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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

The computational prediction of a protein structure from its sequence generally relies on a method to assess the quality of protein models. Most assessment methods rank candidate models using heavily engineered structural features, defined…

Biomolecules · Quantitative Biology 2018-11-26 Georgy Derevyanko , Sergei Grudinin , Yoshua Bengio , Guillaume Lamoureux

Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schroedinger equation. This includes corresponding conservation laws.…

Quantum Physics · Physics 2016-04-25 Hans-Thomas Elze

Statistical model checking is a class of sequential algorithms that can verify specifications of interest on an ensemble of cyber-physical systems (e.g., whether 99% of cars from a batch meet a requirement on their energy efficiency). These…

Machine Learning · Computer Science 2022-06-29 Yu Wang , Hussein Sibai , Mark Yen , Sayan Mitra , Geir E. Dullerud

Information has an entropic character which can be analyzed within the Statistical Theory in molecular systems. R. Landauer and C.H. Bennett showed that a logical copy can be carried out in the limit of no dissipation if the computation is…

Biological Physics · Physics 2012-08-15 J. Ricardo Arias-Gonzalez

With the advent of massive data outputs at a regular rate, admittedly, signal processing technology plays an increasingly key role. Nowadays, signals are not merely restricted to physical sources, they have been extended to digital sources…

Information Theory · Computer Science 2015-07-28 Yi Lu

This article introduces the physics of information in the context of molecular biology and genomics. Entropy and information, the two central concepts of Shannon's theory of information and communication, are often confused with each other…

Biomolecules · Quantitative Biology 2007-05-23 Christoph Adami

DNA storage has emerged as an important area of research. The reliability of DNA storage system depends on designing the DNA strings (called DNA codes) that are sufficiently dissimilar. In this work, we introduce DNA codes that satisfy a…

Information Theory · Computer Science 2022-11-28 Krishna Gopal Benerjee , Sourav Deb , Manish K Gupta

Conservation laws are an inherent feature in many systems modeling real world phenomena, in particular, those modeling biological and chemical systems. If the form of the underlying dynamical system is known, linear algebra and algebraic…

Numerical Analysis · Mathematics 2024-03-11 Tracey Oellerich , Maria Emelianenko

Perturbative supersymmetry breaking on the landscape of string vacua is expected to favor large soft terms as a power-law or log distribution, but tempered by an anthropic veto of inappropriate vacua or vacua leading to too large a value…

High Energy Physics - Phenomenology · Physics 2022-01-05 Howard Baer , Vernon Barger , Shadman Salam , Hasan Serce

Humans share with many animal species the ability to perceive and approximately represent the number of objects in visual scenes. This ability improves throughout childhood, suggesting that learning and development play a key role in…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Kuinan Hou , Marco Zorzi , Alberto Testolin

It is well-known that the Hessian of deep loss landscape matters to optimization, generalization, and even robustness of deep learning. Recent works empirically discovered that the Hessian spectrum in deep learning has a two-component…

Machine Learning · Computer Science 2022-08-02 Zeke Xie , Qian-Yuan Tang , Yunfeng Cai , Mingming Sun , Ping Li

A complete structure-preserving learning scheme for single-input/single-output (SISO) linear port-Hamiltonian systems is proposed. The construction is based on the solution, when possible, of the unique identification problem for these…

Dynamical Systems · Mathematics 2023-03-29 Juan-Pablo Ortega , Daiying Yin

Motivation: Gene regulatory interactions are of fundamental importance to various biological functions and processes. However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes…

Molecular Networks · Quantitative Biology 2017-02-09 Shupeng Gui , Rui Chen , Liang Wu , Ji Liu , Hongyu Miao

In this work, we present a sampling algorithm for single hidden layer neural networks. This algorithm is built upon a recursive series of Bayesian posteriors using a method we call Greedy Bayes. Sampling of the Bayesian posterior for neuron…

Machine Learning · Statistics 2024-07-29 Curtis McDonald , Andrew R Barron

We introduce in this paper a runtime-efficient tree hashing algorithm for the identification of isomorphic subtrees, with two important applications in genetic programming for symbolic regression: fast, online calculation of population…

Machine Learning · Computer Science 2021-07-23 Bogdan Burlacu , Lukas Kammerer , Michael Affenzeller , Gabriel Kronberger

We consider a stochastic Hodgkin-Huxley model driven by a periodic signal as model for the membrane potential of a pyramidal neuron. The associated five dimensional diffusion process is a time inhomogeneous highly degenerate diffusion for…

Probability · Mathematics 2012-07-03 Reinhard Höpfner , Eva Löcherbach , Michèle Thieullen

We propose a novel decoupled unconditionally stable numerical scheme for the simulation of two-phase flow in a Hele-Shaw cell which is governed by the Cahn-Hilliard-Hele-Shaw system (CHHS) with variable viscosity. The temporal…

Numerical Analysis · Mathematics 2014-11-03 Daozhi Han

Motivation: DNA data is transcribed into single-stranded RNA, which folds into specific molecular structures. In this paper we pose the question to what extent sequence- and structure-information correlate. We view this correlation as…

Combinatorics · Mathematics 2016-08-23 Christopher Barrett , Fenix W. Huang , Christian M. Reidys

Real-world observational datasets and machine learning have revolutionized data-driven decision-making, yet many models rely on empirical associations that may be misleading due to confounding and subgroup heterogeneity. Simpson's paradox…

Machine Learning · Computer Science 2026-03-03 Xian Teng , Yu-Ru Lin
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