AIMC Topic: Animals

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Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion.

NPJ systems biology and applications
Different cell types aggregate and sort into hierarchical architectures during the formation of animal tissues. The resulting spatial organization depends (in part) on the strength of adhesion of one cell type to itself relative to other cell types. ...

Supervised learning algorithm for analysis of communication signals in the weakly electric fish Apteronotus leptorhynchus.

Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology
Signal analysis plays a preeminent role in neuroethological research. Traditionally, signal identification has been based on pre-defined signal (sub-)types, thus being subject to the investigator's bias. To address this deficiency, we have developed ...

Identification of the trade-off between speed and efficiency in undulatory swimming using a bio-inspired robot.

Scientific reports
Anguilliform swimmers, like eels or lampreys, are highly efficient swimmers. Key to understanding their performances is the relationship between the body's kinematics and resulting swimming speed and efficiency. But, we cannot prescribe kinematics to...

Improved patient mortality predictions in emergency departments with deep learning data-synthesis and ensemble models.

Scientific reports
The triage process in emergency departments (EDs) relies on the subjective assessment of medical practitioners, making it unreliable in certain aspects. There is a need for a more accurate and objective algorithm to determine the urgency of patients....

A synergistic future for AI and ecology.

Proceedings of the National Academy of Sciences of the United States of America
Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in comp...

Predictive learning by a burst-dependent learning rule.

Neurobiology of learning and memory
Humans and other animals are able to quickly generalize latent dynamics of spatiotemporal sequences, often from a minimal number of previous experiences. Additionally, internal representations of external stimuli must remain stable, even in the prese...

Integrative soft computing approaches for optimizing thermal energy performance in residential buildings.

PloS one
As is known, early prediction of thermal load in buildings can give valuable insight to engineers and energy experts in order to optimize the building design. Although different machine learning models have been promisingly employed for this problem,...

VenomPred 2.0: A Novel Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules.

Journal of chemical information and modeling
The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particu...