Evidence map›Paper›PMID 39971380›Full record

ReviewAnnual review of biomedical engineering2025

The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.

Lingxia Qiao, Ali Khalilimeybodi, Nathaniel J Linden-Santangeli, Padmini Rangamani

Abstract readReview
In one paragraph

Review in Annual review of biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
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  5. Review
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  13. Recent trends in microbial production of alkanes.World journal of microbiology & biotechnology · 2025
    Review
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lingxia QiaoDepartment of Pharmacology, University of California San Diego, La Jolla, California, USA; email: prangamani@health.ucsd.edu.
Ali KhalilimeybodiDepartment of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, California, USA.
Nathaniel J Linden-SantangeliDepartment of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, California, USA.
Padmini RangamaniDepartment of Pharmacology, University of California San Diego, La Jolla, California, USA; email: prangamani@health.ucsd.edu.

Funding

Training in Multi-Scale Analysis of Biological Structure and FunctionT32EB009380 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Andrew D. McCulloch, Padmini Rangamani · 2009 to 2026
$4.8M
CRCNS: Biophysical modeling of axonal morphology and functionR01MH139350 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Padmini Rangamani · 2024 to 2026
$1.1M
NIBIB NIH HHS T32 EB009380NIMH NIH HHS R01 MH139350
6 · The paper itself

Abstract

Understanding interaction mechanisms within cells, tissues, and organisms is crucial for driving developments across biology and medicine. Mathematical modeling is an essential tool for simulating such biological systems. Building on experiments, mechanistic models are widely used to describe small-scale intracellular networks. The development of sequencing techniques and computational tools has recently enabled multiscale models. Combining such larger scale network modeling with mechanistic modeling provides us with an opportunity to reveal previously unknown disease mechanisms and pharmacological interventions. Here, we review systems biology models from mechanistic models to multiscale models that integrate multiple layers of cellular networks and discuss how they can be used to shed light on disease states and even wellness-related states. Additionally, we introduce several methods that increase the certainty and accuracy of model predictions. Thus, combining mechanistic models with emerging mathematical and computational techniques can provide us with increasingly powerful tools to understand disease states and inspire drug discoveries.

Indexed as

Models, BiologicalSystems BiologyAnimalsComputer SimulationHumansUncertaintydrug discoverymathematical biologysensitivity analysissystems biologysystems medicineuncertainty quantification

Identifiers

PMID39971380
PMCPMC12700611

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.