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

Fed-Batch Culture

Fed-Batch Culture

Fed-batch culture is a widely used bioprocessing strategy combining aspects of batch culture with controlled substrate feeding to optimize cell growth and product formation. In this semi-closed system, nutrients are strategically added during fermentation, while the accumulated products and biomass remain within the bioreactor until the end of the operation. This controlled addition of substrates allows for better management of growth kinetics, nutrient limitation, and metabolite...

You might also read

Related Articles

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

Sort by

Same author

AGR2-high cells drive a FOXM1-mediated pro-malignancy program in non-functional pancreatic neuroendocrine tumors (NF-PanNETs) and informatively predict patient outcomes.

Science bulletin·2026

Same author

Spatial distribution of the proteome in the human body and in cancers.

Nature·2026

Same author

Methodological comparison of capillary and venous blood parameters in pediatric <i>Mycoplasma pneumoniae</i> pneumonia: a prospective study with exploratory machine learning assessment.

Translational pediatrics·2026

Same author

A k-mer-based genome-wide association study approach empowering gene mining in polyploids.

Nature genetics·2026

Same author

Hierarchical Amplification-Interlinked CRISPR-Cas14a Luminescent Biosensor Coupled with Portable Photonic Crystal Biochip-Boosted Time-Delayed Signaling for the Diagnosis of Pediatric <i>Mycoplasma pneumoniae</i> Pneumonia.

Analytical chemistry·2026

Same author

Insight of immune checkpoint blockades in melanoma: mechanism and clinical translation.

Molecular cancer·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

Same journal

Hierarchy of MS-Based Evidence.

Journal of proteome research·2026

Same journal

Proteomic Profiling of Exosomes from HPV-Positive and HPV-Negative Head and Neck Squamous Cell Carcinoma: Selective Cargo Packaging.

Journal of proteome research·2026

Same journal

Proteomic Analysis Identifies ATE1-Dependent Arginylation Dysregulation across Meningioma Grades.

Journal of proteome research·2026

Same journal

Proteomic Impact of Peripheral Expression of Mutant Huntingtin in <i>C. elegans</i>.

Journal of proteome research·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 17, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

BatchServer: A Web Server for Batch Effect Evaluation, Visualization, and Correction.

Tiansheng Zhu^1,2,3,4, Rui Sun^2,3,4, Fangfei Zhang^2,3,4

¹Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, 200438 Shanghai, China.

Journal of Proteome Research

|December 18, 2020

Summary

This summary is machine-generated.

BatchServer is a new R/Shiny web platform that helps researchers evaluate and correct batch effects in omics data. It uses autoComBat, PVCA, and UMAP for improved data analysis and reliability.

Keywords:

ComBat batch effects bioinformatics data preprocess

More Related Videos

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Related Experiment Videos

Last Updated: Jun 17, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Area of Science:

Bioinformatics
Computational Biology
Data Science

Background:

Batch effects are common in omics data, introducing unwanted variations that can bias analysis.
Accurate evaluation and correction of batch effects are crucial for reliable omics data interpretation.

Purpose of the Study:

To introduce BatchServer, a user-friendly R/Shiny web platform for interactive batch effect analysis.
To provide a tool that facilitates both the evaluation and correction of batch effects in omics datasets.

Main Methods:

BatchServer integrates Principal Variance Component Analysis (PVCA) and Uniform Manifold Approximation and Projection (UMAP) for batch effect evaluation and visualization.
It features autoComBat, a modified version of the widely used ComBat tool, for batch effect correction.

Main Results:

The platform demonstrates effective application in analyzing multiple proteomics and transcriptomic datasets.
BatchServer provides an interactive graphical interface for streamlined batch effect assessment.

Conclusions:

BatchServer offers a valuable, open-source solution for addressing batch effects in omics data analysis.
The tool enhances the reliability and accuracy of omics data interpretation through effective batch effect management.