Biostatistics - quiz

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Questions and Answers

Which of the following is a primary goal of telemedicine?

  • To replace traditional in-person medical consultations.
  • To improve access to healthcare services, especially in remote areas. (correct)
  • To create new ways to make the medical practice more expensive.
  • To solely focus on developing new medical devices.

What does the partition coefficient (P) primarily describe?

  • The distribution of a drug between lipophilic and hydrophilic phases (correct)
  • The strength of a drug's binding to a receptor
  • The electrical charge of a drug molecule
  • The rate of drug metabolism in the liver

In the context of statistical hypothesis testing, what does a Type II error refer to?

  • Correctly rejecting the null hypothesis.
  • Failing to reject the null hypothesis that is actually false. (correct)
  • Accepting the null hypothesis that is correct.
  • Falsely rejecting the null hypothesis.

Which of the following best describes the characteristics of a representative sample in statistics?

<p>It accurately reflects the characteristics of the entire population. (A)</p> Signup and view all the answers

What is the primary purpose of constructing an artificial neuron in neural networks?

<p>To model and process information through a simplified mathematical calculation. (A)</p> Signup and view all the answers

What is the main difference between supervised and unsupervised learning methods as used in neural networks?

<p>Supervised learning requires labeled data for training, while unsupervised learning does not. (C)</p> Signup and view all the answers

What is a key characteristic of the normal distribution, often described by the '3 sigma rule'?

<p>Approximately 99.7% of the data falls within 3 standard deviations of the mean. (C)</p> Signup and view all the answers

If the correlation coefficient is close to -1, what is the relationship between variables?

<p>Strong negative correlation (D)</p> Signup and view all the answers

Which of the following best describes the relationship between accuracy and precision in the context of measurement?

<p>Accuracy refers to how close measurements are to the true value, while precision refers to how close measurements are to each other. (A)</p> Signup and view all the answers

In computer-aided drug design, what is the primary distinction between receptor-independent (RI) and receptor-dependent (RD) design?

<p>RI focuses solely on the drug's physical properties, while RD involves interaction with a known receptor structure. (B)</p> Signup and view all the answers

Which of the following is a characteristic of a Kohonen network?

<p>It is an unsupervised learning method used for data visualization and dimensionality reduction. (D)</p> Signup and view all the answers

What is the primary purpose of data preprocessing steps such as scaling and centering in statistics?

<p>To normalize the data and improve the performance of algorithms by preventing bias. (B)</p> Signup and view all the answers

If a statistical test results in the rejection of the null hypothesis, what does this indicate?

<p>There is strong evidence against the null hypothesis and in favor of the alternative. (D)</p> Signup and view all the answers

Which of the following best describes the concept of a 'pharmacophore'?

<p>The set of structural features in a molecule that are responsible for its biological activity. (B)</p> Signup and view all the answers

How does the concept of 'lipophilicity', as a molecular descriptor, influence drug design?

<p>It describes the drug's ability to dissolve in lipid and fat, crucial for membrane permeability and ADME. (B)</p> Signup and view all the answers

In the context of a reverse antagonist, what is its primary mode of action?

<p>It binds to a receptor, causing the opposite effect of an agonist. (D)</p> Signup and view all the answers

Which of the following accurately describes a key aspect of 1D-4D drug models?

<p>They involve the use of time-dependent properties of molecular structures. (A)</p> Signup and view all the answers

If a dataset's dispersion is high, what can be generally inferred about the dataset?

<p>The data points are widely scattered from the mean. (D)</p> Signup and view all the answers

Which scenario best exemplifies the concept of a confidence interval?

<p>Estimating a range within which the true population mean likely lies. (A)</p> Signup and view all the answers

In neural network training, Hebb's rule is used for what purpose?

<p>Unsupervised learning to modify connection strengths based on neuron firing patterns. (A)</p> Signup and view all the answers

When comparing two samples, what does a Student's t-distribution help to determine?

<p>The difference between two means by showing the probability of obtaining this difference. (C)</p> Signup and view all the answers

Which measure is the most sensitive to extreme values in a dataset?

<p>Arithmetic Mean (C)</p> Signup and view all the answers

If a drug is highly lipophilic, what characteristic would be most expected?

<p>High affinity for fatty tissues. (C)</p> Signup and view all the answers

What is the primary goal of 'scaling' a dataset?

<p>To standardize the values of different features to a specific range. (C)</p> Signup and view all the answers

Flashcards

3 Phases of Drug Action

The process by which a drug interacts with the body to produce its desired effect. It can be divided into three phases: Pharmacokinetic Phase - The movement of the drug through the body, Pharmacodynamic Phase - The interaction of the drug with its target site and Pharmacogenomic Phase - The influence of genetic variations on drug response.

Computer-Aided Drug Design (CADD)

A drug design approach that uses computer simulations and algorithms to predict the behavior and properties of drug molecules. It is divided into two main categories: Rational design and Reverse design. Rational design aims to find new drugs by studying the structure and function of a target molecule. Reverse design, on the other hand, starts with a known drug or a lead compound and tries to improve its efficacy or safety.

Drug Models (1D-4D)

Mathematical models that represent the structure of drugs. 1D-4D models represent drug information from simple linear properties (1D) to complex, multidimensional data (4D), including geometrical, electronic, and pharmacodynamic properties.

Molecular Surfaces

Representations of the 3D structure of molecules, commonly used in drug design. Different types of surfaces can be generated based on the molecule's properties, including:** Van der Waals surface: Represents the space occupied by atoms. Solvent-accessible surface: Encapsulates all points accessible by a solvent molecule. Molecular surface: Provides a representation of the molecule's shape and electrostatic potential.

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Receptor Theories in Molecular Modeling

Theories explaining how drugs bind to their targets (receptors) and elicit a response. In molecular modeling, lock and key and induced fit are two important theories. The Lock and Key model proposes that the drug fits perfectly into the receptor site like a key in a lock. Induced fit, on the other hand, suggests that both the drug and the receptor adjust their shapes upon binding.

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Agonist, Antagonist, Reverse Antagonist

Types of drug molecules that interact with receptors. Agonists activate the receptor and trigger a response. Antagonists bind to the receptor but block the action of other molecules. Reverse antagonists bind to the receptor and have an opposite effect compared to the agonist, effectively inactivating the receptor.

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Drug and Receptor Databases

Databases containing information about drug molecules and their receptors. Drug databases store chemical and physical data about drugs, while receptor databases store information about their structure, function, and interactions with drug molecules.

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Pharmacophore, 0D and 1D QSAR

A simplified representation of the key features of a molecule that determine its biological activity. 0D and 1D QSAR (Quantitative Structure-Activity Relationships) use simplified models to predict biological activity based on the chemical structure. 0D QSAR relies on molecular properties like size and hydrophobicity. 1D QSAR considers structural features like the number of atoms and bonds.

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Types of Molecular Surfaces

Representations of the 3D structure of molecules, commonly used in drug design. Different types of surfaces can be generated based on the molecule's properties, including Van der Waals surface (space occupied by atoms), Solvent-accessible surface (points accessible to a solvent molecule), and Molecular surface (shape and electrostatic potential of the molecule).

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Pharmacophore

A representation of the key features of a molecule that determine its biological activity. It helps understand how a molecule binds to a receptor and elicit a biological effect.

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Quantitative Structure-Activity Relationships (QSAR)

The study of how a drug's physical and chemical properties relate to its biological activity. It predicts a drug's activity by analyzing its structure.

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Drug Lipophilicity

A measure of how readily a molecule crosses cell membranes. It reflects the substance's affinity or attraction to fatty tissues.

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Partition Coefficient (P)

The ratio of a substance's concentration in an organic solvent to its concentration in water. It quantifies how well a molecule partitions between these phases.

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Lipophilicity Constant (logP)

A measure of a substance's hydrophobicity or affinity for lipids. It quantifies how well a molecule dissolves in a non-polar environment.

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Study Notes

Exam Topics

  • Practical Exam (7th Instructions):

    • Draw 2D drug models in ChemSketch
    • Create 3D drug models in ChemSketch
    • Calculate simple molecular descriptors in ChemSketch
    • Research databases for molecular descriptor values
    • Graph statistical data
    • Simple statistical calculations using spreadsheets (e.g., OpenOffice Calc)

  • Theoretical Exam (4 Lectures):

    • Three phases of drug action
    • Computer-aided drug design (RI and RD) directions
    • 1D to 4D drug models
    • Types of molecular surfaces
    • Receptor theories in modeling
    • Agonists, antagonists, reverse antagonists
    • Receptor and drug databases
    • Pharmacophore, OD, 1D-QSAR
    • Drug lipophilicity as a descriptor
    • Partition coefficient (P)
    • Lipophilicity constant
    • Constructing artificial neural networks
    • Types of neural networks
    • Supervised learning (delta rule)
    • Unsupervised learning (Hebb's rule)
    • Kohonen network characteristics
    • Telemedicine goals
    • Telecardiology implementation methods
    • Qualitative and quantitative data measurement scales in statistics
    • Population and statistical sample concepts
    • Representative sample characteristics
    • Measurement error types (accuracy vs. precision)
    • Case studies for measurement errors
    • Measures of central tendency (statistics) and their advantages/disadvantages
    • Dispersion measures (statistics) and their advantages/disadvantages
    • Data preprocessing techniques (scaling, centering, standardization)
    • Hypothesis testing steps in statistics
    • Arithmetic mean, weighted mean, mode, and median calculation
    • Comparing standard deviations across samples
    • Properties of normal distribution (3 sigma rule)
    • Confidence interval calculations for arithmetic mean
    • Student's t-distribution characteristics
    • Type I and II error characteristics
    • Statistical tests, calculations, and critical area specifications
    • Correlation coefficient value range and interpretation
    • Regression analysis basic methods

Practical Exam - Examples

  • Draw 2D and 3D models of Aspirin
  • Calculate logP for Aspirin
  • Calculate Euclidean distance between vectors
  • Calculate descriptive statistics (mean, median, standard deviation) for a given vector

Theoretical Exam - Examples

  • Describe the three phases of drug action
  • Define agonists, antagonists, and reverse antagonists
  • What's the difference between a supervised and unsupervised learning method?

Statistical Concepts

  • Correlation Coefficient: Value range and interpretation
  • Regression Analysis: Basic methods
  • Scales of Measurement: Nominal, ordinal, interval, ratio (e.g., military ranks: Nominal)
  • Data Distributions: Normal distribution characteristics (e.g., symmetry, tails, 3 sigma rule), comparison of distributions between sets (e.g., symmetric distributions, normal/bell-shaped densities.)
  • Measures of Central Tendency: Mean, median, mode
  • Measures of Dispersion: Standard deviation
  • Statistical tests, calculations, and critical areas specification

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