AIMC Topic: Models, Biological

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AI: A transformative opportunity in cell biology.

Molecular biology of the cell
The success of artificial intelligence (AI) algorithms in predicting protein structure and more recently, protein interactions, demonstrates the power and potential of machine learning and AI for advancing and accelerating biomedical research. As cel...

Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets.

Briefings in bioinformatics
Modelling biological systems depends on the availability of data and components of the system at hand. As our understanding of these systems evolves, the ability to gradually refine models by adding new components of different formalisms covering sto...

Moving in an Uncertain World: Robust and Adaptive Control of Locomotion from Organisms to Machine Intelligence.

Integrative and comparative biology
Whether walking, running, slithering, or flying, organisms display a remarkable ability to move through complex and uncertain environments. In particular, animals have evolved to cope with a host of uncertainties-both of internal and external origin-...

Process-Informed Neural Networks: A Hybrid Modelling Approach to Improve Predictive Performance and Inference of Neural Networks in Ecology and Beyond.

Ecology letters
Despite deep learning being state of the art for data-driven model predictions, its application in ecology is currently subject to two important constraints: (i) deep-learning methods are powerful in data-rich regimes, but in ecology data are typical...

From Behavior to Bio-Inspiration: Aerial Reorientation and Multi-Plane Stability in Kangaroo Rats, Computational Models, and Robots.

Integrative and comparative biology
Tails play essential roles in functions related to locomotor stability and maneuverability among terrestrial and arboreal animals. In kangaroo rats, bipedal hopping rodents, tails are used as effective inertial appendages for stability in hopping, bu...

Toward a foundation model of causal cell and tissue biology with a Perturbation Cell and Tissue Atlas.

Cell
Comprehensively charting the biologically causal circuits that govern the phenotypic space of human cells has often been viewed as an insurmountable challenge. However, in the last decade, a suite of interleaved experimental and computational technol...

Biomimetic Synchronization in Biciliated Robots.

Physical review letters
Direct mechanical coupling is known to be critical for establishing synchronization among cilia. However, the actual role of the connections is still elusive-partly because controlled experiments in living samples are challenging. Here, we employ an ...

Surrogate Simulation of Subject-Specific Lateral Pinch via Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Musculoskeletal modeling and simulation is often a lengthy and computationally expensive process, particularly when developing and using personalized models. We present a deep learning-based adaptive surrogate model for lateral pinch, which accepts b...

Machine learning framework to predict pharmacokinetic profile of small molecule drugs based on chemical structure.

Clinical and translational science
Accurate prediction of a new compound's pharmacokinetic (PK) profile is pivotal for the success of drug discovery programs. An initial assessment of PK in preclinical species and humans is typically performed through allometric scaling and mathematic...

Pressure-Based Soft Agents.

Artificial life
Biological agents have bodies that are composed mostly of soft tissue. Researchers have resorted to soft bodies to investigate Artificial Life (ALife)-related questions; similarly, a new era of soft-bodied robots has just begun. Nevertheless, because...