Quantitative Model of Transcriptional Noise Regulation by mRNA Condensates
Andreas Lanitis, Anatoly B. Kolomeisky
This study develops a theoretical framework to quantify how reversible mRNA condensation affects transcriptional noise and robustness.
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Center for Theoretical Biological PhysicsORCID 0000-0001-5677-6690Unclaimed ORCID profile · follow to get notified of new preprints
12 papers
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Andreas Lanitis, Anatoly B. Kolomeisky
This study develops a theoretical framework to quantify how reversible mRNA condensation affects transcriptional noise and robustness.
Cheuk Fung Alvin Leung, Anatoly B. Kolomeisky
This paper presents a stochastic model to study microbial growth dynamics in a single-species-single-resource system, identifying three dynamical regimes and showing how stochasticity affects behavior at low population levels.
Zhuoyan Lyu, Anatoly B. Kolomeisky
The paper proposes a stochastic mechanism for dominant follicle selection, showing how FSH and estradiol interact to ensure single follicle selection through negative feedback.
Angela Medvedeva, Ksenia Kolomeisky, Anatoly B. Kolomeisky
The paper develops a physical-chemical framework to identify fragment-level structural determinants of molecular mechanisms, applying it to pyronaridine's crystal-growth inhibition and antimalarial activity.
Kinshuk Banerjee, Pintu Patra, Anatoly B. Kolomeisky, Biswajit Das
The paper demonstrates that the Fano factor can be used to determine cooperativity in biological networks, showing that non-linear Fano factor variation indicates positive cooperativity.
Tripti Midha, Anatoly B. Kolomeisky, Oleg A. Igoshin
This study develops a theoretical model to explain sequence-dependent transcriptional error rates, revealing how downstream nucleotides influence RNA polymerase II fidelity.
Carson C. Cole, Brett H. Pogostin, Kiana A. Cahue…·Jeffrey D. Hartgerink
This paper demonstrates that Dopa crosslinking with lysine covalently stabilizes collagen mimetic peptides and their assemblies, enhancing thermal stability for biomedical applications.
Hamid Teimouri, Zahra S. Ghoreyshi, Anatoly B. Kolomeisky, Jason Thomas George
This study shows that feature selection improves peptide binding predictions for TCRs by optimizing model complexity and performance using physicochemical properties and machine learning.
Zahra S. Ghoreyshi, Hamid Teimouri, Anatoly B. Kolomeisky, Jason Thomas George
This study improves T cell-antigen specificity prediction by integrating kinetic data into affinity-driven models, enhancing predictions for low-affinity TCR-pMHC interactions.
Carson C. Cole, Douglas R. Walker, Sarah A. H. Hulgan…·Jeffrey D. Hartgerink
This paper designs a collagen heterotrimer with high folding specificity and reports its faster folding rate compared to other systems.
Hamid Teimouri, Angela Medvedeva, Anatoly B. Kolomeisky
The paper develops a computational method to predict protein-protein interactions using dipeptide compositions as key features, showing strong correlation across organisms.
Y.G. Pan, S. Banerjee, K. Zagorski…·Y. L. Lyubchenko
The paper develops a molecular model explaining how surface interactions accelerate protein aggregation, validated through experiments with synuclein and APOBEC3G.