Statistical methods used in qsar analysis

  • What are the statistical methods used in data analysis?

    Two main statistical methods are used in data analysis: descriptive statistics, which summarizes data using indexes such as mean and median and another is inferential statistics, which draw conclusions from data using statistical tests such as student's t-test..

  • What is the methodology of QSAR?

    QSAR is based on the hypothesis that similar structural compounds may possess similar biological activities (Miki, 2002).
    Chemical features of molecules, also known as molecular descriptors, are correlated with the observed activity by the mean of statistical analysis..

These methods include Best Multiple Linear Regression (BMLR), Heuristic Method (HM), Genetic Algorithm based Multiple Linear Regression (GA-MLR), Stepwise MLR, Factor Analysis MLR and so on. The three most important and commonly used of these methods are described in detail below.

How can QSAR be used to reduce intercorrelated and redundant chemical information?

Furthermore, the descriptor data matrix can also be subjected to various pruning methods to reduce intercorrelated and redundant chemical information.
The developed QSAR models are also subjected to several validation tests to check for the reliability of the developed correlation models.

,

How is a QSAR model validated?

The developed QSAR models are also subjected to several validation tests to check for the reliability of the developed correlation models.
After its development, a QSAR model is usually verified by employing multiple statistical validation strategies giving an estimation of its predictivity and stability.

,

What is multiple linear regression (MLR) in QSAR?

6.2.1 Multiple linear regression Multiple linear regression (MLR) is one of the most popular methods of QSAR due to its simplicity in operation, reproducibility, and ability to allow easy interpretation of the features used.
This is a regression approach of the dependent variable (response property or activity) on more than one descriptor.

Matched molecular pair analysis (MMPA) is a method in cheminformatics that compares the properties of two molecules that differ only by a single chemical transformation, such as the substitution of a hydrogen atom by a chlorine one.
Such pairs of compounds are known as matched molecular pairs (MMP).
Because the structural difference between the two molecules is small, any experimentally observed change in a physical or biological property between the matched molecular pair can more easily be interpreted.
The term was first coined by Kenny and Sadowski in the book Chemoinformatics in Drug Discovery.
Statistical methods used in qsar analysis
Statistical methods used in qsar analysis

Overview of the industry in Estonia

There are two kinds of oil shale in Estonia, both of which are sedimentary rocks laid down during the Ordovician geologic period.
Graptolitic argillite is the larger oil shale resource, but, because its organic matter content is relatively low, it is not used industrially.
The other is kukersite, which has been mined for more than a hundred years.
Kukersite deposits in Estonia account for 1% of global oil shale deposits.

Categories

Statistical methods used in research
Statistical methods used to analyze data
Statistical methods used in classification
Statistical methods used in epidemiology
Statistical methods used in human resources
Statistical methods ucf
Statistical methods used in forecasting
Statistical methods using r
Statistical methods used in quality control
Statistical methods used in quantitative research
Statistical methods used in excel
Statistical methods uitm
Statistical methods vs machine learning
Statistical methods valencia
Neural networks and statistical methods
Statistical methods variability
Statistical method validation for test laboratories
Statistical method variance
Statistical method voting
Statistical analysis vocabulary