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MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization.

Nucleic acids research
MusiteDeep is an online resource providing a deep-learning framework for protein post-translational modification (PTM) site prediction and visualization. The predictor only uses protein sequences as input and no complex features are needed, which res...

Partial directed coherence based graph convolutional neural networks for driving fatigue detection.

The Review of scientific instruments
The mental state of a driver can be accurately and reliably evaluated by detecting the driver's electroencephalogram (EEG) signals. However, traditional machine learning and deep learning methods focus on the single electrode feature analysis and ign...

Graph kernels combined with the neural network on protein classification.

Journal of bioinformatics and computational biology
At present, most of the researches on protein classification are based on graph kernels. The essence of graph kernels is to extract the substructure and use the similarity of substructures as the kernel values. In this paper, we propose a novel graph...

YAMDA: thousandfold speedup of EM-based motif discovery using deep learning libraries and GPU.

Bioinformatics (Oxford, England)
MOTIVATION: Motif discovery in large biopolymer sequence datasets can be computationally demanding, presenting significant challenges for discovery in omics research. MEME, arguably one of the most popular motif discovery software, takes quadratic ti...

Blind prediction of protein B-factor and flexibility.

The Journal of chemical physics
The Debye-Waller factor, a measure of X-ray attenuation, can be experimentally observed in protein X-ray crystallography. Previous theoretical models have made strong inroads in the analysis of beta (B)-factors by linearly fitting protein B-factors f...

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

Bioinformatics (Oxford, England)
MOTIVATION: Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find i...

Towards a Machine-Learning Approach for Sickness Prediction in 360° Stereoscopic Videos.

IEEE transactions on visualization and computer graphics
Virtual reality systems are widely believed to be the next major computing platform. There are, however, some barriers to adoption that must be addressed, such as that of motion sickness - which can lead to undesirable symptoms including postural ins...

GraphCom: A multidimensional measure of graphic complexity applied to 131 written languages.

Behavior research methods
We report a new multidimensional measure of visual complexity (GraphCom) that captures variability in the complexity of graphs within and across writing systems. We applied the measure to 131 written languages, allowing comparisons of complexity and ...

The Reactome Pathway Knowledgebase.

Nucleic acids research
The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism, and other cellular processes as an ordered network of molecular transformations-an extended version of a clas...

Reactome enhanced pathway visualization.

Bioinformatics (Oxford, England)
MOTIVATION: Reactome is a free, open-source, open-data, curated and peer-reviewed knowledge base of biomolecular pathways. Pathways are arranged in a hierarchical structure that largely corresponds to the GO biological process hierarchy, allowing the...