AIMC Topic: Deep Learning

Clear Filters Showing 28281 to 28290 of 28423 articles

Off-target predictions in CRISPR-Cas9 gene editing using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: The prediction of off-target mutations in CRISPR-Cas9 is a hot topic due to its relevance to gene editing research. Existing prediction methods have been developed; however, most of them just calculated scores based on mismatches to the g...

Behavioral tracking gets real.

Nature neuroscience
A deep-learning-based software package called DeepLabCut rapidly and easily enables video-based motion tracking in any animal species. Such tracking technology is bound to revolutionize movement science and behavioral tracking in the laboratory and i...

Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Classification of plants based on a multi-organ approach is very challenging. Although additional data provide more information that might help to disambiguate between species, the variability in shape and appearance in plant organs also raises the d...

[Deep learning to support therapy decisions for intravitreal injections].

Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft
Significant progress has been made in artificial intelligence and computer vision research in recent years. Machine learning methods excel in a wide variety of tasks where sufficient data are available. We describe the application of a deep convoluti...

GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS.

Bioinformatics (Oxford, England)
SUMMARY: Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic architecture of human diseases. However, a significant proportion of identified genetic variants are ac...

Deep learning improves antimicrobial peptide recognition.

Bioinformatics (Oxford, England)
MOTIVATION: Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by wet-laborat...