Yasubumi Sakakibara
Keio University
Publications 153
#1Wakako Kumita (Central Institute for Experimental Animals)H-Index: 2
#2Kenya Sato (Central Institute for Experimental Animals)H-Index: 3
Last.Yasubumi Sakakibara (Keio: Keio University)H-Index: 29
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Genetically modified nonhuman primates (NHP) are useful models for biomedical research. Gene editing technologies have enabled production of target-gene knock-out (KO) NHP models. Target-gene-KO/knock-in (KI) efficiency of CRISPR/Cas9 has not been extensively investigated in marmosets. In this study, optimum conditions for target gene modification efficacies of CRISPR/mRNA and CRISPR/nuclease in marmoset embryos were examined. CRISPR/nuclease was more effective than CRISPR/mRNA in avoiding mosai...
#1Le Thi Thu Hong (National Agriculture and Food Research Organization)
#2Tsuyoshi Hachiya (Keio: Keio University)H-Index: 11
Last.Keitarou Kimura (National Agriculture and Food Research Organization)H-Index: 13
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Poly-γ-glutamic acid (γPGA) production by Bacillus subtilis is regulated by the quorum sensing system where DegQ transmits the cell density signal to a DNA-binding protein DegU. A mutation suppressing the γPGA-negative phenotype of degQ gene knock-out mutant (Δ degQ ) was identified through whole genome sequencing. The mutation conferred an amino acid substitution of Ser103 to phenylalanine (S103F) in yabJ that belongs to the highly conserved YjgF/YER057c/UK114 family. Genetic experiments includ...
#1Yoshihiro Yamanishi (Kyushu Institute of Technology)H-Index: 26
#2Yasubumi Sakakibara (Keio: Keio University)H-Index: 29
Last.Yangjun Chen (La Trobe University)H-Index: 27
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#1Maya Hirohara (Keio: Keio University)
#2Yutaka Saito (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 4
Last.Yasubumi Sakakibara (Keio: Keio University)H-Index: 29
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Previous studies have suggested deep learning to be a highly effective approach for screening lead compounds for new drugs. Several deep learning models have been developed by addressing the use of various kinds of fingerprints and graph convolution architectures. However, these methods are either advantageous or disadvantageous depending on whether they (1) can distinguish structural differences including chirality of compounds, and (2) can automatically discover effective features. We develope...
#1Yoshimasa Aoto (Keio: Keio University)H-Index: 1
#2Kazuhiro OkumuraH-Index: 7
Last.Yasubumi Sakakibara (Keio: Keio University)H-Index: 29
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Recent years have witnessed substantial progress in understanding tumor heterogeneity and the process of tumor progression; however, the entire process of the transition of tumors from a benign to metastatic state remains poorly understood. In the present study, we performed a prospective cancer genome-sequencing analysis by employing an experimental carcinogenesis mouse model of squamous cell carcinoma to systematically understand the evolutionary process of tumors. We surgically collected a pa...
Jul 7, 2018 in ISMB (Intelligent Systems in Molecular Biology)
#1Genta Aoki (Keio: Keio University)H-Index: 1
#2Yasubumi Sakakibara (Keio: Keio University)H-Index: 29
Motivation: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successfully derived position weight matrices on the learned kernels that corresponded to sequence motifs such as protein-binding sites. Results: We propose a novel application of CNNs to classification of pairwise alignments of sequences for accurate cluste...
#1Manato Akiyama (Keio: Keio University)H-Index: 1
#2Yasubumi Sakakibara (Keio: Keio University)H-Index: 29
Last.Kengo Sato (Keio: Keio University)H-Index: 16
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Motivation: Existing approaches for predicting RNA secondary structures depend on how to decompose a secondary structure into substructures, so-called the architecture, to define their parameter space. However, the architecture has not been sufficiently investigated especially for pseudoknotted secondary structures. Results: In this paper, we propose a novel algorithm to directly infer base-pairing probabilities with neural networks that does not depend on the architecture of RNA secondary struc...