AIMC Topic: Neural Networks, Computer

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Molecular graph convolutions: moving beyond fingerprints.

Journal of computer-aided molecular design
Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structur...

Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
We present a novel method to segment retinal images using ensemble learning based convolutional neural network (CNN) architectures. An entropy sampling technique is used to select informative points thus reducing computational complexity while perfor...

Predicting the errors of predicted local backbone angles and non-local solvent- accessibilities of proteins by deep neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Backbone structures and solvent accessible surface area of proteins are benefited from continuous real value prediction because it removes the arbitrariness of defining boundary between different secondary-structure and solvent-accessibil...

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

Biotechnology progress
This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating pa...

BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species.

BioMed research international
MicroRNAs (miRNAs) are a set of short (21-24 nt) noncoding RNAs that play significant regulatory roles in cells. In the past few years, research on miRNA-related problems has become a hot field of bioinformatics because of miRNAs' essential biologica...

Design and Hardware Implementation of a New Chaotic Secure Communication Technique.

PloS one
In this paper, a scheme for chaotic modulation secure communication is proposed based on chaotic synchronization of an improved Lorenz system. For the first time, the intensity limit and stability of the transmitted signal, the characteristics of bro...

Implementation of Imitation Learning using Natural Learner Central Pattern Generator Neural Networks.

Neural networks : the official journal of the International Neural Network Society
In this paper a new design of neural networks is introduced, which is able to generate oscillatory patterns. The fundamental building block of the neural network is O-neurons that can generate an oscillation in its transfer functions. Since the natur...

Improving Detection Accuracy of Memristor-Based Bio-Signal Sensing Platform.

IEEE transactions on biomedical circuits and systems
Recently a novel neuronal activity sensor exploiting the intrinsic thresholded integrator capabilities of memristor devices has been proposed. Extracellular potentials captured by a standard bio-signal acquisition platform are fed into a memristive d...

Surface Adsorbed Antibody Characterization Using ToF-SIMS with Principal Component Analysis and Artificial Neural Networks.

Langmuir : the ACS journal of surfaces and colloids
Artificial neural networks (ANNs) form a class of powerful multivariate analysis techniques, yet their routine use in the surface analysis community is limited. Principal component analysis (PCA) is more commonly employed to reduce the dimensionality...

Network or regression-based methods for disease discrimination: a comparison study.

BMC medical research methodology
BACKGROUND: In stark contrast to network-centric view for complex disease, regression-based methods are preferred in disease prediction, especially for epidemiologists and clinical professionals. It remains a controversy whether the network-based met...