Recurrent neural networks in synthetic cells: a route to autonomous molecular agents?

Front Bioeng Biotechnol

Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy.

Published: June 2023

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284608PMC
http://dx.doi.org/10.3389/fbioe.2023.1210334DOI Listing

Publication Analysis

Top Keywords

recurrent neural
4
neural networks
4
networks synthetic
4
synthetic cells
4
cells route
4
route autonomous
4
autonomous molecular
4
molecular agents?
4
recurrent
1
networks
1

Similar Publications

Background/objectives: Glioblastoma multiforme (GBM) is the most common high-grade primary brain cancer in adults. Despite efforts to advance treatment, GBM remains treatment resistant and inevitably progresses after first-line therapy. Induced neural stem cell (iNSC) therapy is a promising, personalized cell therapy approach that has been explored to circumvent challenges associated with the current GBM treatment.

View Article and Find Full Text PDF

Remaining useful life (RUL) prediction is a cornerstone of Prognostic and Health Management (PHM) for power machinery, playing a crucial role in ensuring the reliability and safety of these critical systems. In recent years, deep learning techniques have shown great promise in RUL prediction, providing more reliable and accurate outcomes. However, existing models often struggle with comprehensive feature extraction, especially in capturing the complex behavior of power machinery, where non-linear degradation patterns arise under varying operational conditions.

View Article and Find Full Text PDF

This paper presents a comparative study of different AI models for indoor positioning systems, emphasizing improvements in localization accuracy and processing time. This study examines Artificial Neural Networks (ANNs), Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNNs), and the Kalman filter using a real Received Signal Strength Indicator (RSSI) and 9-axis ICM-20948 sensor. An in-depth analysis is provided in this paper for data cleaning and feature selection to reduce errors for all the models.

View Article and Find Full Text PDF

This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descriptors, including MSER (Maximally Stable Extremal Regions), SURF (Speeded-Up Robust Features), distance transform, and DOF (Degrees of Freedom), were applied to skeleton points, while BRIEF (Binary Robust Independent Elementary Features), HOG (Histogram of Oriented Gradients), FAST (Features from Accelerated Segment Test), and Optical Flow were used on silhouettes or full-body points to capture both geometric and motion-based features.

View Article and Find Full Text PDF

Background/objectives: Strabismus is the most common ocular disorder of childhood. Three rare, recurrent genetic duplications have been associated with both esotropia and exotropia, but the mechanisms by which they contribute to strabismus are unknown. This work aims to investigate the mechanisms of the smallest of the three, a 23 kb duplication on chromosome 4 (hg38|4:25,554,985-25,578,843).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!