Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

750
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...
750
Proteomics01:33

Proteomics

9.8K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
9.8K
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.6K
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...
1.6K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.0K
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...
1.0K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.5K
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...
1.5K
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

329
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...
329

You might also read

Related Articles

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

Sort by
Same author

Complete enzyme clustering enhances coenzyme Q biosynthesis via substrate channeling.

Nature communications·2026
Same author

Investigating the relationship between ATP synthase and the TCA cycle by crosslinking mass spectrometry.

Nature communications·2026
Same author

Single-Ion Imaging Native Mass Spectrometry: Unraveling the Structural Features and Dissociation Energetics of Macromolecular Assemblies.

Journal of the American Society for Mass Spectrometry·2026
Same author

(Phospho)proteomic Profiling Reveals Mutation-Specific Adaptive Signaling to PI3Kα Inhibition in <i>PIK3CA</i> Mutant Breast Epithelial Cells.

Journal of proteome research·2026
Same author

Immunoglobulin sub-class levels define inter-donor plasma variability: a longitudinal dual-lab study.

Molecular systems biology·2026
Same author

Foamy microglia link oxylipins to disease progression in multiple sclerosis.

Nature neuroscience·2026
Same journal

Proteomic Profiling of Endothelial Cells Under Laminar Shear Stress Confirms the Importance of KLF4 in the Regulation of Membrane Protein Expression Compared to Oscillatory Flow.

Journal of proteome research·2026
Same journal

Identification of Age-Associated Circulating Proteins and Lipids in 3800 Comorbidity-Enriched Older Adults from Japan-Based Cohorts Using Olink Assays and MRM Mass Spectrometry.

Journal of proteome research·2026
Same journal

Molecular Solution to the Paradox of Ancient Brain Preservation.

Journal of proteome research·2026
Same journal

From Method-Defined Signals to Reference Measurement Procedures: Two Decades of Mass Spectrometry-Based ProGRP Quantification.

Journal of proteome research·2026
Same journal

Proteomic Profiling of Extracellular Vesicle-Enriched Plasma Using Mag-Net for Biomarker Discovery in Pancreatic Ductal Adenocarcinoma.

Journal of proteome research·2026
Same journal

Computationally Efficient Bayesian Estimation of Graphical Networks for Omics Data.

Journal of proteome research·2026
See all related articles

Related Experiment Video

Updated: Feb 1, 2026

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis
14:48

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

7.7K

PaDuA: A Python Library for High-Throughput (Phospho)proteomics Data Analysis.

Anna Ressa1, Martin Fitzpatrick1, Henk van den Toorn1

  • 1Biomolecular Mass Spectrometry and Proteomics Group, Utrecht Institute for Pharmaceutical Science and Bijvoet Center for Biomolecular Research , Utrecht University , Padualaan 8 , 3584 CH Utrecht , The Netherlands.

Journal of Proteome Research
|December 12, 2018
PubMed
Summary
This summary is machine-generated.

PaDuA is a new Python package for processing and analyzing mass spectrometry-based proteomics data. It offers standardized workflows to ensure reproducible results in biomedical research.

Keywords:
data analysishigh-throughputproteomicspython library

More Related Videos

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

972
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.6K

Related Experiment Videos

Last Updated: Feb 1, 2026

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis
14:48

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

7.7K
Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

972
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.6K

Area of Science:

  • Biomedical research
  • Proteomics
  • Bioinformatics

Background:

  • Mass spectrometry-based proteomics is increasingly used in biomedical research.
  • Large-scale proteomic data analysis presents significant challenges due to complexity.
  • Standardized workflows are crucial for reproducible proteomics analysis and data processing.

Purpose of the Study:

  • To develop a tool for standardized processing and analysis of (phospho)proteomics data.
  • To enhance reproducibility in large-scale proteomic data analysis.
  • To facilitate bioinformatics analysis for end-users and developers.

Main Methods:

  • Development of PaDuA, a Python package.
  • PaDuA offers tools for scripted workflows within Jupyter Notebooks.
  • Optimization for processing and analysis of (phospho)proteomics data.

Main Results:

  • PaDuA provides a collection of tools for proteomics data analysis.
  • The package facilitates the creation of automated, sharable, and reproducible workflows.
  • Enables easier bioinformatics analysis for a wider range of users.

Conclusions:

  • PaDuA addresses the challenges in analyzing complex quantitative proteomic data.
  • The package promotes standardized and reproducible proteomics research.
  • PaDuA supports both end-users and developers in bioinformatics analysis.