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Related Concept Videos

Transcription01:10

Transcription

155.8K
Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds...
155.8K
Eukaryotic Transcription Inhibitors01:52

Eukaryotic Transcription Inhibitors

10.9K
Certain biochemical processes, such as embryonic development and cell growth regulation, depend on the repression of specific genes. DNA binding proteins known as eukaryotic transcription inhibitors regulate the repression of gene expression in eukaryotes. The presence of these inhibitors at the required location and time in the cell is triggered by the presence of hormones and additional signals from other cells.
Eukaryotic transcription inhibitors usually contain two distinct domains, a...
10.9K
Transcription Factors02:16

Transcription Factors

82.3K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
82.3K
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

403
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
403
Master Transcription Regulators02:23

Master Transcription Regulators

7.7K
Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
7.7K
Eukaryotic Transcription Activators02:42

Eukaryotic Transcription Activators

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Transcription activators are proteins that promote the transcription of genes from DNA to RNA. In most cases, these proteins contain two separate domains ‒ a domain that binds to DNA and a domain for activating transcription; however, in some cases, a single domain is responsible for both binding and activation of transcription, as seen in the glucocorticoid receptor and MyoD.
The binding domains are capable of recognizing and interacting with regulatory sequences on the DNA. These...
12.6K

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QuaPra: Efficient transcript assembly and quantification using quadratic programming with Apriori algorithm.

Xiangjun Ji1, Weida Tong2, Baitang Ning2

  • 1The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.

Science China. Life Sciences
|May 25, 2019
PubMed
Summary
This summary is machine-generated.

RNA sequencing (RNA-seq) analysis benefits from QuaPra, a new tool for transcriptome assembly and quantification. QuaPra improves transcript detection and accuracy, especially for low abundance transcripts.

Keywords:
RNA-Seqtranscript assemblytranscript quantificationtranscriptome reconstruction

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA sequencing (RNA-seq) is crucial for transcriptome exploration but faces challenges in reconstruction.
  • Current tools and sequencing technologies have limitations impacting transcriptome assembly accuracy.

Purpose of the Study:

  • Introduce QuaPra (Quadratic Programming combined with Apriori), an efficient tool for accurate transcriptome assembly and quantification.
  • Improve the detection and accuracy of low abundance transcripts.

Main Methods:

  • Developed QuaPra, integrating Quadratic Programming and Apriori algorithms.
  • Evaluated QuaPra's performance on simulated and real RNA-seq data.
  • Compared QuaPra against other popular transcriptome assembly tools.

Main Results:

  • QuaPra detected at least 26.5% more low abundance transcripts (0.1-1 FPKM) on simulated data.
  • Achieved over 2.1% increase in sensitivity and precision for low abundance transcripts.
  • Correctly assembled approximately 25% more known transcripts compared to other assemblers on real data.

Conclusions:

  • QuaPra offers enhanced accuracy and sensitivity for transcriptome assembly and quantification.
  • The tool is particularly effective in identifying low abundance transcripts.
  • QuaPra represents a significant advancement for transcriptome analysis.