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Related Concept Videos

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

338
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
338
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

548
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
548
Coordination Compounds and Nomenclature02:54

Coordination Compounds and Nomenclature

26.9K
In most main group element compounds, the valence electrons of the isolated atoms combine to form chemical bonds that satisfy the octet rule. For instance, the four valence electrons of carbon overlap with electrons from four hydrogen atoms to form CH4. The one valence electron leaves sodium and adds to the seven valence electrons of chlorine to form the ionic formula unit NaCl (Figure 1a). Transition metals do not normally bond in this fashion. They primarily form coordinate covalent bonds, a...
26.9K
Coordination Number and Geometry02:57

Coordination Number and Geometry

19.1K
For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
19.1K
Lattice Centering and Coordination Number02:33

Lattice Centering and Coordination Number

12.2K
The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
Types of Unit Cells
Imagine taking a large number of identical...
12.2K
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

578
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

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Interactive and coordinated visualization approaches for biological data analysis.

António Cruz1, Joel P Arrais1, Penousal Machado1

  • 1Universidade de Coimbra Faculdade de Ciencias e Tecnologia, Departamento de Engenharia Informática.

Briefings in Bioinformatics
|March 29, 2018
PubMed
Summary
This summary is machine-generated.

Computational biology relies on data visualization tools to handle large, heterogeneous biological datasets. This survey explores graph-based and multiple-view approaches for analyzing complex data like gene expression and protein networks.

Keywords:
coordinated multiple viewsgene expressionmultivariate visualizationtime series data

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Data visualization

Background:

  • Increasing data volume and heterogeneity in biology necessitate advanced analysis tools.
  • Biological data often contains complex relationships and noise, challenging traditional analysis methods.
  • Existing visualization tools struggle with diverse data types and high dimensionality.

Purpose of the Study:

  • To survey visualization approaches for complex biological data analysis.
  • To highlight graph-based and coordinated multiple-view techniques.
  • To address current challenges in biological data visualization.

Main Methods:

  • Review of visualization techniques applied to biological data.
  • Focus on graph-based visualizations.
  • Emphasis on coordinated multiple-view methods for high-dimensional data.

Main Results:

  • Graph-based visualizations effectively represent biological networks.
  • Coordinated multiple views aid in exploring multivariate, high-dimensional data.
  • These methods facilitate the identification of hidden relationships in biological datasets.

Conclusions:

  • Visualization tools are crucial for modern computational biology.
  • Graph-based and multiple-view approaches offer powerful solutions for complex biological data.
  • Further development of these methods can enhance biological discovery.