ArticleBMC biology2014
Models in biology: 'accurate descriptions of our pathetic thinking'.
Article in BMC biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 1 of them a synthesis that pooled 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.
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
113 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- A mathematical model clarifies the ABC Score formula used in enhancer-gene prediction.bioRxiv : the preprint server for biology · 2024Article
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- Using In silico models to predict lymphocyte activation and development in a data rich era.Immunoinformatics (Amsterdam, Netherlands) · 2024Article
- Simplifications and approximations in a single-gene circuit modeling.Scientific reports · 2024Article
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- Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain.iScience · 2023Article
- Treatment of evolving cancers will require dynamic decision support.Annals of oncology : official journal of the European Society for Medical Oncology · 2023Review
- How to engineer the unknown: Advancing a quantitative and predictive understanding of plant and soil biology to address climate change.PLoS biology · 2023Article
- Transcriptional activators in the early Drosophila embryo perform different kinetic roles.Cell systems · 2023Article
- Loss of regulation of protein synthesis and turnover underpins an attenuated stress response in senescent human mesenchymal stem cells.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Boolean network sketches: a unifying framework for logical model inference.Bioinformatics (Oxford, England) · 2023Article
- Vertical growth dynamics of biofilms.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
53 more citing papers are in PubMed but not listed here.
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
In this essay I will sketch some ideas for how to think about models in biology. I will begin by trying to dispel the myth that quantitative modeling is somehow foreign to biology. I will then point out the distinction between forward and reverse modeling and focus thereafter on the former. Instead of going into mathematical technicalities about different varieties of models, I will focus on their logical structure, in terms of assumptions and conclusions. A model is a logical machine for deducing the latter from the former. If the model is correct, then, if you believe its assumptions, you must, as a matter of logic, also believe its conclusions. This leads to consideration of the assumptions underlying models. If these are based on fundamental physical laws, then it may be reasonable to treat the model as 'predictive', in the sense that it is not subject to falsification and we can rely on its conclusions. However, at the molecular level, models are more often derived from phenomenology and guesswork. In this case, the model is a test of its assumptions and must be falsifiable. I will discuss three models from this perspective, each of which yields biological insights, and this will lead to some guidelines for prospective model builders.
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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.