AIMC Topic: Algorithms

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A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.

International journal of molecular sciences
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous publ...

Accuracy of automated classification of major depressive disorder as a function of symptom severity.

NeuroImage. Clinical
BACKGROUND: Growing evidence documents the potential of machine learning for developing brain based diagnostic methods for major depressive disorder (MDD). As symptom severity may influence brain activity, we investigated whether the severity of MDD ...

Stability analysis of switched cellular neural networks: A mode-dependent average dwell time approach.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the exponential stability of switched cellular neural networks by using the mode-dependent average dwell time (MDADT) approach. This method is quite different from the traditional average dwell time (ADT) method in permitting eac...

Optimization for Service Routes of Pallet Service Center Based on the Pallet Pool Mode.

Computational intelligence and neuroscience
Service routes optimization (SRO) of pallet service center should meet customers' demand firstly and then, through the reasonable method of lines organization, realize the shortest path of vehicle driving. The routes optimization of pallet service ce...

Driving a Semiautonomous Mobile Robotic Car Controlled by an SSVEP-Based BCI.

Computational intelligence and neuroscience
Brain-computer interfaces represent a range of acknowledged technologies that translate brain activity into computer commands. The aim of our research is to develop and evaluate a BCI control application for certain assistive technologies that can be...

Statistical learning theory for high dimensional prediction: Application to criterion-keyed scale development.

Psychological methods
Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in "big data" problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a larg...

Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

Genetics and molecular research : GMR
Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks...

CLASH: Complementary Linkage with Anchoring and Scoring for Heterogeneous biomolecular and clinical data.

BMC medical informatics and decision making
BACKGROUND: The study on disease-disease association has been increasingly viewed and analyzed as a network, in which the connections between diseases are configured using the source information on interactome maps of biomolecules such as genes, prot...

Improved Correction of Atmospheric Pressure Data Obtained by Smartphones through Machine Learning.

Computational intelligence and neuroscience
A correction method using machine learning aims to improve the conventional linear regression (LR) based method for correction of atmospheric pressure data obtained by smartphones. The method proposed in this study conducts clustering and regression ...

Independent Component Analysis-Support Vector Machine-Based Computer-Aided Diagnosis System for Alzheimer's with Visual Support.

International journal of neural systems
Computer-aided diagnosis (CAD) systems constitute a powerful tool for early diagnosis of Alzheimer's disease (AD), but limitations on interpretability and performance exist. In this work, a fully automatic CAD system based on supervised learning meth...