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Related Concept Videos

What is Natural Selection?01:32

What is Natural Selection?

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Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
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Types of Selection01:46

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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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One of the unique features of tRNA is the presence of modified bases. In some tRNAs, modified bases account for nearly 20% of the total bases in the molecule. Altogether, these unusual bases protect the tRNA from enzymatic degradation by RNases.
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Related Experiment Video

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Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
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Samasy: an automated system for sample selection and robotic transfer.

Clinton L Cario1, John S Witte1,2

  • 1Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA.

Biotechniques
|November 28, 2018
PubMed
Summary
This summary is machine-generated.

Managing large sample collections for population studies is challenging. Samasy is a new web application that simplifies sample database construction, information display, and automated sample transfers, improving efficiency in high-throughput research.

Keywords:
96-well platelarge-scale genotypingsample managementsample transferweb interface

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Area of Science:

  • Bioinformatics
  • Laboratory Automation
  • Population Genomics

Background:

  • Increasing scale of population studies necessitates advanced sample management solutions.
  • Traditional 96-well plate formats are becoming insufficient for large-scale, high-throughput projects.
  • Efficient sample tracking and transfer are critical for data integrity and research reproducibility.

Purpose of the Study:

  • To introduce Samasy, a novel web-based application for managing large sample collections.
  • To provide an intuitive platform for sample database construction and information visualization.
  • To enable automated sample transfer and subsetting for high-throughput workflows.

Main Methods:

  • Development of a web-based application accessible via standard web browsers.
  • Implementation of a sample database for organizing sample and batch information.
  • Integration of features for automated sample transfer and subset selection.

Main Results:

  • Samasy facilitates the construction of comprehensive sample databases.
  • The application offers intuitive visualization of sample and batch data.
  • Automated sample transfer and subsetting capabilities are successfully implemented.
  • Samasy is designed for ease of use, rapid setup, and broad browser compatibility.

Conclusions:

  • Samasy offers a user-friendly and efficient solution for sample automation and management in large-scale research.
  • The application addresses the limitations of traditional formats in high-throughput population studies.
  • Samasy enhances sample management workflows, supporting the growing demands of modern biological research.