Hideo Matsuda 研究室

主宰者：Hideo Matsuda

大阪大学

AI 要約（直近 5 年の研究成果）

松田秀雄研究室では、生命現象を支配する細胞間の相互作用と遺伝子発現制御の仕組みを、単一細胞レベルから組織全体に至るまで多角的に解き明かす研究を展開しています。特に、単一細胞RNA塩基配列解析や顕微鏡画像解析といった実験手法と、機械学習やディープラーニングなどの計算手法を組み合わせることで、複雑な生命現象を定量的に評価することに力を入れています。研究対象は多岐にわたり、自己免疫疾患による脱毛症のメカニズム、乳がん治療への応答性予測、肝臓障害における血流障害の原因、がんの遺伝子融合といった様々な疾患・現象を扱っています。また、多能性幹細胞の分化過程における遺伝子制御ネットワークの解明や、組織内の細胞の動的な振る舞いの自動追跡といったテーマも並行して進めています。これらの研究を通じて、細胞間通信の異常が疾患進行を駆動する機構の同定や、治療効果の個人差を予測するための分子マーカーの発見などが実現されています。計算機科学と実験生物学を統合した研究アプローチにより、従来の手法では検出できなかった生命現象の新しい側面を明らかにすることが、この研究室の特徴です。

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

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研究成果（34 件）

[2025] Prognostic significance of HER2 heterogeneity in early-stage and locally advanced HER2-positive breast cancer.
DOI: https://doi.org/10.1200/jco.2025.43.16_suppl.e12595
[2025] IRSN-23 gene diagnosis enhances breast cancer subtype classification and predicts response to neoadjuvant chemotherapy: new validation analyses
DOI: https://doi.org/10.1007/s12282-025-01687-6
[2025] Exploration of Key Signals in Alopecia Areata by Cell-Cell Interaction Analysis
DOI: https://doi.org/10.18178/ijpmbs.14.2.75-79
[2025] Entropy-Based Detection of Unknown Cell Type Using Deep Learning on Single-Cell RNA-Seq Data
DOI: https://doi.org/10.1145/3794209.3794223
[2025] Inhibition of N-myristoyltransferase in pluripotent stem cells promotes the naive state in mice and elicits trophectoderm and primitive endoderm markers in humans
DOI: https://doi.org/10.1016/j.stemcr.2025.102610
[2024] High HER2 Intratumoral Heterogeneity Is a Predictive Factor for Poor Prognosis in Early-Stage and Locally Advanced HER2-Positive Breast Cancer
DOI: https://doi.org/10.3390/cancers16051062
[2024] Accurate Detection of Fusion Genes in Long-Read Transcriptome Datasets from Multiple Cancer Cell Lines
DOI: https://doi.org/10.1145/3640900.3640909
[2024] Quantifying the recovery process of skeletal muscle on hematoxylin and eosin stained images via learning from label proportion
DOI: https://doi.org/10.1038/s41598-024-78433-z
[2024] Detecting Fusion Genes in Long-Read Transcriptome Sequencing Data with FUGAREC
DOI: https://doi.org/10.2197/ipsjtbio.17.1
[2024] Challenges for early diagnosis of neonatal herpes infection in Japan
DOI: https://doi.org/10.3389/frph.2024.1393509

続きを表示（残り 24 件）

[2024] A Novel Approach to Detection Algorithms for Artifacts in Clinical Endoscopy
DOI: https://doi.org/10.2197/ipsjtbio.17.18
[2024] Gene Fusion Detection in Long-Read Transcriptome Datasets from Multiple Cancer Cell Lines
DOI: https://doi.org/10.31083/j.fbl2912413
[2024] Communication Analysis between Human Hair-Follicles and Immune Cells with Single-cell RNA-seq
DOI: https://doi.org/10.1145/3707127.3707168
[2024] Microcirculatory disturbance in acute liver injury is triggered by IFNγ-CD40 axis
DOI: https://doi.org/10.1186/s12950-024-00387-w
[2023] Cell Tracking via Reinforcement Learning with Microscopic Image Simulator
DOI: https://doi.org/10.1145/3620679.3620682
[2023] A Cell Tracking Method for Dynamic Analysis of Immune Cells Based on Deep Learning
DOI: https://doi.org/10.18178/ijml.2023.13.2.1130
[2023] EPH230 Systematic Literature Review on the Clinical and Economic Burdens of Antimicrobial Resistance in the Japanese Population
DOI: https://doi.org/10.1016/j.jval.2023.09.1271
[2023] Synthetic model ecosystem of 12 cryopreservable microbial species allowing for a noninvasive approach
DOI: https://doi.org/10.1016/j.biosystems.2023.105087
[2023] Prospective validation of the IRSN-23 model for personalized chemotherapy and proposal of new breast cancer subtype classification.
DOI: https://doi.org/10.1200/go.2023.9.supplement_1.10
[2023] Pseudotime-based Deep Learning of Gene Regulatory Relationships from Single-Cell Expression Data
DOI: https://doi.org/10.1145/3620679.3620688
[2022] Detection of Biomarkers for Epithelial-Mesenchymal Transition with Single-Cell Trajectory Inference
DOI: https://doi.org/10.31083/j.fbl2704127
[2022] Identification of Lineage Markers for T Cell Immune Dysregulation in Sarcoidosis Using Single-Cell RNA-seq
DOI: https://doi.org/10.17706/ijbbb.2022.12.4.63-70
[2022] A Novel Method for Fusion Gene Detection using Both End-Fragment Sequences of Long Reads
DOI: https://doi.org/10.1145/3574198.3574212
[2022] Inference of Cell-Cell Communication for Detecting Immune Disease-Associated Signaling Pathways using Single-Cell RNA-seq
DOI: https://doi.org/10.1145/3574198.3574210
[2022] Myeloid cell-specific ablation of Runx2 gene exacerbates post-infarct cardiac remodeling
DOI: https://doi.org/10.1038/s41598-022-21202-7
[2022] MPP6 stimulates both RRP6 and DIS3 to degrade a specified subset of MTR4-sensitive substrates in the human nucleus
DOI: https://doi.org/10.1093/nar/gkac559
[2022] A Novel Method for Gene Regulatory Network Inference with Pseudotime Data Using Information Criterion
DOI: https://doi.org/10.17706/ijbbb.2022.12.3.43-52
[2022] A Method for Detection of Markers for Epithelial-Mesenchymal Transition based on Single Cell Transcriptomic Data
DOI: https://doi.org/10.1145/3510427.3510436
[2021] SLPI is a critical mediator that controls PTH-induced bone formation
DOI: https://doi.org/10.1038/s41467-021-22402-x
[2021] Infrastructure Maintenance based on the MICHIMORI System
DOI: https://doi.org/10.3151/coj.59.1_83
[2021] Osteoclasts adapt to physioxia perturbation through DNA demethylation
DOI: https://doi.org/10.15252/embr.202153035
[2021] SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization
DOI: https://doi.org/10.7717/peerj.12087
[2021] A CNN-based cell tracking method for multi-slice intravital imaging data
DOI: https://doi.org/10.1145/3459930.3469559
[2021] Detecting Lineage-Specific Marker Genes for Tumor Evolution Based on Single Cell Transcriptome
DOI: https://doi.org/10.17706/ijbbb.2021.11.3.50-57

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AI 要約（直近 5 年の研究成果）

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関連研究室(8 件)

研究成果（34 件）

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