AIMC Topic: Animals

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Behavioural analysis of single-cell aneural ciliate, using machine learning approaches.

Journal of the Royal Society, Interface
There is still a significant gap between our understanding of neural circuits and the behaviours they compute-i.e. the computations performed by these neural networks (Carandini 2012 , 507-509. (doi:10.1038/nn.3043)). Cellular decision-making process...

Estimation of Bladder Pressure and Volume from the Neural Activity of Lumbosacral Dorsal Horn Using a Long-Short-Term-Memory-based Deep Neural Network.

Scientific reports
In this paper, we propose a deep recurrent neural network (DRNN) for the estimation of bladder pressure and volume from neural activity recorded directly from spinal cord gray matter neurons. The model was based on the Long Short-Term Memory (LSTM) a...

Hierarchical motor control in mammals and machines.

Nature communications
Advances in artificial intelligence are stimulating interest in neuroscience. However, most attention is given to discrete tasks with simple action spaces, such as board games and classic video games. Less discussed in neuroscience are parallel advan...

Multimodal deep representation learning for protein interaction identification and protein family classification.

BMC bioinformatics
BACKGROUND: Protein-protein interactions(PPIs) engage in dynamic pathological and biological procedures constantly in our life. Thus, it is crucial to comprehend the PPIs thoroughly such that we are able to illuminate the disease occurrence, achieve ...

Robust blind spectral unmixing for fluorescence microscopy using unsupervised learning.

PloS one
Due to the overlapping emission spectra of fluorophores, fluorescence microscopy images often have bleed-through problems, leading to a false positive detection. This problem is almost unavoidable when the samples are labeled with three or more fluor...

Deep learning improves automated rodent behavior recognition within a specific experimental setup.

Journal of neuroscience methods
Automated observation and analysis of rodent behavior is important to facilitate research progress in neuroscience and pharmacology. Available automated systems lack adaptivity and can benefit from advances in AI. In this work we compare a state-of-t...

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Preventive veterinary medicine
Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds is critical for the control of this disease. Exploratory machine learning techniques can uncover complex non-linear relationships and interactions wit...

Deep learning tools for the measurement of animal behavior in neuroscience.

Current opinion in neurobiology
Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capt...

Deep Ego-Motion Classifiers for Compound Eye Cameras.

Sensors (Basel, Switzerland)
Compound eyes, also known as insect eyes, have a unique structure. They have a hemispheric surface, and a lot of single eyes are deployed regularly on the surface. Thanks to this unique form, using the compound images has several advantages, such as ...

NNTox: Gene Ontology-Based Protein Toxicity Prediction Using Neural Network.

Scientific reports
With advancements in synthetic biology, the cost and the time needed for designing and synthesizing customized gene products have been steadily decreasing. Many research laboratories in academia as well as industry routinely create genetically engine...