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Calculus offers essential techniques for businesses seeking to optimize pricing strategies and revenue. In this case, a bakery wants to determine the ideal price and daily sales volume to maximize revenue. By modeling how changes in price affect demand and revenue, the bakery can apply calculus to make data-driven decisions.The demand function relates the price per cupcake to the number of cupcakes sold and captures how lower prices increase sales. Based on market data, the demand function can...
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Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis
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iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data.

Steven Xijin Ge1, Eun Wo Son2, Runan Yao2

  • 1Department of Mathematics and Statistics, South Dakota State University, Box 2225, Brookings, SD, 57007, USA. gexijin@gmail.com.

BMC Bioinformatics
|December 21, 2018
PubMed
Summary

This study introduces iDEP, an integrated Differential Expression and Pathway analysis web application that simplifies transcriptomic data analysis for biologists. iDEP streamlines complex bioinformatics tasks, enabling easier interpretation of gene expression and pathway insights.

Keywords:
BioinformaticsDifferential gene expression, pathway analysisRNA-seqWeb application

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • RNA sequencing (RNA-seq) is a powerful tool for transcriptomic profiling.
  • Bioinformatic analysis of RNA-seq data is often complex and time-consuming for biologists.
  • There is a need for user-friendly tools to simplify RNA-seq data analysis.

Purpose of the Study:

  • To develop a user-friendly, interactive web application for streamlining transcriptomic data analysis.
  • To facilitate exploratory data analysis, differential gene expression, and pathway analysis.
  • To enable biologists to easily translate transcriptomic and proteomic data into actionable insights.

Main Methods:

  • Development of the iDEP (integrated Differential Expression and Pathway analysis) web application.
  • Integration of 63 R/Bioconductor packages, 2 web services, and extensive annotation/pathway databases.
  • Customizable R code and pathway files for workflow reproducibility.

Main Results:

  • iDEP supports 220 plant and animal species.
  • Analysis of lung fibroblast RNA-seq data revealed roles of SP1, E2F1, and microRNAs in cell cycle regulation.
  • Analysis of mouse B cells demonstrated p53's role in apoptosis and DNA repair, contrasting with MYC and E2F1 pathway activation in p53-deficient cells.

Conclusions:

  • iDEP integrates comprehensive analytical functionalities with extensive annotation databases.
  • The application empowers biologists to readily interpret transcriptomic and proteomic data.
  • iDEP facilitates the generation of novel, testable hypotheses from complex biological datasets.