AIMC Topic: Models, Biological

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An Ameliorated Prediction of Drug-Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features.

International journal of molecular sciences
The prediction of drug-target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper,...

Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

Scientific reports
Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study develop...

Identification of immune correlates of protection in Shigella infection by application of machine learning.

Journal of biomedical informatics
BACKGROUND: Immunologic correlates of protection are important in vaccine development because they give insight into mechanisms of protection, assist in the identification of promising vaccine candidates, and serve as endpoints in bridging clinical v...

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

International journal of neural systems
Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet t...

Blind Nonnegative Source Separation Using Biological Neural Networks.

Neural computation
Blind source separation-the extraction of independent sources from a mixture-is an important problem for both artificial and natural signal processing. Here, we address a special case of this problem when sources (but not the mixing matrix) are known...

A flight-phase terrain following control strategy for stable and robust hopping of a one-legged robot under large terrain variations.

Bioinspiration & biomimetics
This work demonstrates a simple, once per step, flight-control method for robots running on a planar unknown rough-terrain environment. The robot used to exemplify these control strategies is the ParkourBot, a spring loaded inverted pendulum (SLIP)-b...

Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network.

PLoS computational biology
Bacteria of many species rely on a simple molecule, the intracellular secondary messenger c-di-GMP (Bis-(3'-5')-cyclic dimeric guanosine monophosphate), to make a vital choice: whether to stay in one place and form a biofilm, or to leave it in search...

Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities.

Physical biology
Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely ...

Applying an artificial neural network model for developing a severity score for patients with hereditary amyloid polyneuropathy.

Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis
Hereditary (familial) amyloid polyneuropathy (FAP) is a systemic disease that includes a sensorimotor polyneuropathy related to transthyretin (TTR) mutations. So far, a scale designed to classify the severity of this disease has not yet been validate...

Optic flow-based collision-free strategies: From insects to robots.

Arthropod structure & development
Flying insects are able to fly smartly in an unpredictable environment. It has been found that flying insects have smart neurons inside their tiny brains that are sensitive to visual motion also called optic flow. Consequently, flying insects rely ma...