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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Horizontal gene transfer (HGT) is a process where genetic material moves between organisms within the same generation, unlike vertical gene transfer, which occurs from parent to offspring. HGT plays a crucial role in microbial evolution, adaptation, and survival, particularly in shared environments like the human gut.Mobile genetic elements such as plasmids, prophages, integrons, insertion sequences, and transposons facilitate this process. HGT occurs through three primary mechanisms:...
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Types of Genetic Transfer Between Organisms02:18

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Genetic transfer occurs when genetic information is passed from one organism to another. It occurs via two mechanisms: vertical gene transfer and horizontal gene transfer. Vertical gene transfer occurs when genetic information is transferred from one generation to the next, which happens much more frequently than horizontal gene transfer. Both sexual and asexual reproduction are forms of vertical gene transfer, where one or more organisms pass some or all of their genome onto their progeny.
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Mutation, Gene Flow, and Genetic Drift01:09

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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Related Experiment Video

Updated: Sep 26, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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The structural shift and collaboration capacity in GenBank Networks: A longitudinal study.

Jian Qin1, Jeff Hemsley1, Sarah E Bratt1

  • 1School of Information Studies, Syracuse University, Syracuse, NY.

Quantitative Science Studies
|April 18, 2022
PubMed
Summary
This summary is machine-generated.

Analyzing GenBank metadata reveals evolving scientific collaboration networks. This study identifies a trend towards flatter network structures and optimal conditions for enhancing research collaboration capacity.

Keywords:
GenBank metadata analysiscollaboration capacitycollaboration networksimpact assessmentlongitudinal study of collaboration networks

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Area of Science:

  • Bibliometrics and Scientometrics
  • Network Science
  • Bioinformatics and Data Science

Background:

  • Scientific collaboration networks are crucial for research advancement.
  • Publication-based analysis has limitations in capturing full collaboration dynamics.
  • Metadata in scientific data repositories offers a complementary data source.

Purpose of the Study:

  • To analyze the structures and dynamics of GenBank collaboration networks (1992-2018).
  • To identify trends in collaboration network evolution.
  • To develop new metrics for assessing collaboration enablers.

Main Methods:

  • Utilized network science methodologies on GenBank metadata.
  • Conducted longitudinal analysis of large-scale data from 1992 to 2018.
  • Incorporated metadata from both data production and publication stages.

Main Results:

  • Uncovered the historical evolution of GenBank collaboration networks.
  • Identified a trend of flattening network structures over time.
  • Determined the optimal assortative mixing range for enhanced collaboration capacity.

Conclusions:

  • GenBank metadata provides novel insights into scientific collaboration beyond publication data.
  • Collaboration networks exhibit evolving structures and require adaptive strategies.
  • New metrics can effectively assess the impact of human capital, cyberinfrastructure, and science policy on collaboration.