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Dynamic gene-regulatory networks are complex since the number of potential components involved in the system is very large. Estimating dynamic networks is an important task because they compromise valuable information about interactions…

Methodology · Statistics 2012-05-15 Antonino Abbruzzo , Ernst Wit

We propose and discuss a novel strategy for protein design. The method is based on recent theoretical advancements which showed the importance to treat carefully the conformational free energy of designed sequences. In this work we show how…

Statistical Mechanics · Physics 2009-10-31 A. Rossi , A. Maritan , C. Micheletti

We analyze large systems of interacting proteins, using techniques from the non-equilibrium statistical mechanics of disordered many-particle systems. Apart from protein production and removal, the most relevant microscopic processes in the…

Molecular Networks · Quantitative Biology 2015-05-14 A. C. C. Coolen , S. Rabello

Synthetic biology is a growing interdisciplinary field, with far-reaching applications, which aims to design biochemical systems that behave in a desired manner. With the advancement of strand-displacement DNA computing, a large class of…

Molecular Networks · Quantitative Biology 2017-06-21 Tomislav Plesa , Konstantinos C. Zygalakis , David F. Anderson , Radek Erban

We study a genetic regulatory network model developed to demonstrate that genetic robustness can evolve through stabilizing selection for optimal phenotypes. We report preliminary results on whether such selection could result in a…

Molecular Networks · Quantitative Biology 2010-12-07 Volkan Sevim , Per Arne Rikvold

Generative models emerge as promising candidates for novel sequence-data driven approaches to protein design, and for the extraction of structural and functional information about proteins deeply hidden in rapidly growing sequence…

Biomolecules · Quantitative Biology 2021-11-10 Jeanne Trinquier , Guido Uguzzoni , Andrea Pagnani , Francesco Zamponi , Martin Weigt

Nonlinear systems are capable of displaying complex behavior even if this is the result of a small number of interacting time scales. A widely studied case is when complex dynamics emerges out of a nonlinear system being forced by a simple…

Quantitative Methods · Quantitative Biology 2015-06-01 Leandro M. Alonso

Machine-learning models that learn from data to predict how protein sequence encodes function are emerging as a useful protein engineering tool. However, when using these models to suggest new protein designs, one must deal with the vast…

Quantitative Methods · Quantitative Biology 2021-07-07 Brian L. Hie , Kevin K. Yang

The past decade has seen a revived interest in the unavoidable or intrinsic noise in biochemical and genetic networks arising from the finite copy number of the participating species. That is, rather than modeling regulatory networks in…

Molecular Networks · Quantitative Biology 2015-03-17 Aleksandra M. Walczak , Andrew Mugler , Chris H. WIggins

Proteins are macromolecules that perform essential functions in all living organisms. Designing novel proteins with specific structures and desired functions has been a long-standing challenge in the field of bioengineering. Existing…

Biomolecules · Quantitative Biology 2023-03-03 Chence Shi , Chuanrui Wang , Jiarui Lu , Bozitao Zhong , Jian Tang

A key goal of systems biology is the predictive mathematical description of gene regulatory circuits. Different approaches are used such as deterministic and stochastic models, models that describe cell growth and division explicitly or…

Molecular Networks · Quantitative Biology 2012-10-12 Rahul Marathe , Veronika Bierbaum , David Gomez , Stefan Klumpp

Constructing gene regulatory networks is a fundamental task in systems biology. We introduce a Gaussian reciprocal graphical model for inference about gene regulatory relationships by integrating mRNA gene expression and DNA level…

Methodology · Statistics 2016-07-26 Yang Ni , Yuan Ji , Peter Mueller

There is an abundance of prior research on the optimization of production systems, but there is a research gap when it comes to optimizing which components should be included in a design, and how they should be connected. To overcome this…

Neural and Evolutionary Computing · Computer Science 2024-02-05 N. Paape , J. A. W. M. van Eekelen , M. A. Reniers

In many organisms the expression levels of each gene are controlled by the activation levels of known "Transcription Factors" (TF). A problem of considerable interest is that of estimating the "Transcription Regulation Networks" (TRN)…

Applications · Statistics 2010-11-09 Gareth M. James , Chiara Sabatti , Nengfeng Zhou , Ji Zhu

This paper proposes a new mathematical approach to characterize native protein structures based on the discrete differential geometry of tetrahedron tiles. In the approach, local structure of proteins is classified into finite types…

Biomolecules · Quantitative Biology 2007-05-23 Naoto Morikawa

In this work, we investigate an indirect approach for the numerical solution of optimal control problems via neural networks. A customized neural network is constructed, where optimal state, co-state and control trajectories are…

Optimization and Control · Mathematics 2025-02-13 Mominul Rubel , Gabriel Nicolosi

The Gene or DNA sequence in every cell does not control genetic properties on its own; Rather, this is done through translation of DNA into protein and subsequent formation of a certain 3D structure. The biological function of a protein is…

Computational Engineering, Finance, and Science · Computer Science 2019-05-30 Leila Khalatbari , Mohammad Reza Kangavari , Saeid Hosseini , Hongzhi Yin , Ngai-Man Cheung

With the needs of science and business, data sharing and re-use has become an intensive activity for various areas. In many cases, governance imposes rules concerning data use, but there is no existing computational technique to help…

Artificial Intelligence · Computer Science 2019-11-20 Rui Zhao , Malcolm Atkinson

This paper considers generalized linear models using rule-based features, also referred to as rule ensembles, for regression and probabilistic classification. Rules facilitate model interpretation while also capturing nonlinear dependences…

Machine Learning · Computer Science 2019-06-06 Dennis Wei , Sanjeeb Dash , Tian Gao , Oktay Günlük

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