Our work on developing deep learning method for binding affinity prediction accepted by Bioinformatics (Sequence2Vec)
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.
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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.
