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

9.4K
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...
9.4K
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

1.9K
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
1.9K
Qualitative Analysis03:46

Qualitative Analysis

23.8K
For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...
23.8K
Dimensional Analysis03:40

Dimensional Analysis

60.6K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
60.6K
Dimensional Analysis01:27

Dimensional Analysis

654
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
654
Pedigree Analysis01:35

Pedigree Analysis

89.0K
Overview
89.0K

You might also read

Related Articles

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

Sort by
Same author

The spatial proteome of the Plasmodium falciparum schizont illuminates the composition and evolutionary trajectories of its organelles.

Nature communications·2026
Same author

Annealed variational mixtures for disease subtyping and biomarker discovery.

Statistical applications in genetics and molecular biology·2026
Same author

Dynamic subcellular proteomics identifies regulators of adipocyte insulin action.

Nature communications·2026
Same author

Subcellular localization as a driver of protein function.

Nature reviews. Molecular cell biology·2026
Same author

Functional characterisation of tumour suppressor PDCD4 reveals previously undisclosed role in the control of cell adhesion.

Nucleic acids research·2026
Same author

Semi-supervised Bayesian integration of multiple spatial proteomics datasets.

PLoS computational biology·2025

Related Experiment Video

Updated: Jan 24, 2026

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
14:51

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Published on: November 13, 2021

6.1K

A Bioconductor workflow for the Bayesian analysis of spatial proteomics.

Oliver M Crook1,2, Lisa M Breckels1, Kathryn S Lilley1

  • 1Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK.

F1000Research
|May 24, 2019
PubMed
Summary

This study introduces pRoloc for Bayesian analysis of spatial proteomics data, enabling researchers to understand protein function through subcellular localization. The workflow provides a comprehensive guide for data analysis and interpretation.

Keywords:
BayesianBioconductormachine learningpRolocpRolocdataproteomicssoftwarespatial proteomics

More Related Videos

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules
07:35

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules

Published on: December 16, 2021

2.8K
"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome
06:31

"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome

Published on: March 24, 2023

3.1K

Related Experiment Videos

Last Updated: Jan 24, 2026

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
14:51

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Published on: November 13, 2021

6.1K
Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules
07:35

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules

Published on: December 16, 2021

2.8K
"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome
06:31

"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome

Published on: March 24, 2023

3.1K

Area of Science:

  • Proteomics
  • Cell Biology
  • Bioinformatics

Background:

  • Understanding protein function relies on knowing their subcellular location.
  • Spatial proteomics, using high-throughput mass spectrometry, is advancing the systematic localization of thousands of proteins.
  • Advances in experimental techniques necessitate improved data analysis methods.

Purpose of the Study:

  • To demonstrate the application of `pRoloc` for Bayesian analysis of spatial proteomics data.
  • To provide a detailed workflow for setting up, running, and interpreting spatial proteomics data analysis.
  • To offer insights into Bayesian analysis principles for spatial proteomics.

Main Methods:

  • Utilized `pRoloc` software for Bayesian analysis of spatial proteomics datasets.
  • Developed a step-by-step pipeline for data analysis, including convergence assessment.
  • Integrated explanations of Bayesian analysis concepts within the workflow.

Main Results:

  • Successfully applied `pRoloc` to analyze spatial proteomics data.
  • Demonstrated a reproducible workflow for Bayesian analysis of protein localization.
  • Provided clear guidance on interpreting the results of spatial proteomics studies.

Conclusions:

  • `pRoloc` offers a robust framework for Bayesian analysis in spatial proteomics.
  • The provided workflow facilitates the systematic localization and functional inference of proteins.
  • This work enhances the analytical capabilities for spatial proteomics research.