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Related Concept Videos

Heuristics01:21

Heuristics

Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
The Availability Heuristic01:08

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
Patch Clamp01:18

Patch Clamp

Many fundamental cell functions such as muscle contraction and nerve transmission rely on the electrical signals produced by the movement of positively and negatively charged ions across the cell membrane. One competent method to record current flowing across the whole cell or single ion channel is the patch-clamp technique.
In this method, a glass micropipette containing electrolyte solution is tightly sealed against a small portion of the cell membrane. As a result, a patch of the cell...
Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:

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Related Experiment Video

Updated: May 27, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Utility-aware screening with clique-oriented prioritization.

S Joshua Swamidass1, Bradley T Calhoun, Joshua A Bittker

  • 1Division of Laboratory and Genomic Medicine, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA. swamidass@wustl.edu

Journal of Chemical Information and Modeling
|November 29, 2011
PubMed
Summary
This summary is machine-generated.

Clique-Oriented Prioritization (COP) enhances drug discovery by prioritizing screening hits to maximize scaffold discovery. This utility-aware method improves the rate of finding valuable chemical scaffolds by over 3-fold compared to traditional approaches.

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Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish
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Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

Related Experiment Videos

Last Updated: May 27, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish
14:43

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

Area of Science:

  • Drug discovery and development
  • cheminformatics
  • computational chemistry

Background:

  • Traditional screening methods often treat all confirmed active compounds equally, aiming solely to maximize the number of hits.
  • This approach may not efficiently identify diverse and valuable chemical scaffolds.
  • Utility-aware methods incorporate user preferences to enhance information discovery.

Purpose of the Study:

  • To introduce and evaluate Clique-Oriented Prioritization (COP), a novel utility-aware method for prioritizing screening hits.
  • To maximize the discovery of scaffolds with multiple confirmed active compounds.
  • To improve the efficiency of identifying valuable chemical information from screening campaigns.

Main Methods:

  • COP extends an economic framework to prioritize confirmatory testing based on maximizing scaffolds with at least two confirmed actives.
  • The method was evaluated using retrospective and prospective experimental data.
  • Comparison with existing similarity-based methods like Ontology-Based Pattern Identification (OPI) and Local Hit-Rate Analysis (LHR).

Main Results:

  • COP accurately predicts the number of clique discoveries in confirmatory experiments.
  • COP improves the rate of scaffold discovery by over 3-fold.
  • Similarity-based methods like OPI and LHR were found to reduce scaffold discovery rates by approximately 50%.

Conclusions:

  • Clique-Oriented Prioritization (COP) significantly enhances the discovery of valuable chemical scaffolds in drug screening.
  • COP offers a more efficient strategy than traditional and other similarity-based methods for identifying diverse chemical matter.
  • The underlying utility-aware algorithm is versatile and can support various screener preference models.