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Related Concept Videos

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...

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Related Experiment Video

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A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae
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A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Published on: April 25, 2015

FunSys: Software for functional analysis of prokaryotic transcriptome and proteome.

Pablo de Sá, Anne Pinto, Rommel Thiago Jucá Ramos

    Bioinformation
    |July 26, 2012
    PubMed
    Summary

    This study introduces FunSys, a new computational tool for analyzing RNA sequencing and proteomics data. FunSys helps researchers understand gene and protein expression patterns for heredity research.

    Keywords:
    BioinformaticsGene expressionNext-generation sequencingSoftware

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    Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
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    Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

    Published on: January 13, 2016

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Next-generation sequencing (NGS) generates vast amounts of data.
    • Understanding biological macromolecules involved in heredity requires advanced computational tools.
    • Existing tools may not adequately correlate differential expression patterns from diverse datasets.

    Purpose of the Study:

    • To develop a user-friendly computational tool, FunSys.
    • To enable evaluation and correlation of differential expression from RNA sequencing and proteomics data.
    • To aid in the interpretation of complex biological data.

    Main Methods:

    • Development of a stand-alone program named FunSys.
    • Implementation of a user-friendly interface for data analysis.
    • Integration of RNA sequencing and proteomics dataset analysis.

    Main Results:

    • FunSys facilitates the evaluation of differential expression patterns.
    • The tool correlates findings between RNA sequencing and proteomics datasets.
    • FunSys generates interpretable charts and reports.

    Conclusions:

    • FunSys provides a valuable resource for analyzing high-throughput sequencing and proteomics data.
    • The tool aids researchers in understanding the functions of biological macromolecules.
    • FunSys supports the interpretation of differential expression analysis in heredity research.