AIMC Topic: Deep Learning

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Accounting Conformational Dynamics into Structural Modeling Reflected by Cryo-EM with Deep Learning.

Combinatorial chemistry & high throughput screening
With the continuous development of structural biology, the requirement for accurate threedimensional structures during functional modulation of biological macromolecules is increasing. Therefore, determining the dynamic structures of bio-macromolecul...

Review on Deep Learning Methodologies in Medical Image Restoration and Segmentation.

Current medical imaging
This paper comprehensively reviews two major image processing tasks, such as restoration and segmentation in the medical field, from a deep learning perspective. These processes are essential because restoration removes noise and segmentation extract...

Deep learning under mass-to-charge ratio pre-retrieval to realize electron ionization mass spectrometry library retrieval.

Rapid communications in mass spectrometry : RCM
RATIONALE: Gas chromatography-mass spectrometry (GC-MS) is an analytical technique widely used in materials science, biomedicine, and other fields. The target compound in the experiment is identified by searching for its mass spectrum in a large mass...

Accurate and fast clade assignment via deep learning and frequency chaos game representation.

GigaScience
BACKGROUND: Since the beginning of the coronavirus disease 2019 pandemic, there has been an explosion of sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, making it the most widely sequenced virus in the history. S...

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

Zhonghua xin xue guan bing za zhi
To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical e...

The quest for the missing links in fatty liver genetics: Deep learning to the rescue!

Cell reports. Medicine
Park, MacLean, et al. conduct an exome-wide association study of liver fat content in the Penn Medicine BioBank. By leveraging machine learning-assisted analysis of clinical CT scans to quantify steatosis, they uncover previously undescribed liver fa...

Neuron tracing from light microscopy images: automation, deep learning and bench testing.

Bioinformatics (Oxford, England)
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey pape...

DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.

Bioinformatics (Oxford, England)
MOTIVATION: Understanding the functional consequence of genetic variants, especially the non-coding ones, is important but particularly challenging. Genome-wide association studies (GWAS) or quantitative trait locus analyses may be subject to limited...