Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Significant progress has been made towards engineering both single-cell and multi-cellular systems through a combination of synthetic and systems biology, nanobiotechnology, pharmaceutical science, and computational approaches. However, our ability to engineer systems that begin to approach the complexity of natural pathways is severely limited by important challenges, e.g. due to noise, or the fluctuations in gene expression and molecular species at multiple scales (e.g. both intra- and inter-cellular fluctuations). This barrier to engineering requires that biological noise be recognized as a design element with fundamentals that can be actively controlled. Here we highlight studies of an emerging discipline that collectively strives to engineer noise towards predictive stochastic design using interdisciplinary approaches at multiple-scales in diverse living systems.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481707 | PMC |
| http://dx.doi.org/10.1063/1.5025033 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Gene mutation estimations via mutual information and Ewens sampling based CNN & machine learning algorithms.
J Appl Stat
February 2025
Department of Mathematics and State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, People's Republic of China.
We conduct gene mutation rate estimations via developing mutual information and Ewens sampling based convolutional neural network (CNN) and machine learning algorithms. More precisely, we develop a systematic methodology through constructing a CNN. Meanwhile, we develop two machine learning algorithms to study protein production with target gene sequences and protein structures.
View Article and Find Full Text PDFUsing Confidence Distributions in Final and Interim Analyses for Single-Arm Studies or Platform Trials Consisting of Single-Arm Studies.
Stat Med
September 2025
Berry Consultants, Abingdon, UK.
Confidence distributions are a frequentist alternative to the Bayesian posterior distribution. These confidence distributions have received more attention in the recent past because of their simplicity. In rare diseases, oncology, or in pediatric drug development, single-arm trials, or platform trials consisting of a series of single-arm trials are increasingly being used, both to establish proof-of-concept and to provide pivotal evidence for a marketing application.
View Article and Find Full Text PDFPit Morphology, Dissolution Kinetics, and Gas Generation Monitored in Real Time during Localized Anodic Aluminum Corrosion.
J Am Chem Soc
September 2025
Institute of Materials, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
Localized corrosion in metallic materials is a stochastic phenomenon that causes irreversible structural failure. Its initiation, which occurs at the solid-liquid interface on the nanometer scale, remains difficult to predict and challenging to characterize. Herein, we describe an experimental platform that exploits advances in electrochemical liquid-phase scanning and transmission electron microscopy (LPSEM and LPTEM) to study pitting corrosion of thin-film pure aluminum in a saline environment in real time.
View Article and Find Full Text PDFUnravelling the polysorbate 20 composition: A fusion of UPLC-MS analysis and stochastic modelling.
Eur J Pharm Biopharm
September 2025
RaDes GmbH, Schnackenburgallee 114, 22525 Hamburg, Germany. Electronic address:
Polysorbate 20 (PS20) is one of the most commonly used non-ionic surfactants in cosmetics, pharmaceuticals and food products. Considered as biocompatible and non-irritating, it is further valued for its solubilising and protein stabilising properties. PS20 is manufactured through a multi-stage reaction of sorbitol with various fatty acids and ethylene oxide, resulting in a complex mixture of components with different molecular weights and polarity.
View Article and Find Full Text PDFTransfer Learning of Stochastic Kriging for Individualized Prediction.
IEEE Trans Pattern Anal Mach Intell
September 2025
Stochastic Kriging (SK) is a generalized variant of Gaussian process regression, and it is developed for dealing with non-i.i.d.
View Article and Find Full Text PDF