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Genetic algorithms are a powerful tool in optimization for single and multi-modal functions. This paper provides an overview of their fundamentals with some analytical examples. In addition, we explore how they can be used as a parameter…

The hyperclimbing hypothesis is a hypothetical explanation for adaptation in genetic algorithms with uniform crossover (UGAs). Hyperclimbing is an intuitive, general-purpose, non-local search heuristic applicable to discrete product spaces…

Neural and Evolutionary Computing · Computer Science 2013-07-16 Keki M. Burjorjee

Genetic stability is a key factor in maintaining, survival and reproduction of biological cells. It relies on many processes, but one of the most important is a {\it homologous recombination}, in which the repair of breaks in…

Subcellular Processes · Quantitative Biology 2017-04-05 M. P. Kochugaeva , A. A. Shvets , A. B. Kolomeisky

The Metropolis algorithm involves producing a Markov chain to converge to a specified target density $\pi$. In order to improve its efficiency, we can use the Rejection-Free version of the Metropolis algorithm, which avoids the inefficiency…

Computation · Statistics 2022-10-20 Sigeng Chen , Jeffrey S. Rosenthal , Aki Dote , Hirotaka Tamura , Ali Sheikholeslami

Clustering of proteins is of interest in cancer cell biology. This article proposes a hierarchical Bayesian model for protein (variable) clustering hinging on correlation structure. Starting from a multivariate normal likelihood, we enforce…

Computation · Statistics 2022-02-09 Riddhi Pratim Ghosh , Arnab Kumar Maity , Mohsen Pourahmadi , Bani K. Mallick

Protein design is the inverse approach of the three-dimensional (3D) structure prediction for elucidating the relationship between the 3D structures and amino acid sequences. In general, the computation of the protein design involves a…

Biological Physics · Physics 2021-07-14 Tomoei Takahashi , George Chikenji , Kei Tokita

The comparison of computer generated protein structural models is an important element of protein structure prediction. It has many uses including model quality evaluation, selection of the final models from a large set of candidates or…

Computational Engineering, Finance, and Science · Computer Science 2011-07-27 Paweł Widera , Natalio Krasnogor

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims…

Proteins are the basic building blocks of life. They usually perform functions by folding to a particular structure. Understanding the folding process could help the researchers to understand the functions of proteins and could also help to…

Computational Engineering, Finance, and Science · Computer Science 2015-10-21 Jianzhu Ma

Molecular dynamics algorithms are subject to some amount of error dependent on the size of the time step that is used. This error can be corrected by periodically updating the system with a Metropolis criteria, where the integration step is…

Computational Physics · Physics 2015-06-11 Jason A. Wagoner , Vijay S. Pande

Gene expression and regulation rely on an apparently finely tuned set of reactions between some proteins and DNA. Such DNA-binding proteins have to find specific sequences on very long DNA molecules and they mostly do so in absence of any…

Biological Physics · Physics 2013-12-02 Maria Barbi , Fabien Paillusson

The generation of protein crystals is necessary for the study of protein molecular function and structure. This is done empirically by processing large numbers of crystallization trials and inspecting them regularly in search of those with…

Computer Vision and Pattern Recognition · Computer Science 2018-05-15 Soheil Ghafurian , Peter Orth , Corey Strickland , Hua Su , Sangita Patel , Steven Soisson , Belma Dogdas

All-atom and coarse-grained molecular dynamics are two widely used computational tools to study the conformational states of proteins. Yet, these two simulation methods suffer from the fact that without access to supercomputing resources,…

Quantitative Methods · Quantitative Biology 2022-06-13 Gregory Schwing , Luigi L. Palese , Ariel Fernández , Loren Schwiebert , Domenico L. Gatti

To obtain an electron-density map from a macromolecular crystal the phase-problem needs to be solved, which often involves the use of heavy-atom derivative crystals and concomitantly the determination of the heavy atom substructure. This is…

Biomolecules · Quantitative Biology 2018-08-20 Bjørn Panyella Pedersen , Pontus Gourdon , Xiangyu Liu , Jesper Lykkegaard Karlsen , Poul Nissen

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data.…

Computation · Statistics 2018-03-14 Thomas B. Schön , Andreas Svensson , Lawrence Murray , Fredrik Lindsten

Proteins perform much of the work in living organisms, and consequently the development of efficient computational methods for protein representation is essential for advancing large-scale biological research. Most current approaches…

Quantitative Methods · Quantitative Biology 2023-06-09 Francesco Ceccarelli , Lorenzo Giusti , Sean B. Holden , Pietro Liò

Non-native conformations drive protein misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well-suited for elucidating them and their phenotypic effects. Especially…

The differing ability of polypeptide conformations to act as the native state of proteins has long been rationalized in terms of differing kinetic accessibility or thermodynamic stability. Building on the successful applications of physical…

Biomolecules · Quantitative Biology 2021-11-29 Matteo Negri , Guido Tiana , Riccardo Zecchina

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also…

Statistical Mechanics · Physics 2014-05-27 Jerome P. Nilmeier , Gavin E. Crooks , David D. L. Minh , John D. Chodera

Although the applications of Non-Homogeneous Poisson Processes to model and study the threshold overshoots of interest in different time series of measurements have proven to provide good results, they needed to be complemented with an…

Applications · Statistics 2023-09-15 Biviana Marcela Suárez-Sierra , Arrigo Coen , Carlos Alberto Taimal