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Models, Biological

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A bio-lattice deep learning framework for modeling discrete biological materials.

Journal of the mechanical behavior of biomedical materials
Biological tissues dynamically adapt their mechanical properties at the microscale in response to stimuli, often governed by discrete interacting mechanisms that dictate the material's behavior at the macroscopic scale. An approach to model the discr...

Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model.

Scientific reports
Various modelling techniques are available to understand the temporal and spatial variations of the phenology of species. Scientists often rely on correlative models, which establish a statistical relationship between a response variable (such as spe...

Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.

Computers in biology and medicine
This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require careful anticoagulation management. With rising rates of diabetes and cardiovascular diseases, understanding the factors influencing warfarin therapy...

Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling.

Computers in biology and medicine
We present a built-in physics neural network architecture, known as inelastic Constitutive Artificial Neural Network (iCANN), to discover the inelastic phenomenon of tensional homeostasis. In this course, identifying the optimal model and material pa...

I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation.

Journal of the Royal Society, Interface
Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organism's brain, body and environment. Insects, despite their limited computational resources, demonstrate rema...

Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI.

CPT: pharmacometrics & systems pharmacology
A growing number of covariate modeling methods have been proposed in the field of popPK modeling, but limited information exists on how they all compare. The objective of this study was to perform a systematic review of all popPK covariate modeling m...

Addressing data uncertainty of Caulobacter crescentus cell cycles using hybrid Petri nets with fuzzy kinetics.

Computers in biology and medicine
Studying and analysing the various phases and key proteins of cell cycles is essential for the understanding of cell development and differentiation. To this end, mechanistic models play an important role towards a system level understanding of the i...

Evaluating the synergistic use of advanced liver models and AI for the prediction of drug-induced liver injury.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Drug-induced liver injury (DILI) is a leading cause of acute liver failure. Hepatotoxicity typically occurs only in a subset of individuals after prolonged exposure and constitutes a major risk factor for the termination of drug develop...

Plant-inspired decentralized controller for robust orientation control of soft robotic manipulators.

Bioinspiration & biomimetics
Due to the complexity of deformations in soft manipulators, achieving precise control of their orientation is particularly challenging, especially in the presence of external disturbances and human interactions. Inspired by the decentralized growth m...

Resilience of hierarchical actuators highlighted by a myosin-to-muscle mock-up.

Bioinspiration & biomimetics
Skeletal muscle is the main actuator of various families of vertebrates (mammals, fish, reptiles). It displays remarkable robustness to micro-damage, that supposedly originates both from its redundant hierarchical structure and its nervous command. A...