ReviewFrontiers in physiology2014
Why model?
Review in Frontiers in physiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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.
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.
Who cites it
32 citing papers in PubMed.
- Navigating the Challenges of Metallopharmaceutical Agents: Strategies and Predictive Modeling for Skin Cancer Therapy.Pharmaceutics · 2026Review
- Ten "Cheat Codes" for Measuring Oxidative Stress in Humans.Antioxidants (Basel, Switzerland) · 2024Review
- Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3DBiophysics reviews · 2024Review
- The art of modeling gene regulatory circuits.NPJ systems biology and applications · 2024Article
- Geometric analysis enables biological insight from complex non-identifiable models using simple surrogates.PLoS computational biology · 2023Article
- A group theoretic approach to model comparison with simplicial representations.Journal of mathematical biology · 2022Article
- Mechanistically Coupled PK (MCPK) Model to Describe Enzyme Induction and Occupancy Dependent DDI of Dabrafenib Metabolism.Pharmaceutics · 2022Article
- Computational Models for Clinical Applications in Personalized Medicine-Guidelines and Recommendations for Data Integration and Model Validation.Journal of personalized medicine · 2022Review
- Model comparison via simplicial complexes and persistent homology.Royal Society open science · 2021Article
- Using optimal control to understand complex metabolic pathways.BMC bioinformatics · 2020Article
- Genome-scale metabolic reconstruction of the symbiosis between a leguminous plant and a nitrogen-fixing bacterium.Nature communications · 2020Article
- Computational models of melanoma.Theoretical biology & medical modelling · 2020Review
- Simulating Dynamics of Circulation in the Awake State and Different Stages of Sleep Using Non-autonomous Mathematical Model With Time Delay.Frontiers in physiology · 2020Article
- Connecting signaling and metabolic pathways in EGF receptor-mediated oncogenesis of glioblastoma.PLoS computational biology · 2019Article
- Evidence for personalised medicine: mechanisms, correlation, and new kinds of black box.Theoretical medicine and bioethics · 2019Article
- Multiscale Solutions to Quantitative Systems Biology Models.Frontiers in molecular biosciences · 2019Article
- Notions of similarity for systems biology models.Briefings in bioinformatics · 2018Article
- Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways.Frontiers in physiology · 2018Article
- Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2017Article
- Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization.Human genomics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next generation sequencing technologies are bringing about a renaissance of mining approaches. A comprehensive picture of the genetic landscape of an individual patient will be useful, for example, to identify groups of patients that do or do not respond to certain therapies. The high expectations may however not be satisfied if the number of patient groups with similar characteristics is going to be very large. I therefore doubt that mining sequence data will give us an understanding of why and when therapies work. For understanding the mechanisms underlying diseases, an alternative approach is to model small networks in quantitative mechanistic detail, to elucidate the role of gene and proteins in dynamically changing the functioning of cells. Here an obvious critique is that these models consider too few components, compared to what might be relevant for any particular cell function. I show here that mining approaches and dynamical systems theory are two ends of a spectrum of methodologies to choose from. Drawing upon personal experience in numerous interdisciplinary collaborations, I provide guidance on how to model by discussing the question "Why model?"
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.