Sato Laboratory (Biomedical Data Science)
Sato Laboratory (Biomedical Data Science)
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Yasubumi Sakakibara
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Direct inference of base-pairing probabilities with neural networks improves prediction of RNA secondary structures with pseudoknots
A max-margin model for predicting residue-base contacts in protein-RNA interactions
RNA secondary structure prediction using deep learning with thermodynamic integration
An improved de novo genome assembly of the common marmoset genome yields improved contiguity and increased mapping rates of sequence data
Efficient generation of Knock-in/Knock-out marmoset embryo via CRISPR/Cas9 gene editing
A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model
Convolutional neural network based on SMILES representation of compounds for detecting chemical motif
DEclust: A statistical approach for obtaining differential expression profiles of multiple conditions
Generation of a Nonhuman Primate Model of Severe Combined Immunodeficiency Using Highly Efficient Genome Editing
SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing
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