AIMC Topic: Models, Biological

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The application of machine learning to the modelling of percutaneous absorption: an overview and guide.

SAR and QSAR in environmental research
Machine learning (ML) methods have been applied to the analysis of a range of biological systems. This paper reviews the application of these methods to the problem domain of skin permeability and addresses critically some of the key issues. Specific...

Constructing query-driven dynamic machine learning model with application to protein-ligand binding sites prediction.

IEEE transactions on nanobioscience
We are facing an era with annotated biological data rapidly and continuously generated. How to effectively incorporate new annotated data into the learning step is crucial for enhancing the performance of a bioinformatics prediction model. Although m...

Role of moving average analysis for development of multi-target (Q)SAR models.

Mini reviews in medicinal chemistry
In modern drug discovery era, multi target- quantitative structure activity relationship [mt- (Q)SAR] approaches have emerged as novel and powerful alternatives in the field of in-silico drug design so as to facilitate the discovery of new chemical e...

Exoskeleton control for lower-extremity assistance based on adaptive frequency oscillators: adaptation of muscle activation and movement frequency.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
In this article, we analyze a novel strategy for assisting the lower extremities based on adaptive frequency oscillators. Our aim is to use the control algorithm presented here as a building block for the control of powered lower-limb exoskeletons. T...

Computer-based prediction of mitochondria-targeting peptides.

Methods in molecular biology (Clifton, N.J.)
Computational methods are invaluable when protein sequences, directly derived from genomic data, need functional and structural annotation. Subcellular localization is a feature necessary for understanding the protein role and the compartment where t...

Adaptive neuro-fuzzy inference system for real-time monitoring of integrated-constructed wetlands.

Water science and technology : a journal of the International Association on Water Pollution Research
Monitoring large-scale treatment wetlands is costly and time-consuming, but required by regulators. Some analytical results are available only after 5 days or even longer. Thus, adaptive neuro-fuzzy inference system (ANFIS) models were developed to p...

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.)
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...

Using neural networks to understand the information that guides behavior: a case study in visual navigation.

Methods in molecular biology (Clifton, N.J.)
To behave in a robust and adaptive way, animals must extract task-relevant sensory information efficiently. One way to understand how they achieve this is to explore regularities within the information animals perceive during natural behavior. In thi...

Modulation of grasping force in prosthetic hands using neural network-based predictive control.

Methods in molecular biology (Clifton, N.J.)
This chapter describes the implementation of a neural network-based predictive control system for driving a prosthetic hand. Nonlinearities associated with the electromechanical aspects of prosthetic devices present great challenges for precise contr...