Grubbs’ test), estimation of the population parameters (maximum likelihood estimation under Laplace, Gauss, and Gauss-Laplace distribution assumptions), and analysis of kurtosis (departure of sample kurtosis from the Laplace, Gauss, and Gauss-Laplace population kurtosis). Results: The mean of most investigated sets was likely to be Gauss-Laplace while the standard deviation of most investigated sets of compound was likely to be Gauss. The MLE analysis allowed making assumptions regarding the type of errors in the investigated sets. Conclusions: The proposed procedure proved to be useful in analyzing the shape of the distribution according to measurement type and generated several assumptions regarding their association.
Structure-Activity Relationships on the Molecular Descriptors Family Project at the End
Lorentz J?NTSCHI,Sorana D. BOLBOAC
Leonardo Electronic Journal of Practices and Technologies , 2007,
Abstract: Molecular Descriptors Family (MDF) on the Structure-Activity Relationships (SAR), a promising approach in investigation and quantification of the link between 2D and 3D structural information and the activity, and its potential in the analysis of the biological active compounds is summarized. The approach, attempts to correlate molecular descriptors family generated and calculated on a set of biological active compounds with their observed activity. The estimation as well as prediction abilities of the approach are presented. The obtained MDF SAR models can be used to predict the biological activity of unknown substrates in a series of compounds.
Entropy due to Fragmentation of Dendrimers
Lorentz J?ntschi,Sorana D. Bolboac
Surveys in Mathematics and its Applications , 2009,
Abstract: Subgraphs can results through application of criteria based on matrix which characterize the entire graph. The most important categories of criteria are the ones able to produce connected subgraphs (fragments). Based on theoretical frame on graph theory, the fragmentation algorithm on pair of vertices containing the largest fragments (called MaxF) are exemplified. The counting polynomials are used to enumerate number of all connected substructures and their sizes. For a general class of graphs called dendrimers general formulas giving counting polynomials are obtained and characterized using informational measures.
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