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We constructed a gene co-expression network and developed an algorithm to extract biologically diverse gene groups with graph embedding using node2vec.

[Research] NRBdMF: Neighborhood Regularized Bidirectional Matrix Factorization

We developed a matrix factorization recommendation algorithm that considers the bidirectional nature of drug effects (side effects - indications) and can provide highly interpretable prediction results.

[Research] LiverDeconv: Liver-Specific Deconvolution Model

We developed a deconvolution method that can accurately predict the proportions of immune cells from bulk RNA-Seq of liver tissues by modeling the cell types specific to the liver tissue.

[Intern] Summer Internship at Preferred Networks, Inc.

「遺伝⼦に関するグラフを利⽤したモデルの開発」に取り組みました。

[Personal] PAM_Cython: Pachinko Allocation Model (PAM) with Cython

PAMをCythonで実装して高速化しました。

[Research] GLDADec: Guided LDA Deconvolution

We proposed a Guided LDA Deconvolution method, called GLDADec, to estimate cell type proportions by using marker gene names as partial prior information.

publications

Extraction of diverse gene groups with individual relationship from gene co-expression networks

Published in arXiv, 2021

Recommended citation: Azuma, Iori, Tadahaya Mizuno, and Hiroyuki Kusuhara. "Extraction of diverse gene groups with individual relationship from gene co-expression networks." arXiv preprint arXiv:2112.01180 (2021).
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NRBdMF: A Recommendation Algorithm for Predicting Drug Effects Considering Directionality

Published in Journal of Chemical Information and Modeling, 2023

Recommended citation: Azuma, Iori, Tadahaya Mizuno, and Hiroyuki Kusuhara. "NRBdMF: A recommendation algorithm for predicting drug effects considering directionality." Journal of Chemical Information and Modeling 63.2 (2023): 474-483.
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Rat Deconvolution as Knowledge Miner for Immune Cell Trafficking from Toxicogenomics Databases

Published in Toxicological Sciences, 2023

Recommended citation: Morita, Katsuhisa, et al. "Rat deconvolution as knowledge miner for immune cell trafficking from toxicogenomics databases." Toxicological Sciences (2023): 2023-06.
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Investigation of the usefulness of liver-specific deconvolution method by establishing a liver benchmark dataset

Published in NAR Genomics and Bioinformatics, 2024

Recommended citation: Azuma, Iori, et al. "Investigation of the usefulness of liver-specific deconvolution method by establishing a liver benchmark dataset." NAR Genomics and Bioinformatics (2024): 2024-03.
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GLDADec: marker-gene guided LDA modelling for bulk gene expression deconvolution

Published in Briefings in Bioinformatics, 2024

Recommended citation: Azuma, Iori, et al. "GLDADec: marker-gene guided LDA modelling for bulk gene expression deconvolution." Briefings in Bioinformatics (2024): 2024-07
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

Iori Azuma

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portfolio

Portfolio item number 1

Portfolio item number 2

posts2

ピッツァケベロス明治神宮前店

アランジャルシ

SAVOY とまととちーず店

アンティーカ・ピッツェリア・ダ・ミケーレ恵比寿

ナポリスタカ神谷町店

Pizzeria LUMEN

マッシモッタヴィオ

ピッツェリアGG 吉祥寺

PIZZA BORSA

聖林館

ピッツァストラーダ

ピッツェリアブラチェリアチェザリ

projects

[Research] n2v_rc: Node2Vec Recursive Clustering