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#sysbio

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Julio R. Banga

📢 New preprint out!
We used conformal prediction to perform uncertainty quantification in dynamic models of biological systems.

arxiv.org/abs/2409.02644

Great collaboration with
@MarcosMatabuena marcosmatabuena.com/

#sysbio #UQ #ML #DynamicModels

arXiv.orgConformal Prediction in Dynamic Biological SystemsUncertainty quantification (UQ) is the process of systematically determining and characterizing the degree of confidence in computational model predictions. In the context of systems biology, especially with dynamic models, UQ is crucial because it addresses the challenges posed by nonlinearity and parameter sensitivity, allowing us to properly understand and extrapolate the behavior of complex biological systems. Here, we focus on dynamic models represented by deterministic nonlinear ordinary differential equations. Many current UQ approaches in this field rely on Bayesian statistical methods. While powerful, these methods often require strong prior specifications and make parametric assumptions that may not always hold in biological systems. Additionally, these methods face challenges in domains where sample sizes are limited, and statistical inference becomes constrained, with computational speed being a bottleneck in large models of biological systems. As an alternative, we propose the use of conformal inference methods, introducing two novel algorithms that, in some instances, offer non-asymptotic guarantees, enhancing robustness and scalability across various applications. We demonstrate the efficacy of our proposed algorithms through several scenarios, highlighting their advantages over traditional Bayesian approaches. The proposed methods show promising results for diverse biological data structures and scenarios, offering a general framework to quantify uncertainty for dynamic models of biological systems.The software for the methodology and the reproduction of the results is available at https://zenodo.org/doi/10.5281/zenodo.13644870.
Public
Biplab Bose

I am slow and lazy. So my project on writing the textbook on computational systems biology is moving at a snail's pace.
The book chapters are here on git: github.com/biplabbose/Systems_

Please use the materials in your course and give me feedback for improvements.

GitHubGitHub - biplabbose/Systems_Biology_Textbook: A GitHub repository holding chapters of the book – “A Textbook on Computational Systems Biology.” Author: Biplab Bose, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Assam, India, PIN- 781039. All the contents of this repository are provided under the Creative Commons License “CC BY-NC-ND 4.0”A GitHub repository holding chapters of the book – “A Textbook on Computational Systems Biology.” Author: Biplab Bose, Department of Biosciences and Bioengineering, Indian Institute of Technology G...
#SysBio#textbook#computationalbiology
Public
Christian Diener

Hi #mastodon, I'm a Microbial Systems Biologist interested in metabolic interactions in the #microbiome and how that relates to microbial #ecology. I do computational but also ferment a lot of poop 💩 Working as a research scientist at isbscience.org in the Gibbons lab.

I will be mostly crossposting from Twitter here unless it becomes complete 🚮🔥

#introduction #metabolic-modeling #sysbio

Institute for Systems BiologyInstitute for Systems Biology (ISB) - Seattle, WASystems biology was pioneered at ISB, a nonprofit biomedical research organization and affiliate of Providence. Science Transforming Health.
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