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In eukaryotic cells, DNA replication is highly conserved and tightly regulated. Multiple linear chromosomes must be duplicated with high fidelity before cell division, so there are many proteins that fulfill specialized roles in the replication process. Replication occurs in three phases: initiation, elongation, and termination, and ends with two complete sets of chromosomes in the nucleus.
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Replication data collection highlights value in diversity of replication attempts.

K Andrew DeSoto1, Martin Schweinsberg2

  • 1Association for Psychological Science, 1800 Massachusetts Ave NW, Ste 402, Washington, District Of Columbia 20036-1218, USA.

Scientific Data
|March 15, 2017
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Summary
This summary is machine-generated.

This collection presents data from attempts to replicate previous research, highlighting diverse methods and challenges in scientific replication. The data is shared to aid future research and educate scientists on replication practices.

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Area of Science:

  • Scientific methodology
  • Data science

Background:

  • Replicability and reproducibility are fundamental to scientific integrity.
  • Previous research often lacks openly available replication data.

Purpose of the Study:

  • To present a collection of data descriptors from scientific replication attempts.
  • To showcase diverse methodologies and outcomes of replication studies.
  • To encourage the reuse of replication data and serve as educational resources.

Main Methods:

  • Data was collected during attempts to replicate previously published research.
  • Replication efforts included both published and unpublished projects.
  • Data Descriptors were published in Scientific Data to document these efforts.

Main Results:

  • The collection includes data from various scientific replication projects.
  • The papers highlight different approaches to conducting scientific replications.
  • Both the benefits and challenges of replication research are revealed.

Conclusions:

  • The published replication data offers valuable resources for the scientific community.
  • Encouraging data reuse can advance scientific understanding.
  • These examples serve as crucial educational tools for learning about scientific replication.