Results 81 to 90 of about 1,156,059 (330)

State feedback control design for Boolean networks [PDF]

BMC Systems Biology, 2016
Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the ...
Liu, Rongjie, Qian, Chunjiang, Liu, Shuqian, Jin, Yu-Fang   +3 more
openaire   +2 more sources

High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort

Advanced Science, EarlyView.
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño, Víctor M. de la Oliva Roque, Javier‐Ignacio Ramirez‐Lopez, David P. Kreil, Joaquín Dopazo, Carlos Loucera   +5 more
wiley   +1 more source

Target Control in Logical Models Using the Domain of Influence of Nodes

Frontiers in Physiology, 2018
Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies. Network control and its special case of target control, is a promising avenue toward developing
Gang Yang, Jorge Gómez Tejeda Zañudo, Jorge Gómez Tejeda Zañudo, Jorge Gómez Tejeda Zañudo, Réka Albert, Réka Albert   +5 more
doaj   +1 more source

Phenotype Control techniques for Boolean gene regulatory networks

Bulletin of Mathematical Biology, 2023
AbstractModeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What’s more, BNs provide a course-grained approach, not only to understanding molecular communications, but also for targeting pathway components that alter the long-term ...
Daniel Plaugher, David Murrugarra
openaire   +4 more sources

A Bottom‐Up Design Framework for Multifunctional Lattice Metamaterials

Advanced Science, EarlyView.
This study introduces a generative AI framework for designing multifunctional lattice metamaterials. The method combines 3D Gaussian voxel generation with deep learning, enabling greater design freedom and structural performance. The optimized lattice metamaterials achieve enhanced energy absorption by 40–200% compared to conventional structures and ...
Zongxin Hu, Quanqing Tao, Junhao Ding, Shuo Qu, Haitao Ye, Jun Wei Chua, Tianxiao Niu, Rui Li, Winston Wai Shing Ma, Haoming Mo, Hui Liu, Wei Zhai, Xinwei Li, Xu Song   +13 more
wiley   +1 more source

Spin Hall Nano‐Antenna

Advanced Science, EarlyView.
ABSTRACT The spin Hall effect is a well‐known phenomenon in spintronics that has found numerous applications in digital electronics (memory and logic), but relatively few in analog electronics. Practically the only analog application in widespread use is the spin Hall nano‐oscillator (SHNO) that delivers a high frequency alternating current or voltage ...
Raisa Fabiha, Pratap Kumar Pal, Michael Suche, Amrit Kumar Mondal, Erdem Topsakal, Anjan Barman, Supriyo Bandyopadhyay   +6 more
wiley   +1 more source

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis

Scientific Reports, 2023
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states.
Martin Kaltdorf, Tim Breitenbach, Stefan Karl, Maximilian Fuchs, David Komla Kessie, Eric Psota, Martina Prelog, Edita Sarukhanyan, Regina Ebert, Franz Jakob, Gudrun Dandekar, Muhammad Naseem, Chunguang Liang, Thomas Dandekar   +13 more
doaj   +1 more source

Kullback–Leibler Control in Boolean Control Networks

IEEE Transactions on Cybernetics
This article addresses the Kullback-Leibler (KL) control problem in Boolean control networks. In the considered problem, an extended stage cost function depending on the control inputs is introduced; in contrast to a stage cost of the conventional KL control problems in the Markov decision process cannot take into consideration the control inputs.
Mitsuru Toyoda, Yuhu Wu
openaire   +2 more sources

T Cell Exhaustion in Cancer Immunotherapy: Heterogeneity, Mechanisms, and Therapeutic Opportunities

Advanced Science, EarlyView.
T cell exhaustion limits immunotherapy efficacy. This article delineates its progression from stem‐like to terminally exhausted states, governed by persistent antigen, transcription factors, epigenetics, and metabolism. It maps the exhaustion landscape in the TME and proposes integrated reversal strategies, providing a translational roadmap to overcome
Yang Yu, Xiaoyu Yao, Qingyang Wang, Mengrui Yang, Runze Li, Jiangjiang Qin, Jing Zhuang, Changgang Sun   +7 more
wiley   +1 more source

Boolean versus continuous dynamics on simple two-gene modules

, 2010
We investigate the dynamical behavior of simple modules composed of two genes with two or three regulating connections. Continuous dynamics for mRNA and protein concentrations is compared to a Boolean model for gene activity.
A. V. Hill, Barbara Drossel, D. Del Vecchio, D. Del Vecchio, Eva Gehrmann, T. Chen, U. Alon   +6 more
core   +1 more source