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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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Screening Peptides that Activate MRGPRX2 using Engineered HEK Cells
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Published on: November 6, 2021

FrameDP: sensitive peptide detection on noisy matured sequences.

Jérôme Gouzy1, Sébastien Carrere, Thomas Schiex

  • 1Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France.

Bioinformatics (Oxford, England)
|January 21, 2009
PubMed
Summary
This summary is machine-generated.

FrameDP is a new pipeline that predicts protein-coding regions in transcripts. This tool adapts to various sequence qualities, aiding genome-wide studies and protein domain identification.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Transcriptome sequencing is crucial for genome-wide studies.
  • Accurate identification of protein-coding regions (CDS) is essential for downstream analysis.
  • New sequencing technologies are increasingly replacing array technology for expression analysis.

Purpose of the Study:

  • To present FrameDP, a novel pipeline for predicting CDS in transcripts.
  • To develop a tool that adapts to varying sequence qualities.
  • To facilitate systematic amino acid-level analysis and domain identification.

Main Methods:

  • FrameDP utilizes a self-training integrative approach.
  • The pipeline is designed to predict coding sequences (CDS) within transcript sequences.
  • It is adaptable to different levels of sequence quality.

Main Results:

  • FrameDP successfully predicts CDS in transcripts.
  • The pipeline demonstrates adaptability across diverse sequence qualities.
  • This facilitates more accurate protein-level analysis.

Conclusions:

  • Transcriptome sequencing is fundamental for genome-wide and expression analyses.
  • Protein-coding region identification is a prerequisite for amino acid-level analysis.
  • FrameDP is a valuable tool for predicting CDS, supporting advanced genomic research.