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Immunoprecipitation

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Immunoprecipitation, or IP, is a widely used technique that employs protein-antibody interactions to isolate proteins or protein complexes in their native state for studying protein-protein interactions, quaternary structures, or supramolecular complexes. Various modifications of the technique, including chromatin IP, cross-linking IP, and fluorescence IP, are commonly used.
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Mapping Infant Immunity with Minimal Input: Integrative Single-cell and Multiomic Profiling

Mapping Infant Immunity with Minimal Input: Integrative Single-cell and Multiomic Profiling

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Integrating and mining diverse data in human immunological studies.

Janet C Siebert¹, Brandie D Wagner, Elizabeth Juarez-Colunga

¹CytoAnalytics, Denver, CO, USA. jsiebert@cytoanalytics.com.

|January 16, 2014

Summary

This study introduces a four-part analytical pipeline for analyzing complex immunological data from high-throughput technologies. It guides bioanalysts and immunologists in integrating and interpreting multi-assay datasets for systems immunology research.

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Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

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Published on: October 15, 2021

Area of Science:

Immunology
Bioinformatics
Data Science

Background:

High-throughput technologies like gene expression, multiplex bead arrays, and flow cytometry generate vast amounts of data in immunology.
Systems immunology studies require integrating and analyzing high-dimensional data across biological compartments for comprehensive understanding.

Purpose of the Study:

To provide a structured analytical framework for handling multi-assay, high-dimensional immunological datasets.
To guide bioanalysts, immunologists, and data analysts in applying appropriate methods to contemporary immunological data.

Main Methods:

Recommends a four-part analytical pipeline: data integration, hypothesis generation, prediction and hypothesis testing, and validation.
Highlights established analytical methods suitable for integrated, high-dimensional datasets.

Main Results:

The pipeline facilitates the consistent combination and analysis of data from various high-throughput immunological assays.
Demonstrates the application of these methods to human immunological studies.

Conclusions:

The proposed analytical pipeline offers a valuable perspective for approaching and interpreting complex immunological datasets.
Enables more robust systems immunology research through integrated data analysis.