Sequence2Vec

Our work on developing deep learning method for binding affnity prediction accepted by Bioinformatics

7/24/2017
​​Congratulates Ramzan, Hiro, and Yu on their work on developing a novel method that combines the strength of probabilistic graphical models, Hilbert space embedding, and deep learning to model binding affinity of transcription factors which was accepted by Bioinformatics.
https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx480/4042128/Sequence2Vec-A-novel-embedding-approach-for