AIMC Topic: Models, Biological

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A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

Bio Systems
In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter es...

Adaptive Local Information Transfer in Random Boolean Networks.

Artificial life
Living systems such as gene regulatory networks and neuronal networks have been supposed to work close to dynamical criticality, where their information-processing ability is optimal at the whole-system level. We investigate how this global informati...

Evolution of Joint-Level Control for Quadrupedal Locomotion.

Artificial life
We investigate a hierarchical approach to robot control inspired by joint-level control in animals. The method combines a high-level controller, consisting of an artificial neural network (ANN), with joint-level controllers based on digital muscles. ...

Arbitrary Symmetric Running Gait Generation for an Underactuated Biped Model.

PloS one
This paper investigates generating symmetric trajectories for an underactuated biped during the stance phase of running. We use a point mass biped (PMB) model for gait analysis that consists of a prismatic force actuator on a massless leg. The signif...

Modeling of glucose release from native and modified wheat starch gels during in vitro gastrointestinal digestion using artificial intelligence methods.

International journal of biological macromolecules
Estimation of the amounts of glucose release (AGR) during gastrointestinal digestion can be useful to identify food of potential use in the diet of individuals with diabetes. In this work, adaptive neuro-fuzzy inference system (ANFIS), genetic algori...

SVM and SVM Ensembles in Breast Cancer Prediction.

PloS one
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among...

Highly predictive and interpretable models for PAMPA permeability.

Bioorganic & medicinal chemistry
Cell membrane permeability is an important determinant for oral absorption and bioavailability of a drug molecule. An in silico model predicting drug permeability is described, which is built based on a large permeability dataset of 7488 compound ent...

Dynamic predictive model for growth of Salmonella spp. in scrambled egg mix.

Food microbiology
Liquid egg products can be contaminated with Salmonella spp. during processing. A dynamic model for the growth of Salmonella spp. in scrambled egg mix - high solids (SEM) was developed and validated. SEM was prepared and inoculated with ca. 2 log CFU...

Spatial dispersal of bacterial colonies induces a dynamical transition from local to global quorum sensing.

Physical review. E
Bacteria communicate using external chemical signals called autoinducers (AI) in a process known as quorum sensing (QS). QS efficiency is reduced by both limitations of AI diffusion and potential interference from neighboring strains. There is thus a...

Feature Fusion Based SVM Classifier for Protein Subcellular Localization Prediction.

Journal of integrative bioinformatics
For the importance of protein subcellular localization in different branches of life science and drug discovery, researchers have focused their attentions on protein subcellular localization prediction. Effective representation of features from prote...