Chongwei Shi Advances Biostatistical Methods and Computational Biology Through Deep Learning and Statistical Shape Analysis

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
EurekAlert!

Dynamic network plasticity and sample efficiency in biological neural cultures: A comparative study with deep reinforcement learning

(A) Schematic illustration of the DishBrain feedback loop, the simulated game environment, and electrode configurations. (B) A schematic illustration of the overall network construction framework. The ...
Chemistry World

Google’s AlphaGenome deep learning model wants to do for DNA what AlphaFold did for proteins

Model predicts effect of mutations on sequences up to 1 million base pairs in length and is adept at tackling complex ...

Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...
GEN

From Raw Data to Biological Insight

Welcome to this eBook on “From Raw Data to Biological Insight: Unlocking Scientific Discovery with Deep Learning”. In the rapidly evolving landscape of scientific research, we stand at a crucial ...
News Medical

Using Deep Learning for Brain Imaging Data Analysis

Deep learning (DL) is a type of artificial intelligence (AI) that utilizes artificial neural networks (ANNs) to process data through two or more layers, each of which can recognize complex features of ...
AZoOptics on MSN

Deep learning in optical microscopy: Advancements and applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.