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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...

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Related Experiment Video

Updated: May 11, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Textrous!: extracting semantic textual meaning from gene sets.

Hongyu Chen1, Bronwen Martin, Caitlin M Daimon

  • 1Receptor Pharmacology Unit, Laboratory of Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America.

Plos One
|May 7, 2013
PubMed
Summary

Textrous! extracts biomedical meaning from gene sets using natural language processing. This tool enhances interpretation of genomic data by linking genes to scientific literature, improving biological discovery.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Interpreting large gene sets from genomic experiments is vital for understanding biological themes and guiding future research.
  • Current tools often rely on limited vocabularies or simple text searches, failing to capture indirect relationships in scientific literature.

Purpose of the Study:

  • To develop Textrous!, a novel web-based framework for extracting biomedical semantic meaning from gene sets.
  • To improve the interpretation of genomic data by identifying meaningful textual associations within scientific literature.

Main Methods:

  • Utilizes natural language processing techniques such as latent semantic indexing (LSI), sentence splitting, and noun-phrase chunking.
  • Mines data from MEDLINE abstracts, PubMed Central, Online Mendelian Inheritance in Man (OMIM), and Mammalian Phenotype annotations.
  • Employs collective and individual text extraction methodologies for ranking, clustering, and visualization of textual data.

Main Results:

  • Textrous! generates meaningful output even with small gene sets.
  • The framework effectively extracts and presents semantically relevant words and phrases linked to genomic data.
  • Provides both individual and batch gene analysis capabilities.

Conclusions:

  • Textrous! offers an improved approach to deriving biomedical insights from gene sets compared to existing tools.
  • Facilitates the discovery of quantitatively significant and easily appreciable semantic links within scientific literature.
  • Supports the unbiased and reproducible interpretation of high-content gene sets for biological research.