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Many recent generative models make use of neural networks to transform the probability distribution of a simple low-dimensional noise process into the complex distribution of the data. This raises the question of whether biological networks…

Neural and Evolutionary Computing · Computer Science 2018-02-07 Hesham Mostafa , Gert Cauwenberghs

This paper studies the mitigation of intersymbol interference in a diffusive molecular communication system using enzymes that freely diffuse in the propagation environment. The enzymes form reaction intermediates with information molecules…

Information Theory · Computer Science 2014-01-21 Adam Noel , Karen C. Cheung , Robert Schober

Individual mRNAs are translated by multiple ribosomes that initiate translation with a few seconds interval. The ribosome speed is codon dependant, and ribosome queuing has been suggested to explain specific data for translation of some…

Subcellular Processes · Quantitative Biology 2008-09-26 Namiko Mitarai , Kim Sneppen , Steen Pedersen

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation…

Molecular Networks · Quantitative Biology 2015-06-04 Rudolf Hanel , Manfred Pöchacker , Manuel Schölling , Stefan Thurner

There is growing consensus among neuroscientists that neural circuits critical for survival are the result of genomic decompression processes. We introduce SynaptoGen, a novel computational framework--member of the Connectome Models…

Neural and Evolutionary Computing · Computer Science 2025-09-09 Tommaso Boccato , Matteo Ferrante , Nicola Toschi

Ribonucleic acid (RNA) binds to molecules to achieve specific biological functions. While generative models are advancing biomolecule design, existing methods for designing RNA that target specific ligands face limitations in capturing…

Biomolecules · Quantitative Biology 2025-10-14 Runze Ma , Zhongyue Zhang , Zichen Wang , Chenqing Hua , Jiahua Rao , Zhuomin Zhou , Shuangjia Zheng

Understanding the patterns and causes of phenotypic divergence is a central goal in evolutionary biology. Much work has shown that mRNA abundance is highly variable between closely related species. However, the extent and mechanisms of…

Genomics · Quantitative Biology 2013-12-09 Joel McManus , Gemma May , Pieter Spealman , Alan Shteyman

From the vasculature of animals to the porous media making up batteries, the core task of flow networks is to transport solutes and perfuse all cells or media equally with resources. Yet, living flow networks have a key advantage over…

Heterologous gene expression draws resources from host cells. These resources include vital components to sustain growth and replication, and the resulting cellular burden is a widely recognised bottleneck in the design of robust circuits.…

Molecular Networks · Quantitative Biology 2020-04-06 Evangelos-Marios Nikolados , Andrea Y. Weiße , Diego A. Oyarzún

Entropic repulsion between DNA ring polymers under confinement is the key mechanism governing the spatial segregation of bacterial chromosomes, although it remains incompletely understood how proteins aid the process of entropic…

Soft Condensed Matter · Physics 2021-12-23 Debarshi Mitra , Shreerang Pande , Apratim Chatterji

Membrane protein transporters alternate their substrate-binding sites between the extracellular and cytosolic side of the membrane according to the alternating access mechanism. Inspired by this intriguing mechanism devised by nature, we…

Biological Physics · Physics 2017-11-08 Yizhou Tan , Leonardo Dagdug , Jannes Gladrow , Ulrich F. Keyser , Stefano Pagliara

Cells are known to utilize biochemical noise to probabilistically switch between distinct gene expression states. We demonstrate that such noise-driven switching is dominated by tails of probability distributions and is therefore…

Molecular Networks · Quantitative Biology 2009-11-13 Pankaj Mehta , Ranjan Mukhopadhyay , Ned S. Wingreen

Understanding the rules underlying organismal development is a major unsolved problem in biology. Each cell in a developing organism responds to signals in its local environment by dividing, excreting, consuming, or reorganizing, yet how…

Cell Behavior · Quantitative Biology 2025-08-20 Ramya Deshpande , Francesco Mottes , Ariana-Dalia Vlad , Michael P. Brenner , Alma dal Co

It often is emphasized that gene expression is noisy. A seemingly contradictory view is that control mechanisms have been optimized to squeeze as much information as possible out of a limited number of molecules. Here we revisit these…

Biological Physics · Physics 2025-12-17 Nicholas Lawson , William Bialek

The mechanical unfolding of a simple RNA hairpin and of a 236--bases portion of the Tetrahymena thermophila ribozyme is studied by means of an Ising--like model. Phase diagrams and free energy landscapes are computed exactly and suggest a…

Soft Condensed Matter · Physics 2009-11-05 A. Imparato , A. Pelizzola , M. Zamparo

In this paper the qualitative dynamical properties of so-called generalized ribosome flow models are studied. Ribosome flow models known from the literature are generalized by allowing an arbitrary directed network structure between the…

Dynamical Systems · Mathematics 2023-07-19 G. Szederkenyi , M. A. Vaghy

The problem of transport through nanochannels is one of the major questions in cell biology, with a wide range of applications. Brownian ratchets are fundamental in various biochemical processes, and are roughly divided into two categories:…

Soft Condensed Matter · Physics 2013-07-24 Anna Lappala , Alessio Zaccone , Eugene M. Terentjev

Diffusion and flow models have become the dominant paradigm for generative modeling on Riemannian manifolds, with successful applications in protein backbone generation and DNA sequence design. However, these methods require tens to…

Machine Learning · Computer Science 2026-05-04 Dongyeop Woo , Marta Skreta , Seonghyun Park , Kirill Neklyudov , Sungsoo Ahn

We demonstrate how a genetic algorithm solves the problem of minimizing the resources used for network coding, subject to a throughput constraint, in a multicast scenario. A genetic algorithm avoids the computational complexity that makes…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Minkyu Kim , Varun Aggarwal , Una-May O'Reilly , Muriel Medard , Wonsik Kim

Reduction of communication and efficient partitioning are key issues for achieving scalability in hierarchical $N$-Body algorithms like FMM. In the present work, we propose four independent strategies to improve partitioning and reduce…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-20 Mustafa Abduljabbar , George Markomanolis , Huda Ibeid , Rio Yokota , David Keyes
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