Purushottam Dixit
@pdixit.bsky.social
Assistant Professor, Biomedical Engineering, Yale University. Computational biologist.
What if aging isn’t just cellular damage, but a lossy transmission of information?
We used single-cell data and physics-based models to show that as cells age, the flow of transcriptional information collapses. Here’s what that means. 👇
We used single-cell data and physics-based models to show that as cells age, the flow of transcriptional information collapses. Here’s what that means. 👇
Decay in transcriptional information flow is a hallmark of cellular aging https://www.biorxiv.org/content/10.1101/2025.10.30.685689v1
November 4, 2025 at 2:30 PM
What if aging isn’t just cellular damage, but a lossy transmission of information?
We used single-cell data and physics-based models to show that as cells age, the flow of transcriptional information collapses. Here’s what that means. 👇
We used single-cell data and physics-based models to show that as cells age, the flow of transcriptional information collapses. Here’s what that means. 👇
Just out: new preprint (with @ralitsamadsen.bsky.social) is now #Reviewed at @eLife! "Non-equilibrium strategies for ligand specificity in signaling networks". We show how cells use non-equilibrium strategies to discriminate between ligands in surprising ways 🔗 elifesciences.org/reviewed-pre...
Non-equilibrium strategies for ligand specificity in signaling networks
elifesciences.org
July 30, 2025 at 10:13 AM
Just out: new preprint (with @ralitsamadsen.bsky.social) is now #Reviewed at @eLife! "Non-equilibrium strategies for ligand specificity in signaling networks". We show how cells use non-equilibrium strategies to discriminate between ligands in surprising ways 🔗 elifesciences.org/reviewed-pre...
We have a funding for postdoctoral fellowship that needs to be filled very soon. We are exploring new directions (1) at the interface of non-equilibrium computations and physical learning and (2) in building ecologically motivated machine learning models for microbiomes. Please spread the word!
July 23, 2025 at 1:43 AM
We have a funding for postdoctoral fellowship that needs to be filled very soon. We are exploring new directions (1) at the interface of non-equilibrium computations and physical learning and (2) in building ecologically motivated machine learning models for microbiomes. Please spread the word!
Just learnt that our collaborative grant proposal on identifying master regulators of T cell metabolism in Lupus will not be reviewed as the study section was indefinitely postponed, along with many other grants that are vital to biomedical research.
February 26, 2025 at 3:55 PM
Just learnt that our collaborative grant proposal on identifying master regulators of T cell metabolism in Lupus will not be reviewed as the study section was indefinitely postponed, along with many other grants that are vital to biomedical research.
Has anybody looked at approximate Bayesian computation (ABC) using stat mech? The formulation used in rejection ABC: rho(S(D),S(D')) < eps (rho is discrepancy function, S is a summary stat, D is data, D' is simulated data) looks an awful lot like the microcanonical ensemble with an energy = S(D).
February 6, 2025 at 11:48 PM
Has anybody looked at approximate Bayesian computation (ABC) using stat mech? The formulation used in rejection ABC: rho(S(D),S(D')) < eps (rho is discrepancy function, S is a summary stat, D is data, D' is simulated data) looks an awful lot like the microcanonical ensemble with an energy = S(D).
Our work on computational design of microbiomes with desired host properties using mechanistic models is now out in mSystems: journals.asm.org/doi/10.1128/...
Designing host-associated microbiomes using the consumer/resource model | mSystems
Generative models are extremely popular in modern biology. They have been used to
model the variation of protein sequences, entire genomes, and RNA sequencing profiles.
Importantly, generative models ...
journals.asm.org
December 10, 2024 at 2:41 PM
Our work on computational design of microbiomes with desired host properties using mechanistic models is now out in mSystems: journals.asm.org/doi/10.1128/...
Happy to present our second paper on understanding ligand sensing using non-equilibrium reaction networks. Here, we look at some counterintuitive results on how eukaryotic cells sense extracellular spatial gradients in ligands (e.g. growth factors): www.biorxiv.org/content/10.1...
Receptor polarization through localized activity and global sensitization
Eukaryotic cells chemosense concentration gradients of extracellular ligands using membrane-bound receptors that polarize their activity. Receptors from several chemosensing families are preferentiall...
www.biorxiv.org
November 25, 2024 at 9:02 PM
Happy to present our second paper on understanding ligand sensing using non-equilibrium reaction networks. Here, we look at some counterintuitive results on how eukaryotic cells sense extracellular spatial gradients in ligands (e.g. growth factors): www.biorxiv.org/content/10.1...
As my first post here, I am really excited to share a new manuscript with @ralitsamadsen.bsky.social on this platform. We looked how non-equilibrium thermodynamics helps ligand discrimination in signaling networks: t.co/ZA6NteUmaS
https://biorxiv.org/cgi/content/short/2024.10.01.615884v1
t.co
November 18, 2024 at 12:42 AM
As my first post here, I am really excited to share a new manuscript with @ralitsamadsen.bsky.social on this platform. We looked how non-equilibrium thermodynamics helps ligand discrimination in signaling networks: t.co/ZA6NteUmaS