Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Murrugarra, David"'
Many systems in biology, physics, and engineering are modeled by nonlinear dynamical systems where the states are usually unknown and only a subset of the state variables can be physically measured. Can we understand the full system from what we meas
Externí odkaz:
http://arxiv.org/abs/2408.00143
Autor:
Kadelka, Claus, Murrugarra, David
Biological networks such as gene regulatory networks possess desirable properties. They are more robust and controllable than random networks. This motivates the search for structural and dynamical features that evolution has incorporated in biologic
Externí odkaz:
http://arxiv.org/abs/2402.09703
Autor:
Murrugarra, David, Veliz-Cuba, Alan, Dimitrova, Elena, Kadelka, Claus, Wheeler, Matthew, Laubenbacher, Reinhard
The concept of control is crucial for effectively understanding and applying biological network models. Key structural features relate to control functions through gene regulation, signaling, or metabolic mechanisms, and computational models need to
Externí odkaz:
http://arxiv.org/abs/2401.12477
Autor:
Wheeler, Matthew, Kadelka, Claus, Veliz-Cuba, Alan, Murrugarra, David, Laubenbacher, Reinhard
Boolean networks have been used in a variety of settings, as models for general complex systems as well as models of specific systems in diverse fields, such as biology, engineering, and computer science. Traditionally, their properties as dynamical
Externí odkaz:
http://arxiv.org/abs/2402.00022
Publikováno v:
Physica D: Nonlinear Phenomena, 451, 133775, 2023
Stability is an important characteristic of network models that has implications for other desirable aspects such as controllability. The stability of a Boolean network depends on various factors, such as the topology of its wiring diagram and the ty
Externí odkaz:
http://arxiv.org/abs/2209.02044
Autor:
Kadelka, Claus, Laubenbacher, Reinhard, Murrugarra, David, Veliz-Cuba, Alan, Wheeler, Matthew
This paper presents the foundation for a decomposition theory for Boolean networks, a type of discrete dynamical system that has found a wide range of applications in the life sciences, engineering, and physics. Given a Boolean network satisfying cer
Externí odkaz:
http://arxiv.org/abs/2206.04217
Autor:
Plaugher, Daniel1 (AUTHOR) plaugher_dr@uky.edu, Murrugarra, David2 (AUTHOR)
Publikováno v:
NPJ Systems Biology & Applications. 7/13/2024, Vol. 10 Issue 1, p1-11. 11p.
Publikováno v:
Automatica, 146 (2022)
Boolean functions can be represented in many ways including logical forms, truth tables, and polynomials. Additionally, Boolean functions have different canonical representations such as minimal disjunctive normal forms. Other canonical representatio
Externí odkaz:
http://arxiv.org/abs/2106.06580
Publikováno v:
In Physica D: Nonlinear Phenomena September 2023 451
Improving RNA secondary structure prediction via state inference with deep recurrent neural networks
Publikováno v:
Computational and Mathematical Biophysics, 8(1), 36-50, 2020
The problem of determining which nucleotides of an RNA sequence are paired or unpaired in the secondary structure of an RNA, which we call RNA state inference, can be studied by different machine learning techniques. Successful state inference of RNA
Externí odkaz:
http://arxiv.org/abs/1906.10819