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Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.

PLoS computational biology
There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilay...

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals.

Computational intelligence and neuroscience
Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlie...
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Consensus Kernel -Means Clustering for Incomplete Multiview Data.

Computational intelligence and neuroscience
Multiview clustering aims to improve clustering performance through optimal integration of information from multiple views. Though demonstrating promising performance in various applications, existing multiview clustering algorithms cannot effectivel...

Early Detection of Ureteropelvic Junction Obstruction Using Signal Analysis and Machine Learning: A Dynamic Solution to a Dynamic Problem.

The Journal of urology
PURPOSE: We sought to define features that describe the dynamic information in diuresis renograms for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction.

Machine learning applied to neuroimaging for diagnosis of adult classic Chiari malformation: role of the basion as a key morphometric indicator.

Journal of neurosurgery
OBJECTIVE The current diagnostic criterion for Chiari malformation Type I (CM-I), based on tonsillar herniation (TH), includes a diversity of patients with amygdalar descent that may be caused by a variety of factors. In contrast, patients presenting...

Predicting pathogenic genes for primary myelofibrosis based on a system‑network approach.

Molecular medicine reports
The aim of the present study was to predict pathogenic genes for primary myelofibrosis (PMF) using a system‑network approach by combining protein‑protein interaction (PPI) network and gene expression data with known pathogenic genes. PMF gene express...

Learning-based deformable registration for infant MRI by integrating random forest with auto-context model.

Medical physics
PURPOSE: Accurately analyzing the rapid structural evolution of human brain in the first year of life is a key step in early brain development studies, which requires accurate deformable image registration. However, due to (a) dynamic appearance and ...

A New Approach to Predict user Mobility Using Semantic Analysis and Machine Learning.

Journal of medical systems
Mobility prediction is a technique in which the future location of a user is identified in a given network. Mobility prediction provides solutions to many day-to-day life problems. It helps in seamless handovers in wireless networks to provide better...

A deep convolutional neural network for classification of red blood cells in sickle cell anemia.

PLoS computational biology
Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological...