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Related Concept Videos

Mutations01:35

Mutations

Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
Mutations01:39

Mutations

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Mutations01:39

Mutations

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Mutations in Microorganisms01:18

Mutations in Microorganisms

Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
Mismatch Repair01:20

Mismatch Repair

Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
Mismatch Repair01:36

Mismatch Repair

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Algorithms and semantic infrastructure for mutation impact extraction and grounding.

Jonas B Laurila1, Nona Naderi, René Witte

  • 1Department of Computer Science & Applied Statistics, University of New Brunswick, Saint John, New Brunswick, Canada. j02h9@unb.ca

BMC Genomics
|December 15, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel rule-based system for extracting protein mutation impacts from scientific literature. The system categorizes impacts as positive, negative, or neutral, improving data accessibility for researchers.

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Computational Biology

Background:

  • Automated extraction of protein mutation impacts from scientific literature remains a significant challenge.
  • Existing phenotype-prediction systems rely on manually curated databases, limiting their scope and accessibility.
  • Unstructured data on protein mutations and their effects hinders progress in protein engineering and systems biology.

Purpose of the Study:

  • To develop the first rule-based approach for extracting mutation impacts on protein properties, including directionality (positive, negative, neutral).
  • To ground protein and mutation mentions to UniProtKB IDs and map protein properties to Gene Ontology concepts.
  • To create a queryable Mutation Impact ontology and provide programmatic data access via semantic web services.

Main Methods:

  • Developed a rule-based system for mutation impact extraction and directionality categorization.
  • Implemented entity grounding to UniProtKB IDs and Gene Ontology concepts.
  • Constructed an OWL-DL Mutation Impact ontology and utilized SPARQL for querying.
  • Integrated Semantic Automated Discovery and Integration (SADI) framework for web services.

Main Results:

  • Successfully extracted mutation impacts with directionality (positive, negative, neutral).
  • Achieved high precision and recall for Mutation Grounding.
  • Demonstrated retrieval of proteins and mutant sequences based on impact direction and properties.
  • Established programmatic access to mutation impact data.

Conclusions:

  • The novel mutation impact extraction methods address the challenge of accessing unstructured legacy data.
  • The system achieves state-of-the-art performance for Mutation Grounding and respectable precision for Mutant-Impact relation extraction.
  • The deployed system leverages text mining and semantic web technologies for broad consumer access.