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Gene expression is a biochemical process, where stochastic binding and un-binding events naturally generate fluctuations and cell-to-cell variability in gene dynamics. These fluctuations typically have destructive consequences for proper…

Populations and Evolution · Quantitative Biology 2022-03-22 Yen Ting Lin , Nicolas E. Buchler

Foundation models for single-cell RNA sequencing (scRNA-seq) have shown promising capabilities in capturing gene expression patterns. However, current approaches face critical limitations: they ignore biological prior knowledge encoded in…

Machine Learning · Computer Science 2025-03-04 Mufan Qiu , Xinyu Hu , Fengwei Zhan , Sukwon Yun , Jie Peng , Ruichen Zhang , Bhavya Kailkhura , Jiekun Yang , Tianlong Chen

The inference of gene regulatory networks (GRNs) is a foundational stride towards deciphering the fundamentals of complex biological systems. Inferring a possible regulatory link between two genes can be formulated as a link prediction…

Machine Learning · Computer Science 2025-04-25 Binon Teji , Swarup Roy

Search for possible relationships between phylogeny and ontogeny is one of the most important issues in the field of evolutionary developmental biology. By representing developmental dynamics of spatially located cells with gene expression…

Populations and Evolution · Quantitative Biology 2015-04-01 Takahiro Kohsokabe , Kunihiko Kaneko

The Gene Regulatory Network (GRN) of biological cells governs a number of key functionalities that enables them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and…

Neural and Evolutionary Computing · Computer Science 2023-10-10 Adrian Ratwatte , Samitha Somathilaka , Sasitharan Balasubramaniam , Assaf A. Gilad

Over the past twenty years, artificial Gene Regulatory Networks (GRNs) have shown their capacity to solve real-world problems in various domains such as agent control, signal processing and artificial life experiments. They have also…

Neural and Evolutionary Computing · Computer Science 2018-07-17 Dennis G Wilson , Kyle Harrington , Sylvain Cussat-Blanc , Hervé Luga

Genetic regulatory networks enable cells to respond to the changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits…

Biological Physics · Physics 2015-03-17 Aleksandra M Walczak , Gašper Tkačik

Large sets of genotypes give rise to the same phenotype because phenotypic expression is highly redundant. Accordingly, a population can accept mutations without altering its phenotype, as long as thegenotype mutates into another one on the…

Populations and Evolution · Quantitative Biology 2015-02-18 Susanna Manrubia , José A. Cuesta

Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which…

Molecular Networks · Quantitative Biology 2014-11-26 Deok-Sun Lee

Gene regulatory network inference uses genome-wide transcriptome measurements in response to genetic, environmental or dynamic perturbations to predict causal regulatory influences between genes. We hypothesized that evolution also acts as…

Genomics · Quantitative Biology 2015-05-20 Anagha Joshi , Yvonne Beck , Tom Michoel

Evolution has fascinated quantitative and physical scientists for decades: how can the random process of mutation, recombination, and duplication of genetic information generate the diversity of life? What determines the rate of evolution?…

Populations and Evolution · Quantitative Biology 2018-04-23 Richard A. Neher , Aleksandra M. Walczak

In multi-cellular organisms, cells differentiate into multiple types as they divide. States of these cell types, as well as their numbers, are known to be robust to external perturbations; as conceptualized by Waddington's epigenetic…

Biological Physics · Physics 2026-01-21 Davey Plugers , Kunihiko Kaneko

Robustness to genetic or environmental disturbances is often considered as a key property of living systems. Yet, in spite of being discussed since the 1950s, how robustness emerges from the complexity of genetic architectures and how it…

Populations and Evolution · Quantitative Biology 2022-03-31 Arnaud Le Rouzic

The editing of transcribed RNA by other molecules such that the form of the final product differs from that specified in the corresponding DNA sequence is ubiquitous. This paper uses an abstract, tunable Boolean genetic regulatory network…

Neural and Evolutionary Computing · Computer Science 2015-05-11 Larry Bull

Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and…

Molecular Networks · Quantitative Biology 2018-03-16 Edgar Herrera-Delgado , Ruben Perez-Carrasco , James Briscoe , Peter Sollich

The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic…

Populations and Evolution · Quantitative Biology 2015-06-15 Kunihiko Kaneko

Evolutionary dynamics is often viewed as a subtle process of change accumulation that causes a divergence among organisms and their genomes. However, this interpretation is an inheritance of a gradualistic view that has been challenged at…

Populations and Evolution · Quantitative Biology 2018-07-27 Jacobo Aguirre , Pablo Catalán , José A. Cuesta , Susanna Manrubia

Background: Duplication of genes is important for evolution of molecular networks. Many authors have therefore considered gene duplication as a driving force in shaping the topology of molecular networks. In particular it has been noted…

Populations and Evolution · Quantitative Biology 2009-11-13 Jakob Enemark , Kim Sneppen

Molecular noise in gene regulatory networks has two intrinsic components, one part being due to fluctuations caused by the birth and death of protein or mRNA molecules which are often present in small numbers and the other part arising from…

Molecular Networks · Quantitative Biology 2015-11-17 Davit A. Potoyan , Peter G. Wolynes

Gene expression is inherently noisy as many steps in the read-out of the genetic information are stochastic. To disentangle the effect of different sources of stochasticity in such systems, we consider various models that describe some…

Molecular Networks · Quantitative Biology 2015-06-05 Rahul Marathe , David Gomez , Stefan Klumpp