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Related Concept Videos

Criticisms of the Evolutionary Perspective01:23

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In a study where individuals posing as strangers offered compliments and proposed casual sex to students, the responses differed significantly based on gender. Not a single woman accepted the proposal, while 70% of the men agreed. This outcome provides a useful scenario to explore through the lens of evolutionary psychology and social learning theory, highlighting the diverse perspectives on human sexual behaviors.
Evolutionary psychology provides one explanation for these findings, suggesting...
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Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...
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Updated: May 1, 2026

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
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Retrodiction in Evolutionary Genomics: A Philosophical Perspective.

Elliott Sober1,2

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Summary
This summary is machine-generated.

This study explores probability models in population genetics, showing Bayesian models can predict and retrodict. Information loss in causal chains can be mitigated by phylogenetic branching, illustrating Simpson

Keywords:
AICBayesianismEvolutionForward/backward directed probabilitiesFrequentismInformation theoryInstrumentalismLikelihoodModel selectionPredictionRetrodictionSimpson’s paradox

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Area of Science:

  • Theoretical Biology
  • Population Genetics
  • Information Theory

Background:

  • Traditional population genetics relied on forward-directed probability models.
  • Coalescent theory introduced backward-directed probabilities, enabling retrodiction.
  • A gap existed in models capable of both prediction and retrodiction.

Purpose of the Study:

  • To analyze the distinction between forward and backward-directed conditional probabilities.
  • To investigate the predictive and retrodictive capabilities of different probability models.
  • To explore information loss in causal chains and its modulation in phylogenetic trees.

Main Methods:

  • Analysis of conditional probabilities (forward-directed vs. backward-directed).
  • Examination of Bayesian models for dual predictive and retrodictive capacity.
  • Application of model selection theory and information theory theorems.
  • Investigation of information degradation in causal chains and phylogenetic branching.

Main Results:

  • Forward models predict, backward models retrodict; Bayesian models can do both.
  • Model selection theory challenges the assumption that true models are always superior.
  • Information degrades over time in causal chains, but branching in phylogenetic trees can mitigate this.
  • Separating within-lineage and across-lineage information loss exemplifies Simpson's paradox.

Conclusions:

  • Bayesian probability models offer a unified framework for prediction and retrodiction.
  • Phylogenetic branching structures can preserve information against temporal degradation.
  • Understanding Simpson's paradox is crucial for interpreting information loss in evolutionary lineages.