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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

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Two-Compartment Open Model: Overview

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Open and closed-loop control systems

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Related Experiment Video

Updated: May 19, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

MilliMap: interactive closed-loop analysis for spatial omics.

Qianlu Feng1,2, Siyuan Brant Qian3, Lily Jiaxin Wan4

  • 1Neuroscience Program, University of Illinois Urbana-Champaign.

Biorxiv : the Preprint Server for Biology
|May 18, 2026
PubMed
Summary
This summary is machine-generated.

MilliMap unifies spatial omics analysis by integrating statistical computation and tissue visualization. This interactive framework allows biologists to refine parameters and validate findings within a single environment for improved spatial biology insights.

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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Published on: July 6, 2022

Related Experiment Videos

Last Updated: May 19, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Area of Science:

  • Spatial biology
  • Computational pathology
  • Bioinformatics

Background:

  • Current spatial omics workflows separate statistical analysis from tissue-context interpretation.
  • This fragmentation hinders efficient data exploration and validation.

Purpose of the Study:

  • To introduce MilliMap, an interactive framework unifying spatial omics analysis.
  • To enable seamless integration of statistical computation and spatial visualization.
  • To empower biologists with a single environment for parameter steering, region refinement, and finding validation.

Main Methods:

  • Development of an interactive framework (MilliMap) that closes the analysis-visualization loop.
  • Integration of statistical analysis tools with spatial exploration capabilities.
  • Demonstration of utility in neuroanatomy and tumor microenvironment studies.

Main Results:

  • MilliMap successfully unifies statistical analysis and spatial exploration in a single environment.
  • The framework facilitates iterative refinement of analytical parameters and regions of interest (ROIs).
  • Demonstrated ability to delineate complex neuroanatomy and identify niche-specific functional states in tumors.

Conclusions:

  • MilliMap streamlines spatial omics analysis by integrating previously disconnected computational and visualization steps.
  • The unified framework enhances biologist-driven exploration, parameter tuning, and validation of spatial omics data.
  • MilliMap provides a powerful tool for advancing spatial biology research, particularly in complex tissues like the brain and tumor microenvironments.