AIMC Topic: Deep Learning

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DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays.

Bioinformatics (Oxford, England)
MOTIVATION: Mapping distal regulatory elements, such as enhancers, is a cornerstone for elucidating how genetic variations may influence diseases. Previous enhancer-prediction methods have used either unsupervised approaches or supervised methods wit...

On the feasibility of deep learning applications using raw mass spectrometry data.

Bioinformatics (Oxford, England)
SUMMARY: In recent years, SWATH-MS has become the proteomic method of choice for data-independent-acquisition, as it enables high proteome coverage, accuracy and reproducibility. However, data analysis is convoluted and requires prior information and...

CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes.

Bioinformatics (Oxford, England)
MOTIVATION: CRISPR/Cas9 is a revolutionary gene-editing technology that has been widely utilized in biology, biotechnology and medicine. CRISPR/Cas9 editing outcomes depend on local DNA sequences at the target site and are thus predictable. However, ...

keras_dna: a wrapper for fast implementation of deep learning models in genomics.

Bioinformatics (Oxford, England)
SUMMARY: Prediction of genomic annotations from DNA sequences using deep learning is today becoming a flourishing field with many applications. Nevertheless, there are still difficulties in handling data in order to conveniently build and train model...

[Deep learning-based dental plaque detection on permanent teeth and the influenced factors].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
To develop an artificial intelligence system for detecting dental plaque on permanent teeth and find the influenced factors. Photos of the labial or buccal surfaces of the permanent teeth were taken by using an intraoral camera (1 280×960 pixels; T...

Binocular vision supports the development of scene segmentation capabilities: Evidence from a deep learning model.

Journal of vision
The application of deep learning techniques has led to substantial progress in solving a number of critical problems in machine vision, including fundamental problems of scene segmentation and depth estimation. Here, we report a novel deep neural net...

Deep representation learning improves prediction of LacI-mediated transcriptional repression.

Proceedings of the National Academy of Sciences of the United States of America
Recent progress in DNA synthesis and sequencing technology has enabled systematic studies of protein function at a massive scale. We explore a deep mutational scanning study that measured the transcriptional repression function of 43,669 variants of ...

Multicolor image classification using the multimodal information bottleneck network (MMIB-Net) for detecting diabetic retinopathy.

Optics express
Multicolor (MC) imaging is an imaging modality that records confocal scanning laser ophthalmoscope (cSLO) fundus images, which can be used for the diabetic retinopathy (DR) detection. By utilizing this imaging technique, multiple modal images can be ...

Hierarchical Learning of Statistical Regularities over Multiple Timescales of Sound Sequence Processing: A Dynamic Causal Modeling Study.

Journal of cognitive neuroscience
Our understanding of the sensory environment is contextualized on the basis of prior experience. Measurement of auditory ERPs provides insight into automatic processes that contextualize the relevance of sound as a function of how sequences change ov...