AIMC Topic: Models, Biological

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Cumulative inhibition in neural networks.

Cognitive processing
We show how a multi-resolution network can model the development of acuity and coarse-to-fine processing in the mammalian visual cortex. The network adapts to input statistics in an unsupervised manner, and learns a coarse-to-fine representation by u...

Controllable switching between planar and helical flagellar swimming of a soft robotic sperm.

PloS one
Sperm cells undergo a wide variety of swimming patterns by a beating flagellum to maintain high speed regardless of the rheological and physical properties of the background fluid. In this work, we develop and control a soft robotic sperm that underg...

Force feasible set prediction with artificial neural network and musculoskeletal model.

Computer methods in biomechanics and biomedical engineering
Developing tools to predict the force capabilities of the human limbs through the Force Feasible Set (FFS) may be of great interest for robotic assisted rehabilitation and digital human modelling for ergonomics. Indeed, it could help to refine rehabi...

A computational method for prediction of xylanase enzymes activity in strains of Bacillus subtilis based on pseudo amino acid composition features.

PloS one
Xylanases are hydrolytic enzymes which based on physicochemical properties, structure, mode of action and substrate specificities are classified into various glycoside hydrolase (GH) families. The purpose of this study is to show that the activity of...

Assessment of specific versus combined purpose knowledge based models in prostate radiotherapy.

Journal of applied clinical medical physics
Knowledge-based planning (KBP) can be used to improve plan quality, planning speed, and reduce the inter-patient plan variability. KPB may also identify and reduce systematic variations in VMAT plans, something very important in multi-institutional c...

The hepatotoxic potential of protein kinase inhibitors predicted with Random Forest and Artificial Neural Networks.

Toxicology letters
Protein kinases (PKs) play a role in many pivotal aspects of cellular function. Dysregulation and mutations of protein kinases are involved in the development of different diseases, which might be treated by inhibition of the corresponding kinase. Pr...

Application of Machine Learning Techniques for Clinical Predictive Modeling: A Cross-Sectional Study on Nonalcoholic Fatty Liver Disease in China.

BioMed research international
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. Machine learning techniques were introduced to evaluate the optimal predictive clinical model of NAFLD.

Variable importance for sustaining macrophyte presence via random forests: data imputation and model settings.

Scientific reports
Data sets plagued with missing data and performance-affecting model parameters represent recurrent issues within the field of data mining. Via random forests, the influence of data reduction, outlier and correlated variable removal and missing data i...

A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites.

International journal of molecular sciences
Protein hydroxylation is one type of post-translational modifications (PTMs) playing critical roles in human diseases. It is known that protein sequence contains many uncharacterized residues of proline and lysine. The question that needs to be answe...

Modeling the Human Visuo-Motor System to Support Remote-Control Operation.

Sensors (Basel, Switzerland)
The working hypothesis in this project is that gaze interactions play a central role in structuring the joint control and guidance strategy of the human operator performing spatial tasks. Perceptual guidance and control is the idea that the visual an...