Gene prediction and annotation Flashcards

1
Q

Identification of genes

A
  • Prokaryote
    • generally easy
    • sequence without interruptions
  • Eukaryotes
    • more difficult (exons are divided)
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2
Q

What is gene prediction?

A
  • the identification of genetic elements in a genomic sequence
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3
Q

How is gene prediction done?

A
  • de-novo predictions
    • training set
  • evidence Based
    • EST, Proteins, RNAseq
  • comparatve genomics
    • other genomes
    • useful in the discovery of functionally relevant regions
  • combiner
    • training set
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4
Q

GBROWSE

A
  • tool for the visualization of genetic annotations
    • based on a relational database
  • helps in the understanding of the predictions
    • de novo prediction using different predictors: many false positives
    • alignment of EST and proteins: very good but not all genes are covered
    • objects in the Gbrowser can be linked to the annotation platform
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5
Q

Genetic annotations

A
  • process of identifying the locations of genes and all of the coding regions in a genome and determining what those genes do
  • is a note added as a commentary
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6
Q

Functional annotation

A
  • process of attaching biological information to sequences of genes or proteins
  • two methods
    • Automatic annotation
      • relatively fast
      • generally inferred from sequence similarity
      • useful as starting point
    • Manual annotation
      • requires experts
      • long process
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7
Q

Gene ontology

A
  • controlled, structured and dynamic dictionary of biological processes, molecular functions and cellular components
    • can be applied to all organisms
  • tool for the unification of biology
  • easier comparison among different species
  • annotations have evidence codes
    • information about the evidence from which the annotation has been made.
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8
Q

Gene ontology typer of annotations?

A
  • electronic annotation
    • relatively quick
    • large number of annotations
    • sequence similarity and mapping
    • useful for not well known genomes
  • manual annotation
    • high-quality annotation
    • expert biologists needed
    • time consuming
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9
Q

Markov chains

A
  • predicting events
    • stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event
  • can predict whether a certain text belongs to one language or another
    • can be used to detect signatures in DNA and amino acid sequences
    • discriminate between coding and non-coding regions (de novo)
  • Hidden Markov Models (HMM) states are not directly visible
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