Search Results - "Tsukiyama, Sho"

ICAN: Interpretable cross-attention network for identifying drug and target protein interactions by Kurata, Hiroyuki, Tsukiyama, Sho

“…Drug–target protein interaction (DTI) identification is fundamental for drug discovery and drug repositioning, because therapeutic drugs act on disease-causing…”
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iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model by Kurata, Hiroyuki, Tsukiyama, Sho, Manavalan, Balachandran

“…Abstract The COVID-19 pandemic caused several million deaths worldwide. Development of anti-coronavirus drugs is thus urgent. Unlike conventional non-peptide…”
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BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches by Tsukiyama, Sho, Hasan, Md Mehedi, Deng, Hong-Wen, Kurata, Hiroyuki

“…Abstract N6-methyladenine (6mA) is associated with important roles in DNA replication, DNA repair, transcription, regulation of gene expression. Several…”
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PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides by Kurata, Hiroyuki, Harun-Or-Roshid, Md, Tsukiyama, Sho, Maeda, Kazuhiro

“…Interleukin (IL)-13 has emerged as one of the recently identified cytokine. Since IL-13 causes the severity of COVID-19 and alters crucial biological…”
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Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention–based neural networks by Tsukiyama, Sho, Kurata, Hiroyuki

“…[Display omitted] •Cross-attention PHV implements two key technologies: cross-attention mechanism and 1D-CNN.•It accurately predicts PPIs between human and…”
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CNN6mA: Interpretable neural network model based on position-specific CNN and cross-interactive network for 6mA site prediction by Tsukiyama, Sho, Hasan, Md Mehedi, Kurata, Hiroyuki

“…N6-methyladenine (6mA) plays a critical role in various epigenetic processing including DNA replication, DNA repair, silencing, transcription, and diseases…”
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LSTM-PHV: prediction of human-virus protein-protein interactions by LSTM with word2vec by Tsukiyama, Sho, Hasan, Md Mehedi, Fujii, Satoshi, Kurata, Hiroyuki

“…Viral infection involves a large number of protein-protein interactions (PPIs) between human and virus. The PPIs range from the initial binding of viral coat…”
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Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy by Hasan, Md Mehedi, Tsukiyama, Sho, Cho, Jae Youl, Kurata, Hiroyuki, Alam, Md Ashad, Liu, Xiaowen, Manavalan, Balachandran, Deng, Hong-Wen

“…As one of the most prevalent post-transcriptional epigenetic modifications, N5-methylcytosine (m5C) plays an essential role in various cellular processes and…”
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MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models by Kurata, Hiroyuki, Harun-Or-Roshid, Md, Mehedi Hasan, Md, Tsukiyama, Sho, Maeda, Kazuhiro, Manavalan, Balachandran

“…•MLm5C is a novel machine learning-based predictor of the 5-methylcytosine (m5C) modification sites of RNA sequences.•MLm5C stacks the 44 baseline…”
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PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides by Hiroyuki Kurata, Md. Harun-Or-Roshid, Sho Tsukiyama, Kazuhiro Maeda

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