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We consider a Moran model with recombination in a haploid population of size $N$. At each birth event, with probability $1-\rho_N R$ the offspring copies one parent's chromosome, and with probability $\rho_N R$ she inherits a chromosome…

Probability · Mathematics 2022-01-19 Amaury Lambert , Verónica Miró Pina , Emmanuel Schertzer

Epigenetic mechanisms of silencing via heritable chromatin modifications play a major role in gene regulation and cell fate specification. We consider a model of epigenetic chromatin silencing in budding yeast and study the bifurcation…

Molecular Networks · Quantitative Biology 2013-04-24 Adel Dayarian , Anirvan M. Sengupta

A Restricted Boltzmann Machine (RBM) is an unsupervised machine-learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relevant statistical features. As such, RBM were recently…

Machine Learning · Computer Science 2019-02-19 Jérôme Tubiana , Simona Cocco , Rémi Monasson

We propose a model for the formation of chromatin loops based on the diffusive sliding of a DNA-bound factor which can dimerise to form a molecular slip-link. Our slip-links mimic the behaviour of cohesin-like molecules, which, along with…

Biological Physics · Physics 2017-10-04 C. A. Brackley , J. Johnson , D. Michieletto , A. N. Morozov , M. Nicodemi , P. R. Cook , D. Marenduzzo

"Epigenetic Tracking" is an evo-devo method to generate arbitrary 2d or 3d shapes; as such, it belongs to the field of "artificial embryology". In silico experiments have proved the effectiveness of the method in devo-evolving shapes of any…

Adaptation and Self-Organizing Systems · Physics 2010-05-27 Alessandro Fontana

Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B compartments play critical roles in a wide range of cellular processes by regulating gene…

Genomics · Quantitative Biology 2024-03-07 Brydon P. G. Wall , My Nguyen , J. Chuck Harrell , Mikhail G. Dozmorov

Fluorescence microscopy reveals that the contents of many (membrane-free) nuclear "bodies" exchange rapidly with the soluble pool whilst the underlying structure persists; such observations await a satisfactory biophysical explanation. To…

Biological Physics · Physics 2017-04-26 C. A. Brackley , B. Liebchen , D. Michieletto , F. Mouvet , P. R. Cook , D. Marenduzzo

Polymers with active segments constitute prospective future materials and are used as a model for some biological systems such as chromatin. The directions of the active forces are typically introduced with temporal or spatial correlations…

Soft Condensed Matter · Physics 2024-11-25 Adam H. T. P. Höfler , Iurii Chubak , Christos N. Likos , Jan Smrek

Sequencing a genome to determine an individual's DNA produces an enormous number of short nucleotide subsequences known as reads, which must be reassembled to reconstruct the full genome. We present a method for analyzing this type of data…

Machine Learning · Computer Science 2025-05-23 Filip Thor , Carl Nettelblad

An In Silico model to relate the properties of proteins to the structure, sequence, function and evolutionary history of proteins is shown. The derived ideal sequences for amino acid residues in proteins can then be considered as attractors…

Condensed Matter · Physics 2007-05-23 S. Bumble

Low-cost, high-throughput DNA and RNA sequencing (HTS) data is the backbone of the life sciences. Genome sequencing is now becoming a part of Predictive, Preventive, Personalized, and Participatory (termed 'P4') medicine. All genomic data…

Nanoscale chromatin domains, variously termed nucleosome clutches, nanodomains, or packing domains, have emerged as fundamental architectural units of the mammalian genome during interphase and mitosis. Unlike cohesin-dependent loops or…

Biological Physics · Physics 2025-10-13 Vinayak Vinayak , Melike Lakadamyali , Vivek B Shenoy

Statistical analysis of evolutionary-related protein sequences provides insights about their structure, function, and history. We show that Restricted Boltzmann Machines (RBM), designed to learn complex high-dimensional data and their…

Quantitative Methods · Quantitative Biology 2019-02-28 Jérôme Tubiana , Simona Cocco , Rémi Monasson

The memory of contemporary Large Language Models is bound by a physical paradox: as they learn, they fill up. The linear accumulation (O(N)) of Key-Value states treats context as a warehouse of static artifacts, eventually forcing a…

Neural and Evolutionary Computing · Computer Science 2025-12-24 Tarik Houichime , Abdelghani Souhar , Younes El Amrani

Recent experimental and theoretical approaches have attempted to quantify the physical organization (compaction and geometry) of the bacterial chromosome with its complement of proteins (the nucleoid). The genomic DNA exists in a complex…

Since the completion of the human genome sequencing project in 2001, significant progress has been made in areas such as gene regulation editing and protein structure prediction. However, given the vast amount of genomic data, the segments…

Other Quantitative Biology · Quantitative Biology 2025-01-29 Wang Liang

Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such landscapes are difficult to learn from data and, once learned, hard to sample from.…

Machine Learning · Computer Science 2026-05-19 Christoph Griesbacher , Lea Bogensperger , Andreas Habring , Thomas Pock

In Xenopus early embryos, replication origins neither require specific DNA sequences nor is there an efficient S/M checkpoint, even though the whole genome (3 billion bases) is completely duplicated within 10-20 minutes. This leads to…

Quantitative Methods · Quantitative Biology 2018-11-06 Suckjoon Jun , John Herrick , Aaron Bensimon , John Bechhoefer

Motivated by the problem of domain formation in chromosomes, we studied a co--polymer model where only a subset of the monomers feel attractive interactions. These monomers are displaced randomly from a regularly-spaced pattern, thus…

Biomolecules · Quantitative Biology 2018-02-13 Matteo Negri , Marco Gherardi , Guido Tiana , Marco Cosentino Lagomarsino

Abstract: Bionic learning with fused sensing, memory and processing functions outperforms artificial neural networks running on silicon chips in terms of efficiency and footprint. However, digital hardware implementation of bionic learning…

Emerging Technologies · Computer Science 2022-02-22 Shijie Wang , Xi Chen , Chao Zhao , Yuxin Kong , Baojun Lin , Yongyi Wu , Zhaozhao Bi , Ziyi Xuan , Tao Li , Yuxiang Li , Wei Zhang , En Ma , Zhongrui Wang , Wei Ma