Venice Summer School in Evolutionary Systems BiologyWhat a week! A huge thank you to all the students and teachers for the for the engaged discussions, thoughtful questions, and good vibes. Rock on, and stay curious! 🤓 ✨
#VeniceEvoDevo #levels #morphogenesis #sysbio #evodevo
Darren WilkinsonPublished in JOSS: 'jax-smfsb: A Python library for stochastic systems biology modelling and inference' https://doi.org/10.21105/joss.07491 #python #JAX #scicomp #sciml #sysbio #bayesian
jax-smfsb: A Python library for stochastic systems biology modelling and inference
Wilkinson, D. J., (2025). jax-smfsb: A Python library for stochastic systems biology modelling and inference. Journal of Open Source Software, 10(106), 7491, https://doi.org/10.21105/joss.07491
Julio R. Banga📢 New preprint out!
We used conformal prediction to perform uncertainty quantification in dynamic models of biological systems.
https://arxiv.org/abs/2409.02644
Great collaboration with
@MarcosMatabuena https://www.marcosmatabuena.com/
#sysbio #UQ #ML #DynamicModels
Conformal Prediction in Dynamic Biological Systems
Uncertainty 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.
Pablo Cárdenas R.Wassup! Paper pile for weekly #Evoluncheons meetup (week 14 Aug 2023).
Some fundamental stuff, some viruses, some systems and synthetic bio with evolutionary implications (specifically, fitness effects of gene regulation).
We have: 1/n
Biplab BoseI 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: https://github.com/biplabbose/Systems_Biology_Textbook
Please use the materials in your course and give me feedback for improvements.
GitHub - 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...
Dr. Chris Rackauckas 
📣 Calling all #sysbio tool developers and users! Applications for the "Systems biology: community needs, plans, and visions" discussion @JuliaCon are now open! Brainstorm future developments and collaborate with top players in the field.
#SciML #JuliaLang #JuliaCon2023
➡️Apply now: https://forms.gle/icu9Fp1cNPPvCJsW7
➡️More info: https://pretalx.com/juliacon2023/talk/review/TFZC7Z8WHUXFMJSZHET3NKAHB7X88FSF
#SciML #JuliaLang #JuliaCon2023
➡️Apply now: https://forms.gle/icu9Fp1cNPPvCJsW7
➡️More info: https://pretalx.com/juliacon2023/talk/review/TFZC7Z8WHUXFMJSZHET3NKAHB7X88FSF
Application for the "Systems biology: community needs, plans, and visions" discussion @JuliaCon 2023
The Scientific Machine Learning (SciML) ecosystem is rapidly gaining momentum within the field of systems biology. With this birds of feather discussion we want to bring the international community of systems biology tool developers and users at one table to brainstorm promising routes for future developments, and facilitate collaborative projects. For more details, please check out our event description and the JuliaCon website. Applicants will be accepted on a rolling basis and notified by email. Please [email protected] with any questions.
Mike Hucka📣 We now have an account for COMBINE (the COmputational Modeling in BIology NEtwork) on Mastodon!
@combine – https://fediscience.org/@combine
It is currently a bit sparse, but hopefully that will improve over time.
#SystemsBiology #SysBio #Biology #ComputationalBiology #Science #ComputationalNeuroscience #Ontologies #Bioinformatics #SyntheticBiology #Neuroscience
COMBINE (@[email protected])
0 Posts, 1 Following, 23 Followers · This is the official Mastodon account for COMBINE (the COmputational Modeling in BIology NEtwork). COMBINE is an initiative to coordinate the development of the various community standards and formats for computational models in biology. #SystemsBiology #SysBio #SyntheticBiology #SynBio #Bioinformatics #Neuroscience #ComputationalNeuroscience #Science #Ontologies
Christian DienerHi #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 https://isbscience.org in the Gibbons lab.
I will be mostly crossposting from Twitter here unless it becomes complete 🚮🔥
#introduction #metabolic-modeling #sysbio
esteban antonicellilet's do a hashtags #introduction
I'm a biologist with a MSc in plant physiology and a PhD in plant biochemistry and molecular biology. My current interests are #AI #synbio #genomics #sysbio #RNAseq #metabolomics #plants #bioinformatics #DL #ML #statistics #R #python #julia #philosophy #aiethics
I'm a biologist with a MSc in plant physiology and a PhD in plant biochemistry and molecular biology. My current interests are #AI #synbio #genomics #sysbio #RNAseq #metabolomics #plants #bioinformatics #DL #ML #statistics #R #python #julia #philosophy #aiethics
Lynn ChiuFreaking amazing that we're at the stage whereby the #evolution tag actually returns rich, meaningful posts about evolutionary biology and the people working on it. Taking advantage of this hashtag before it's overrrun by ... other ... sorts of evolution content.
More hashtags! #evobio #evotheory #ecoevo #evodevo #ecoevodevo #devobio #philbio #developmentalbiology #ees #devogenetics #sysbio