scholarly journals DesMol2, an Effective Tool for the Construction of Molecular Libraries and Its Application to QSAR Using Molecular Topology

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 736 ◽  
Author(s):  
Inma García-Pereira ◽  
Riccardo Zanni ◽  
Maria Galvez-Llompart ◽  
Jorge Galvez ◽  
Ramón García-Domenech
Keyword(s):  
Mathematical Models ◽  
Predictive Model ◽  
Data Base ◽  
Web Application ◽  
Molecular Topology ◽  
Multilinear Regression ◽  
Piperazine Derivatives ◽  
Discriminant Analyses ◽  
Molecular Libraries ◽  
Molecular Library

A web application, DesMol2, which offers two main functionalities, is presented: the construction of molecular libraries and the calculation of topological indices. These functionalities are explained through a practical example of research of active molecules to the formylpeptide receptor (FPR), a receptor associated with chronic inflammation in systemic amyloidosis and Alzheimer’s disease. Starting from a data(base) of 106 dioxopiperazine pyrrolidin piperazine derivatives and their respective constant values of binding affinity to FPR, multilinear regression and discriminant analyses are performed to calculate several predictive topological-mathematical models. Next, using the DesMol2 application, a molecular library consisting of 6,120 molecules is built and performed for each predictive model. The best potential active candidates are selected and compared with results from other previous works.

Application of Molecular Topology to the Prediction of Water Quality Indices of Alkylphenol Pollutants

2013 ◽  
pp. 1-10
Author(s):  
Jorge Gálvez ◽  
Miriam Parreño ◽  
Jordi Pla ◽  
Jaime Sanchez ◽  
María Gálvez-Llompart ◽  
...  
Keyword(s):  
Water Quality ◽  
Regression Analysis ◽  
Mathematical Models ◽  
Chemical Oxygen Demand ◽  
Cross Validation ◽  
Oxygen Demand ◽  
Molecular Topology ◽  
Quality Indices ◽  
Randomization Tests ◽  
Internal Validation

In this paper, topological-mathematical models based on multilineal regression analysis have been built as a model of the degradability of 26 alkylphenols through the Chemical Oxygen Demand (COD) and Biochemical Oxigen Demand (BOD5). Two models with three-variable were selected (r2= 0.8793 and q2=0.8075 for log(1/COD) and r2= 0.8928 and q2=0.8327 for log(1/BOD5). The models were validated by cross-validation, internal validation and randomization tests. The results, which stand in good accordance with the obtained results, confirm the robustness of the method.

scholarly journals Machine Learning Algorithms Using Logistic Regression for Predicting Neurosurgical Outcomes

2020 ◽  
Author(s):  
Nida Fatima
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Predictive Model ◽  
Web Application ◽  
Learning Algorithms ◽  
Area Under The Curve ◽  
Machine Learning Algorithms ◽  
Brier Score ◽  
Patient Counselling ◽  
Selection Of Variables

Abstract Background: Preoperative prognostication of clinical and surgical outcome in patients with neurosurgical diseases can improve the risk stratification, thus can guide in implementing targeted treatment to minimize these events. Therefore, the author aims to highlight the development and validation of predictive models determining neurosurgical outcomes through machine learning algorithms using logistic regression.Methods: Logistic regression (enter, backward and forward) and least absolute shrinkage and selection operator (LASSO) method for selection of variables from selected database can eventually lead to multiple candidate models. The final model with a set of predictive variables must be selected based upon the clinical knowledge and numerical results.Results: The predictive model which performed best on the discrimination, calibration, Brier score and decision curve analysis must be selected to develop machine learning algorithms. Logistic regression should be compared with the LASSO model. Usually for the big databases, the predictive model selected through logistic regression gives higher Area Under the Curve (AUC) than those with LASSO model. The predictive probability derived from the best model could be uploaded to an open access web application which is easily deployed by the patients and surgeons to make a risk assessment world-wide.Conclusions: Machine learning algorithms provide promising results for the prediction of outcomes following cranial and spinal surgery. These algorithms can provide useful factors for patient-counselling, assessing peri-operative risk factors, and predicting post-operative outcomes after neurosurgery.

scholarly journals GIS/GPS SOLUTIONS AS EFFICIENT TOOLS FOR SUSTAINABLE MANAGEMENT OF VINEYARDS IN KOSOVO

2019 ◽  
Vol 45 (5) ◽  
pp. 28-36
Author(s):  
Ymer Kuka ◽  
Perparim Ameti ◽  
Temenoujka Bandrova
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Information Management ◽  
Sustainable Management ◽  
Web Application ◽  
Gis Technology ◽  
Mobile Gis ◽  
Java Programming ◽  
Gis System ◽  
Insight Into

The main objective of this paper is to analyze and develop a GIS system that includes all necessary information obtained by using GPS and mobile GIS techniques as well. Since several techniques for information management exist, the aim is how to integrate them for a sustainable management of vineyards areas in Kosovo. It has been designed a system, which is able to produce maps, make various analyses based on the requests of the specific users and offers trend orientation for decision making. The JAVA programming language has been used. This provides the most possible flexibility in the data flow and data management. The structure of the data base is proposed to be designed in that way that the textual and geometric data have been processed in a unique data base in PostGIS PostgreSQL technology.Web GIS technology presented in this paper, shows an advantage comparing to the desktop based technology since it enables an access in real time. Foremost, the application offers an access depending on the roles and privileges for different users. Development of a WEB application for viticulture management will improve the efficiency and decision making process as well.Results show numerous capabilities of GIS methodologies to manage the agricultural crops, in this particular case, the vineyards. Further, the results provide insight into information management in a single system and serve as a basis for similar researches in other areas of agriculture in the future.

scholarly journals Methods for measuring the evolutionary stability of engineered genomes to improve their longevity

2021 ◽  
Author(s):  
Scott L Nuismer ◽  
Nathan C. Layman ◽  
Alec J Redwood ◽  
Baca Chan ◽  
James J Bull
Keyword(s):  
Mathematical Models ◽  
Mutation Rate ◽  
Half Life ◽  
Web Application ◽  
Estimation Method ◽  
Evolutionary Stability ◽  
Serial Transfer ◽  
Predictive Tools ◽  
Mutation And Selection

Abstract Diverse applications rely on engineering microbes to carry and express foreign transgenes. This engineered baggage rarely benefits the microbe and is thus prone to rapid evolutionary loss when the microbe is propagated. For applications where a transgene must be maintained for extended periods of growth, slowing the rate of transgene evolution is critical and can be achieved by reducing either the rate of mutation or the strength of selection. Because the benefits realized by changing these quantities will not usually be equal, it is important to know which will yield the greatest improvement to the evolutionary half-life of the engineering. Here, we provide a method for jointly estimating the mutation rate of transgene loss and the strength of selection favoring these transgene-free, revertant individuals. The method requires data from serial transfer experiments in which the frequency of engineered genomes is monitored periodically. Simple mathematical models are developed that use these estimates to predict the half-life of the engineered transgene and provide quantitative predictions for how alterations to mutation and selection will influence longevity. The estimation method and predictive tools have been implemented as an interactive web application, MuSe.

scholarly journals Reformulating the Cube Law for Proportional Representation Elections

1986 ◽  
Vol 80 (2) ◽  
pp. 489-504 ◽  
Author(s):  
Rein Taagepera
Keyword(s):  
Predictive Model ◽  
Data Base ◽  
Curve Fitting ◽  
Proportional Representation ◽  
Total Size ◽  
Allocation Rules ◽  
Seat Allocation ◽  
Basic Features ◽  
Number Of Parties ◽  
Existing Data

The cube law was proposed around 1910 to express the conversion of a party's vote shares into its seat share in two-party plurality elections with single-seat districts. This article develops predictive seat-vote equations for a much wider range of elections, including those involving many parties, single- and multi-seat districts, and diverse seat allocation rules such as plurality and list proportional representation (PR). Without any statistical curve fitting based on the seat and vote shares themselves, the basic features of the conversion are predicted using exogenous parameters: magnitude and number of districts, number of parties, and total size of the electorate and of the assembly. The link between the proposed equations and the original cube law is explicated. Using an existing data base, the fit of the predictive model is examined. On balance, this model accounts well for the conversion of votes to seats, and for the deviation from proportionality in PR systems.

scholarly journals A predictive model of “favorable” and “unfavorable” anteroposterior skeletal relations among Class Is and Class IIs

2021 ◽  
Author(s):  
Jacob S. Bleyer ◽  
Larry Tadlock ◽  
Matthew Kesterke ◽  
Peter H. Buschang
Keyword(s):  
Longitudinal Study ◽  
Predictive Model ◽  
Multiple Regression ◽  
Discriminant Function ◽  
Growth Potential ◽  
Valid Measure ◽  
Discriminant Analyses

ABSTRACT Objectives To validate the use of the sagittal distance between ANS and Pg (ANSPg) as a measure of favorable and unfavorable anteroposterior skeletal relations and to identify multivariate cephalometric measures that could be used to predict favorable and unfavorable relations at 15 years of age. Materials and Methods This longitudinal study included 226 untreated adolescents evaluated at 10 and 15 years of age. Patients were grouped as “favorable” or “unfavorable” based on the ANSPg (measured parallel to S-N -7°) at 15 years of age (ANSPg15). ANSPg15 was validated based on its correlation with changes in ANSPg between 10 and 15 years of age, as well as its relationships with established measures of growth potential. Multiple regression and discriminant analyses were performed to predict ANSPg15 from measures at 10 years of age. Results ANSPg15 and the change in ANSPg between 10 and 15 years of age were significantly correlated (R= –0.661; P ≤ .001), with 77% of patients in whom relationships improved (ie, distance decreased) exhibiting favorable relationships at 15 years of age. Established measures of growth potential were significantly (P < .001) correlated with ANSPg15 and showed significant differences between patients with favorable and unfavorable relations. Multiple regression showed that the Y-axis, ANS-N-Pg, and symphyseal angle measured at 10 years explained approximately 60% (R = 0.78) of the variation in ANSPg15. Based on these three variables, discriminant function correctly predicted favorable or unfavorable relations of ANSPg15 77% of the time. Conclusions ANSPg15 was a valid measure for determining favorable and unfavorable anteroposterior skeletal relationships that could be predicted with moderately high levels of accuracy.

Kinematic and Passive Resistive Properties of Human Elbow Complex

1987 ◽  
Vol 109 (4) ◽  
pp. 318-323 ◽  
Author(s):  
Ali Erkan Engin ◽  
Shuenn-Muh Chen
Keyword(s):  
Mathematical Models ◽  
Data Base ◽  
Human Body ◽  
Statistical Data ◽  
Normal Male ◽  
Angular Range ◽  
Elbow Extension ◽  
Expansion Form ◽  
Motion Studies ◽  
Male Subjects

In recent years, owing to their versatility and reduced cost of operation, multisegmented mathematical models of the total human body have gained increased attention in gross biodynamic motion studies. This, in turn, has stimulated the need for a proper biomechanical data base for the major human articulating joints. The lack of such a database for the humero-elbow complex is the impetus for this study. The total angular range of motion permitted by the complex and the passive resistive properties beyond the full elbow extension were studied. Results obtained on ten normal male subjects were utilized to establish a statistical data base for the humero-elbow complex. Results are also expressed in functional expansion form suitable for incorporation into the existing multisegmented models.

A Problem of Domain Restriction in Data Bases a Logical Approach

1985 ◽  
Vol 8 (1) ◽  
pp. 1-25
Author(s):  
Andrzej W. Jankowski ◽  
Cecylia Rauszer
Keyword(s):  
Information Systems ◽  
Mathematical Models ◽  
Data Base ◽  
Mathematical Description ◽  
Data Bases ◽  
Domain Restriction ◽  
Intermediate Logic ◽  
Logical Constants ◽  
Limited Access ◽  
Logical Approach

The paper deals with the mathematical description of information systems with a limited access to a data base. Similarly as in [1] an area to which the user has access is called his priority. The information systems introduced in the paper are mathematical models for an intermediate logic with logical constants that corresponds to the priorities. The principles for operating this language are described, as well as a complete semantics is formulated.

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