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Framework of fully integrated hybrid systems
(Springer U K, 2012-02)
A framework of fully integrated hybrid systems (HSs) is proposed for the development and management of HS which involve databases, advanced user interfaces, symbolic systems, and artificial neural networks. This framework ...
MIANN models of networks of biochemical reactions, ecosystems, and U.S. Supreme Court with Balaban-Markov indices
(Bentham Science, 2015)
[Abstract] We can use Artificial Neural Networks (ANNs) and graph Topological Indices (TIs) to seek structure-property relationship. Balabans’ J index is one of the classic TIs for chemo-informatics studies. We used here ...
Experimental Study and ANN Dual-Time Scale Perturbation Model of Electrokinetic Properties of Microbiota
(Frontiers Science, 2017-06-30)
[Abstract] The electrokinetic properties of the rumen microbiota are involved in cell surface adhesion and microbial metabolism. An in vitro study was carried out in batch culture to determine the effects of three levels ...
MIANN models in medicinal, physical and organic chemistry
(Bentham, 2013)
[Abstract] Reducing costs in terms of time, animal sacrifice, and material resources with computational methods has become a promising goal in Medicinal, Biological, Physical and Organic Chemistry. There are many computational ...
Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution
(World Scientific, 2015-04-06)
[Abstract] Artificial Neuron–Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way ...
Net-Net AutoML Selection of Artificial Neural Network Topology for Brain Connectome Prediction
(MDPI, 2020-02-14)
[Abstract]
Brain Connectome Networks (BCNs) are defined by brain cortex regions (nodes) interacting with others by electrophysiological co-activation (edges). The experimental prediction of new interactions in BCNs ...
Machine Learning Techniques for Single Nucleotide Polymorphism—Disease Classification Models in Schizophrenia
(Molecular Diversity Preservation International, 2010)
[Abstract] Single nucleotide polymorphisms (SNPs) can be used as inputs in disease computational studies such as pattern searching and classification models. Schizophrenia is an example of a complex disease with an important ...
Artificial Neural Networks Manipulation Server: Research on the Integration of Databases and Artificial Neural Networks
(Springer U K, 2002-06)
This paper proposes a new whole and distributed integration approach between Artificial Neural Networks (ANNs) and Databases (DBs) taking into account the different stages of the former’s lifecycle (training, test and ...
Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
(MDPI, 2016-08-11)
[Abstract] Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other ...
Artificial glial cells in artificial neuronal networks: a systematic review
(Springer Nature, 2023-11)
[Abstract]: The concept of tripartite synapses has revolutionized the world of neuroscience and the way we understand how information is transmitted in the brain. Since its discovery, some research groups have incorporated ...