Show newer

So happy to finally see this collaboration with Rion Correia and @alainbarrat out. The distance backbone is a unique, algebraically-principled network subgraph that preserves all shortest paths. We were were excited to find out (with and other data) that the backbones of contain large amounts of redundant interactions that can be removed with very little impact on and spread.



:

dx.plos.org/10.1371/journal.pc

Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs

Author summary It is through social networks that contagious diseases spread in human populations, as best illustrated by the current pandemic and efforts to contain it. Measuring such networks from human contact data typically results in noisy and dense graphs that need to be simplified for effective analysis, without removal of their essential features. Thus, the identification of a primary subgraph that maintains the social interaction structure and likely transmission pathways is of relevance for studying epidemic spreading phenomena as well as devising intervention strategies to hinder spread. Here we propose and study the metric backbone as an optimal subgraph for sparsification of social contact networks in the study of simple spreading dynamics. We demonstrate that it is a unique, algebraically-principled network subgraph that preserves all shortest paths. We also discover that nine contact networks obtained from proximity sensors in a variety of social contexts contain large amounts of redundant interactions that can be removed with very little impact on community structure and epidemic spread. This reveals that epidemic spread on social networks is very robust to random interaction removal. However, extraction of the metric backbone subgraph reveals which interventions—strategic removal of specific social interactions—are likely to result in maximum impediment to epidemic spread.

dx.plos.org

Super happy to have participated on this special issue on the principle of dynamical . It was really fun to expand our work on effective connectivity, and with Jordan Rozum, Felipe Costa, and Austin Marcus. An a bonus for publishing in ---makes me feel quite cybernetic!
mdpi.com/1099-4300/25/2/374

Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks

Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, protein) typically has high regulatory redundancy, where small subsets of regulators determine activation via collective canalization. Previous work has shown that effective connectivity, a measure of collective canalization, leads to improved dynamical regime prediction for homogeneous automata networks. We expand this by (i) studying random Boolean networks (RBNs) with heterogeneous in-degree distributions, (ii) considering additional experimentally validated automata network models of biomolecular processes, and (iii) considering new measures of heterogeneity in automata network logic. We found that effective connectivity improves dynamical regime prediction in the models considered; in RBNs, combining effective connectivity with bias entropy further improves the prediction. Our work yields a new understanding of criticality in biomolecular networks that accounts for collective canalization, redundancy, and heterogeneity in the connectivity and logic of their automata models. The strong link we demonstrate between criticality and regulatory redundancy provides a means to modulate the dynamical regime of biochemical networks.

www.mdpi.com

Periodic reminder that I've always enjoyed the @petshopboys much more than Pink Floyd. Nothing against the latter, but they never resonated with me like the former. Thank you for the music boys, and very much so for the earnest irony.
youtu.be/bH-JzfkAvD8

We're super happy to have contributed the special issue of on The Principle of Dynamical in .

"Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Networks"

and canalization play major role in predicting , even after accounting for structure, in experimentally-validated biochemical regulation models and random networks. Emphasizing role of redundancy in .systems.

mdpi.com/1099-4300/25/2/374

Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks

Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, protein) typically has high regulatory redundancy, where small subsets of regulators determine activation via collective canalization. Previous work has shown that effective connectivity, a measure of collective canalization, leads to improved dynamical regime prediction for homogeneous automata networks. We expand this by (i) studying random Boolean networks (RBNs) with heterogeneous in-degree distributions, (ii) considering additional experimentally validated automata network models of biomolecular processes, and (iii) considering new measures of heterogeneity in automata network logic. We found that effective connectivity improves dynamical regime prediction in the models considered; in RBNs, combining effective connectivity with bias entropy further improves the prediction. Our work yields a new understanding of criticality in biomolecular networks that accounts for collective canalization, redundancy, and heterogeneity in the connectivity and logic of their automata models. The strong link we demonstrate between criticality and regulatory redundancy provides a means to modulate the dynamical regime of biochemical networks.

www.mdpi.com

So much cool stuff coming from tech. Check out @cyrilpedia update
mRNA vaccine effective against RSV respiratory disease nature.com/articles/d41591-023

Our review on 'Electronic health records and polygenic risk scores for predicting disease risk' in Nature Reviews nature.com/articles/s41576-020 #ehr #gwas #prs #genetics #genomics #bioinformatics

I've since left twitter in response to Elon Musk's repeated attacks on public health and his repeated endorsement of medical disinformation. My account is locked and people can no longer see the original thread unless they followed me before I left.

In light of the Times story, I think it's important for people to see the original thread in full. I've therefore made a pdf available here:

carlbergstrom.com/publications

Feel free to cross-post that link to twitter if you still indulge.

Show thread

, which I like and John Cleese wants to bring back, reminds me that in Anglo-US-North-EU Academics, I had to first enter as the Manuel character, not the Cleese or his wife characters. is complicated. Be kind to non-native speakers.
youtu.be/cwYPCFfbhZM

Colegas PT. Não é normal noutros países a média de uma cadeira fundamental no currículo ser 6 ou 7/20 (c/ 11/20 para 10º melhor). Mais, não é admissível que professor responsável continue. Isto depois de alunos serem selecionados com numerus clausus altíssimos.

The media spectacle of #GenerativeAI (in which AI companies' breathless claims of their software's sorcerous powers are endlessly repeated) has understandably alarmed many #CreativeWorkers, a group that's already traumatized by extractive abuse by media and tech companies.

If you'd like an essay-formatted version of this thread to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

pluralistic.net/2023/02/09/ai-

1/

. So much respect! No one better in laying down tenderness to . So many to choose, but here is my favorite.
Dusty Springfield - The Look of Love youtu.be/Tf1d65OHYXo via @YouTube

I am pasting in a post here from Jay Varma, who used to be with the NYC Department of Health and Mental Hygiene. I agree with every word he writes.

"I was shocked today to learn that New York City will end its requirement that City employees be vaccinated against #COVID19. The City's own data, paid for by its dollars and analyzed by its staff, are abundantly clear: Vaccinating adults averts infections, hospitalizations, and deaths (lnkd.in/eiKt7K95). " 1/

Show older
Qoto Mastodon

QOTO: Question Others to Teach Ourselves
An inclusive, Academic Freedom, instance
All cultures welcome.
Hate speech and harassment strictly forbidden.