Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pivot Bearings

Pivot Bearings

In mechanical systems, bearings are crucial in facilitating relative motion between two components while minimizing friction and wear. They help distribute various loads (radial, axial or a combination of both loads) across machinery parts, ensuring smooth and efficient operation.
A pivot bearing is a specialized type of bearing designed to support axial loads on a rotating shaft. The bearing surface, or the pivot, is positioned at the end of a shaft to support the axial thrust. The pivot may...

Analysis of Population Pharmacokinetic Data

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...

Overview of Microsoft Excel as a Data Analysis Tool

Overview of Microsoft Excel as a Data Analysis Tool

Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...

Performing a Simple Data Analysis using MS-Excel Function

Performing a Simple Data Analysis using MS-Excel Function

Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro.

bioRxiv : the preprint server for biology·2026

Same author

Single-cell Transcriptomic Variance Analysis Reveals Intercellular Circadian Desynchrony in the Alzheimer's Affected Human Brain.

bioRxiv : the preprint server for biology·2026

Same author

Interpretable Semi-federated Learning for Multimodal Cardiac Imaging and Risk Stratification: A Privacy-Preserving Framework.

Journal of imaging informatics in medicine·2025

Same author

Antitumor effects and mechanisms of traditional Chinese medicine gamboge: A review.

Frontiers in pharmacology·2025

Same author

Controlling nephron precursor differentiation to generate proximal-biased kidney organoids with emerging maturity.

Nature communications·2025

Same author

Guiqi Yishen granule alleviates obstructive nephropathy-induced renal fibrosis by targeting PI3K/AKT signaling pathway.

Journal of ethnopharmacology·2025

Same journal

Model-based quantification of protein-protein interaction aberrations for exploring dysregulated signalling pathways through pathway maps and gene expression levels.

BMC bioinformatics·2026

Same journal

Research on multi-trait genome association study method based on Shannon information entropy.

BMC bioinformatics·2026

Same journal

A multi-view feature fusion framework with interpretable graph convolution for predicting microbe-drug associations.

BMC bioinformatics·2026

Same journal

Covariance decomposition for distance based species tree estimation.

BMC bioinformatics·2026

Same journal

SNPio: a Python interface for population genomic data processing.

BMC bioinformatics·2026

Same journal

SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.

BMC bioinformatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 16, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

PIVOT: platform for interactive analysis and visualization of transcriptomics data.

Qin Zhu¹, Stephen A Fisher², Hannah Dueck²

¹Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.

BMC Bioinformatics

|January 7, 2018

Summary

This summary is machine-generated.

PIVOT is a new R-based platform simplifying transcriptome analysis for researchers. It offers a user-friendly interface and graphical data management for interactive exploration of transcriptomics data, making complex analyses accessible.

Keywords:

Exploratory data analysis Graphical user interface Interactive visualization Transcriptomics

More Related Videos

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

Related Experiment Videos

Last Updated: Feb 16, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Existing R packages for transcriptome analysis often require programming expertise.
Integrating results from diverse R packages necessitates complex scripting for data type management.
Tracking derived datasets from exploratory analyses, such as subsets or transformations, is challenging.

Purpose of the Study:

To introduce PIVOT, an R-based platform designed to democratize transcriptome analysis.
To provide a uniform user interface and graphical data management for interactive exploration of transcriptomics data.
To enable researchers without extensive programming skills to utilize sophisticated analysis tools.

Main Methods:

PIVOT integrates over 40 popular open-source transcriptome analysis packages.
It features a uniform user interface and graphical data management for intuitive interaction.
A graph-based visual interface tracks relationships between derived datasets, aiding data version control.

Main Results:

PIVOT offers a unified platform for accessing and executing numerous transcriptome analysis tools.
The graphical interface facilitates interactive exploration and management of transcriptomics datasets.
Features include automatic report generation, publication-quality plots, and saving/sharing of analysis states for reproducibility.

Conclusions:

PIVOT empowers researchers across various backgrounds to perform advanced transcriptome analysis.
The platform enhances the accessibility and reproducibility of transcriptomics data exploration.
It bridges the gap between complex bioinformatics tools and researchers with limited programming experience.