Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

DNA Mapping Algorithms: Strategies for Single Restriction Enzyme and Multiple Restriction Enzyme Mapping

Authors: Gillett, Will;

DNA Mapping Algorithms: Strategies for Single Restriction Enzyme and Multiple Restriction Enzyme Mapping

Abstract

An approach to high-resolution restriction-fragment DNA mapping, known as Multiple-Restriction-Enzyme mapping (MRE mapping), is present. This approach significantly reduces the uncertainty of clone placement by using clone ends to synchronize the position in of clones within different maps, each map being constructed from fragment-length data produced by digestion of each clone with a specific restriction enzyme. Maps containing both fragments-length data and clone-end data are maintained for each restriction enzyme, and synchronization between two such maps is achieved by requiring them to have "compatible" clone-end map projections. Basic definitions of different kinds of maps, such as restriction sites maps, restriction fragment maps and clone end maps, are presented. Several specifications notations, such as sequence-set notation and sequence-set-tree notation, for describing the structure of these maps, are defined. Basic concepts, such as the match/merge approach to map incorporation, extension vs. assimilation and ambiguity, are exposed. Supporting techniques, such as window sizing, window placement, and ambiguity resolution, are also discussed. A mathematical analysis of how MRE mapping effects false positives and false negatives is presented. For concreteness, MRE mapping is presented using a specific methodological framework. However, many of the concepts and techniques have a wider range of use than just high-resolution restriction-fragment mapping.

Related Organizations
Keywords

Computer Sciences, Computer Engineering

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!