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At the point of a second order phase transition also termed as a critical point, systems display long range order and their macroscopic behaviors are independent of the microscopic details making up the system. Due to these properties, it…

Neurons and Cognition · Quantitative Biology 2017-07-18 Vaibhav Wasnik

The ability to simulate realistic networks based on empirical data is an important task across scientific disciplines, from epidemiology to computer science. Often simulation approaches involve selecting a suitable network generative model…

Social and Information Networks · Computer Science 2024-06-13 Raima Carol Appaw , Nicholas Fountain-Jones , Michael A. Charleston

Synthetic genetic circuits are implemented in living cells for their operation. During gene expression, proteins are produced from the respective genes, by formation of complexes through the process of transcription and translation. In…

Molecular Networks · Quantitative Biology 2021-12-10 Priya Chakraborty , Sayantari Ghosh

Recent genomic and bioinformatic advances have motivated the development of numerous random network models purporting to describe graphs of biological, technological, and sociological origin. The success of a model has been evaluated by how…

Molecular Networks · Quantitative Biology 2007-05-23 Manuel Middendorf , Etay Ziv , Carter Adams , Jen Hom , Robin Koytcheff , Chaya Levovitz , Gregory Woods , Linda Chen , Chris Wiggins

Genetic circuits need a cellular environment to operate in, which naturally couples the circuit function with the overall functionality of gene regulatory network. To execute their functions all gene circuits draw resources in the form of…

Quantitative Methods · Quantitative Biology 2020-07-17 Priya Chakraborty , Sayantari Ghosh

Understanding the molecular processes that drive cellular life is a fundamental question in biological research. Ambitious programs have gathered a number of molecular datasets on large populations. To decipher the complex cellular…

Genomics · Quantitative Biology 2023-03-22 Myriam Bontonou , Anaïs Haget , Maria Boulougouri , Jean-Michel Arbona , Benjamin Audit , Pierre Borgnat

Foundation models in genomics have shown mixed success compared to their counterparts in natural language processing. Yet, the reasons for their limited effectiveness remain poorly understood. In this work, we investigate the role of…

Machine Learning · Computer Science 2026-04-07 Maxime Rochkoulets , Lovro Vrček , Mile Šikić

The capacity of cells and organisms to respond to challenging conditions in a repeatable manner is limited by a finite repertoire of pre-evolved adaptive responses. Beyond this capacity, cells can use exploratory dynamics to cope with a…

Molecular Networks · Quantitative Biology 2017-07-05 Hallel I. Schreier , Yoav Soen , Naama Brenner

Chemical gradients can be used by a particle to determine its position. This \textit{positional information} is of crucial importance, for example in developmental biology in the formation of patterns in an embryo. The central goal of this…

Statistical Mechanics · Physics 2025-02-21 Prashant Singh , Karel Proesmans

Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes. Modeling GRNs is significantly important in order to reveal fundamental cellular processes, examine gene functions and understanding…

Computational Engineering, Finance, and Science · Computer Science 2012-05-10 Khalid Raza , Rafat Parveen

Living cells use readout molecules to record the state of receptor proteins, similar to measurements or copies in typical computational devices. But is this analogy rigorous? Can cells be optimally efficient, and if not, why? We show that,…

Molecular Networks · Quantitative Biology 2017-04-12 Thomas E. Ouldridge , Christopher C. Govern , Pieter Rein ten Wolde

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

Position determination in biological systems is often achieved through protein concentration gradients. Measuring the local concentration of such a protein with a spatially-varying distribution allows the measurement of position within the…

Subcellular Processes · Quantitative Biology 2007-05-23 Filipe Tostevin , Pieter Rein ten Wolde , Martin Howard

Compression has been a critical lens to understand the success of Transformers. In the past, we have typically taken the target distribution as a criterion to evaluate a model's compression performance. Nevertheless,it often remains…

Machine Learning · Computer Science 2025-04-29 Ruifeng Ren , Yong Liu

Quantization reduces the numerical precision of Transformer computations and is widely used to accelerate inference, yet its effect on expressivity remains poorly characterized. We demonstrate a fine-grained theoretical tradeoff between…

Machine Learning · Computer Science 2026-02-04 Sayak Chakrabarti , Toniann Pitassi , Josh Alman

In computer science, we can theoretically neatly separate transmission and processing of information, hardware and software, and programs and their inputs. This is much more intricate in biology, Nevertheless, I argue that Shannon's concept…

Populations and Evolution · Quantitative Biology 2020-11-02 Jürgen Jost

Our work is motivated by and illustrated with application of association networks in computational biology, specifically in the context of gene/protein regulatory networks. Association networks represent systems of interacting elements,…

Applications · Statistics 2012-05-01 Natallia Katenka , Eric D. Kolaczyk

Heterogeneous, interconnected, systems-level, molecular data have become increasingly available and key in precision medicine. We need to utilize them to better stratify patients into risk groups, discover new biomarkers and targets,…

Other Quantitative Biology · Quantitative Biology 2024-05-17 Natasa Przulj , Noel Malod-Dognin

The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing…

Quantitative Methods · Quantitative Biology 2008-12-05 A. Braunstein , A. Pagnani , M. Weigt , R. Zecchina

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance…

Biomolecules · Quantitative Biology 2018-05-24 A. Possenti , M. Vendruscolo , C. Camilloni , G. Tiana
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