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Related Concept Videos

Entropy02:39

Entropy

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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
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Standard Entropy Change for a Reaction03:00

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Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
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Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
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Spearman's Rank Correlation Test01:20

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Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
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Entropy and Solvation02:05

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The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
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Identifying Drug Resistant miRNAs Using Entropy Based Ranking.

Jayanta Kumar Pal, Shubhra Sankar Ray, Sankar K Pal

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    A new method, Set Partitioning Entropy Measure (SPEM), identifies cancer drug-resistant microRNAs. Focusing on the top 1% of these microRNAs significantly improves treatment classification accuracy.

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    Area of Science:

    • Biochemistry
    • Bioinformatics
    • Computational Biology

    Background:

    • MicroRNAs regulate drug sensitivity and resistance in cancer.
    • Identifying specific microRNAs linked to drug resistance is crucial for improving cancer treatment efficacy.

    Purpose of the Study:

    • To introduce a novel set theoretic entropy measure (SPEM) for assessing microRNA relevance and confidence in determining drug resistance.
    • To develop a method for identifying key drug-resistant microRNAs in cancer.

    Main Methods:

    • A new measure, granular probability, was defined to determine the confidence level of membership values.
    • Granules were computed using a histogram-based method with automatically determined bin widths and numbers.
    • SPEM was calculated using pairs of fuzzy and crisp membership values along with their confidence levels.

    Main Results:

    • SPEM demonstrated efficiency across six datasets.
    • Using all microRNAs with an SVM classifier yielded an F-score between 0.31 and 0.50.
    • Utilizing only the top 1% of drug-resistant microRNAs identified by SPEM improved the F-score to a range of 0.67 to 0.94.

    Conclusions:

    • The proposed SPEM method significantly enhances the accuracy of classifying sensitive and resistant cancer samples.
    • The identified top 1% of microRNAs are biologically significant and crucial for understanding cancer drug resistance.