AIMC Topic: Models, Biological

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Investigation of machine learning algorithms for taxonomic classification of marine metagenomes.

Microbiology spectrum
Taxonomic profiling of microbial communities is essential to model microbial interactions and inform habitat conservation. This work develops approaches in constructing training/testing data sets from publicly available marine metagenomes and evaluat...

Multi-Label Local to Global Learning: A Novel Learning Paradigm for Chest X-Ray Abnormality Classification.

IEEE journal of biomedical and health informatics
Deep neural network (DNN) approaches have shown remarkable progress in automatic Chest X-rays classification. However, existing methods use a training scheme that simultaneously trains all abnormalities without considering their learning priority. In...

Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning.

Annals of biomedical engineering
The large amount of training samples required to develop a deep learning brain injury model demands enormous computational resources. Here, we study how a transformer neural network (TNN) of high accuracy can be used to efficiently generate pretraini...

An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

Computer methods in biomechanics and biomedical engineering
The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forces and chemical reactions in order to release nutrients. All ingested items, including our nutrition, should first pass through the stomach, making it...

Modeling of astaxanthin biosynthesis via machine learning, mathematical and metabolic network modeling.

Critical reviews in biotechnology
Natural astaxanthin is synthesized by diverse organisms including: bacteria, fungi, microalgae, and plants involving complex cellular processes, which depend on numerous interrelated parameters. Nonetheless, existing knowledge regarding astaxanthin b...

Intelligent solution predictive networks for non-linear tumor-immune delayed model.

Computer methods in biomechanics and biomedical engineering
In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the immune system (cytotoxic T lymphocytes, T helper cells), where the delays portray the times required fo...

Bridging the gap between mechanistic biological models and machine learning surrogates.

PLoS computational biology
Mechanistic models have been used for centuries to describe complex interconnected processes, including biological ones. As the scope of these models has widened, so have their computational demands. This complexity can limit their suitability when r...

Coupling machine learning and epidemiological modelling to characterise optimal fungicide doses when fungicide resistance is partial or quantitative.

Journal of the Royal Society, Interface
Increasing fungicide dose tends to lead to better short-term control of plant diseases. However, high doses select more rapidly for fungicide resistant strains, reducing long-term disease control. When resistance is qualitative and complete-i.e. resi...

Artificial Intelligence-Based Quantitative Structure-Property Relationship Model for Predicting Human Intestinal Absorption of Compounds with Serotonergic Activity.

Molecular pharmaceutics
Oral medicines represent the largest pharmaceutical market area. To achieve a therapeutic effect, a drug must penetrate the intestinal walls, the main absorption site for orally delivered active pharmaceutical ingredients (APIs). Indeed, predicting d...

Constrained disorder principle-based variability is fundamental for biological processes: Beyond biological relativity and physiological regulatory networks.

Progress in biophysics and molecular biology
The constrained disorder principle (CDP) defines systems based on their degree of disorder bounded by dynamic boundaries. The principle explains stochasticity in living and non-living systems. Denis Noble described the importance of stochasticity in ...