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

Proteomics01:33

Proteomics

9.0K
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...
9.0K
Genomics02:02

Genomics

39.2K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
39.2K

You might also read

Related Articles

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

Sort by
Same author

"Dual-Boosting" Strategy to Enhance Radical Generation of Photosensitizer for Mitochondria-Targeted Phototherapy.

Research (Washington, D.C.)·2026
Same author

Dynamic Manipulation Skill Learning for Tactile Myoelectric Prosthetic Hands in Tool Handling.

Cyborg and bionic systems (Washington, D.C.)·2026
Same author

A Multi-Scenario Coupled Simulation of Diet-Land Systems: Diet-Land Supply-Demand Matching and Responses from the Historical-to-Future.

Foods (Basel, Switzerland)·2026
Same author

SPD-DANN: An SPD manifold unsupervised domain adaptation method for cross subject motor imagery EEG decoding.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Updated subnational estimates of Water, Sanitation and Hygiene access in Low- and Middle-Income countries: a spatially referenced hierarchical ordinal multinomial modeling analysis using R template model builder.

Research square·2026
Same author

Trends and future of the disease burden of malignant neoplasms of bone and articular cartilage in China from 1990 to 2023: An analysis based on the Global Burden of Disease 2023.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology·2026

Related Experiment Video

Updated: Dec 9, 2025

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
09:52

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

Published on: January 10, 2025

1.0K

Managing a Large-Scale Multiomics Project: A Team Science Case Study in Proteogenomics.

Paul A Stewart1, Eric A Welsh1, Bin Fang1

  • 1H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.

Methods in Molecular Biology (Clifton, N.J.)
|September 14, 2020
PubMed
Summary

This study outlines key steps for successful large-scale proteogenomics projects, emphasizing collaborative planning and rigorous testing. It provides guidelines for developing complex multiomics research, from experimental design to data integration.

Keywords:
Big dataBiostatisticsCancerExperimental designInformaticsLandscape paperPlanningProteogenomics

More Related Videos

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

3.5K
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

578

Related Experiment Videos

Last Updated: Dec 9, 2025

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
09:52

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

Published on: January 10, 2025

1.0K
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

3.5K
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

578

Area of Science:

  • Multiomics research
  • Proteogenomics
  • Big data in science

Background:

  • Large-scale scientific projects require scientists to expand expertise beyond their usual scope.
  • Success in big data projects hinges on meticulous planning across experimental design, data acquisition, and analysis.
  • Effective collaboration and communication are crucial for managing complex, multi-disciplinary research endeavors.

Purpose of the Study:

  • To provide guidelines for developing large-scale multiomics projects.
  • To share lessons learned from a proteogenomics project.
  • To support scientists undertaking complex, data-intensive research.

Main Methods:

  • Defined hypotheses and identified suitable clinical cohorts.
  • Conducted pilot projects to assess feasibility and refine experimental designs.
  • Facilitated extensive team discussions for project guidance and communication.

Main Results:

  • A comprehensive framework for planning and executing large-scale proteogenomics studies was developed.
  • Identified critical components for success, including experimental design, data handling, and interdisciplinary collaboration.
  • Demonstrated the feasibility of integrating diverse data types in a proteogenomics context.

Conclusions:

  • Successful large-scale multiomics projects depend on careful planning, pilot studies, and continuous team communication.
  • The described proteogenomics project serves as a model for future big data research initiatives.
  • Guidelines are provided to aid researchers in navigating the complexities of multiomics project development.