AIMC Topic: Software

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DANTE: Deep alternations for training neural networks.

Neural networks : the official journal of the International Neural Network Society
We present DANTE, a novel method for training neural networks using the alternating minimization principle. DANTE provides an alternate perspective to traditional gradient-based backpropagation techniques commonly used to train deep networks. It util...

Predicting protein model correctness in Coot using machine learning.

Acta crystallographica. Section D, Structural biology
Manually identifying and correcting errors in protein models can be a slow process, but improvements in validation tools and automated model-building software can contribute to reducing this burden. This article presents a new correctness score that ...

lncRNA_Mdeep: An Alignment-Free Predictor for Distinguishing Long Non-Coding RNAs from Protein-Coding Transcripts by Multimodal Deep Learning.

International journal of molecular sciences
Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex diseases. Distinguishing lncRNAs from protein-coding transcripts is a fundamental step for analyzing the lncRNA functional mechanism. However, the exp...

IoT Architecture for Smart Control of an Exoskeleton Robot in Rehabilitation by Using a Natural User Interface Based on Gestures.

Journal of medical systems
This paper describes a system for allowing a therapist to record specific motions, as a part of a rehabilitation program, mainly aimed at the elderly people, by using a Natural User Interface based on gestures. Motions are sent to an exoskeleton robo...

Predicting gene regulatory regions with a convolutional neural network for processing double-strand genome sequence information.

PloS one
With advances in sequencing technology, a vast amount of genomic sequence information has become available. However, annotating biological functions particularly of non-protein-coding regions in genome sequences without experiments is still a challen...

Cross-species regulatory sequence activity prediction.

PLoS computational biology
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...

A novel riboswitch classification based on imbalanced sequences achieved by machine learning.

PLoS computational biology
Riboswitch, a part of regulatory mRNA (50-250nt in length), has two main classes: aptamer and expression platform. One of the main challenges raised during the classification of riboswitch is imbalanced data. That is a circumstance in which the recor...

Designing a Cyber-Physical System for Ambient Assisted Living: A Use-Case Analysis for Social Robot Navigation in Caregiving Centers.

Sensors (Basel, Switzerland)
The advances of the Internet of Things, robotics, and Artificial Intelligence, to give just a few examples, allow us to imagine promising results in the development of smart buildings in the near future. In the particular case of elderly care, there ...

Automatic CT image segmentation of maxillary sinus based on VGG network and improved V-Net.

International journal of computer assisted radiology and surgery
PURPOSE: The analysis of the maxillary sinus (MS) can provide an assessment for many clinical diagnoses, so accurate CT image segmentation of the MS is essential. However, common segmentation methods are mainly done by experienced doctors manually, a...