Brain science is the frontier of scientific research, as it is essential for exploring the fundamental principles of how our brain works, and why mental disorders happen. Elucidating these challenging questions requires revolutionary approaches, for which we believe that both “wet” and “dry” biotechnologies are essential for this pursuit. We are curious about how deep learning algorithms and big data analyses could breakout boundaries and extend our understanding of the principles underlie brain diseases. To achieve this, we took neurological diseases (especially ALS) as our research model, which is one of the most challenging types of diseases to cure. In our recent work, we focused on developing cutting-edge biotechnologies to investigate how genetic mutations modulate molecular changes (such as RNA splicing/expression and DNA methylation), and what are the genetic mechanisms of neurodegenerative diseases at a single cellular and spatial transcriptomic resolution.

Spliformer

Spliformer is a deep-learning tool based on CNN and self-attention mechanism for predicting the influence of genetic variants on RNA splicing in human and visualizing the attention weight score (AWS) of splicing motifs.

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SpatialE

SpatialE is a tool for analyzing the spatial enrichment of specific gene sets in spatial transcriptome data.

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