135 citations · 572 across the 19 of their papers we have counts for
6 papers · 1 filter
PromID: human promoter prediction by deep learning
Ramzan Umarov, Hiroyuki Kuwahara, Yu Li +2
Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with…
Accelerating Flash Calculation through Deep Learning Methods
Yu Li, Tao Zhang, Shuyu Sun +1
In the past two decades, researchers have made remarkable progress in accelerating flash calculation, which is very useful in a variety of engineering processes. In this paper, gen…
On the Decision Boundary of Deep Neural Networks
Yu Li, Lizhong Ding, Xin Gao
While deep learning models and techniques have achieved great empirical success, our understanding of the source of success in many aspects remains very limited. In an attempt to b…
DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy
Yu Li, Fan Xu, Fa Zhang +6
Super-resolution fluorescence microscopy, with a resolution beyond the diffraction limit of light, has become an indispensable tool to directly visualize biological structures in l…
OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction
Fatima Zohra Smaili, Xin Gao, Robert Hoehndorf
Motivation: Ontologies are widely used in biology for data annotation, integration, and analysis. In addition to formally structured axioms, ontologies contain meta-data in the for…
Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations
Fatima Zohra Smaili, Xin Gao, Robert Hoehndorf
We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wid…