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Tatsuya Akutsu

Tatsuya Akutsu

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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
63
Citations
15762
World Ranking
2757
National Ranking
18

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Tatsuya Akutsu is a researcher affiliated with Kyoto University in Japan. Their work spans multiple disciplines, with a primary focus on biochemistry, genetics, molecular biology, and computer science. They have contributed extensively to subfields including molecular biology, computational theory and mathematics, artificial intelligence, materials chemistry, and spectroscopy.

The main topics covered in their research include:

  • Computational Drug Discovery Methods
  • Gene Regulatory Network Analysis
  • Machine Learning in Bioinformatics
  • Protein Structure and Dynamics
  • Bioinformatics and Genomic Networks
  • Machine Learning in Materials Science
  • RNA and protein synthesis mechanisms

Tatsuya Akutsu has published a significant number of papers in various venues. The most frequent publication platforms include:

  • arXiv (Cornell University)
  • Briefings in Bioinformatics
  • IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • BMC Bioinformatics
  • Scientific Reports

Their recent publications demonstrate an emphasis on machine learning applications in bioinformatics and related fields. Some of these notable papers are:

  • iLearnPlus:a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization, 2021, Nucleic Acids Research
  • Procleave: Predicting Protease-Specific Substrate Cleavage Sites by Combining Sequence and Structural Information, 2020, Genomics Proteomics & Bioinformatics
  • iFeatureOmega:an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets, 2022, Nucleic Acids Research
  • DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy, 2020, Briefings in Bioinformatics
  • iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities, 2023, Briefings in Bioinformatics

Their collaborations involve frequent co-authorship with researchers such as Jianshen Zhu, Hiroshi Nagamochi, Naveed Ahmed Azam, Jiangning Song, and Kazuya Haraguchi, with collaboration counts ranging from 19 to 25 publications each.

Best Publications

  • Identification of genetic networks from a small number of gene expression patterns under the Boolean network model.

    Tatsuya Akutsu;Satoru Miyano;Satoru Kuhara

  • Control of Boolean networks: hardness results and algorithms for tree structured networks.

    Tatsuya Akutsu;Morihiro Hayashida;Wai-Ki Ching;Michael K. Ng

  • Inferring qualitative relations in genetic networks and metabolic pathways

    Tatsuya Akutsu;Satoru Miyano;Satoru Kuhara

  • Protein homology detection using string alignment kernels

    Hiroto Saigo;Jean-Philippe Vert;Nobuhisa Ueda;Tatsuya Akutsu

  • Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots

    Tatsuya Akutsu

  • iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.

    Zhen Chen;Pei Zhao;Fuyi Li;Tatiana T Marquez-Lago

  • IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming

    Kengo Sato;Yuki Kato;Michiaki Hamada;Tatsuya Akutsu

  • Extensions of marginalized graph kernels

    Pierre Mahé;Nobuhisa Ueda;Tatsuya Akutsu;Jean-Luc Perret

  • Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function.

    Tatsuya Akutsu;Satoru Miyano;Satoru Kuhara

  • iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization.

    Zhen Chen;Pei Zhao;Chen Li;Fuyi Li;Fuyi Li

  • Graph Kernels for Molecular Structure−Activity Relationship Analysis with Support Vector Machines

    Pierre Mahé;Nobuhisa Ueda;Tatsuya Akutsu;Jean-Luc Perret

  • iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites

    Jiangning Song;Yanan Wang;Fuyi Li;Tatsuya Akutsu

  • Dominating scale-free networks with variable scaling exponent: heterogeneous networks are not difficult to control

    Jose C Nacher;Jose C Nacher;Tatsuya Akutsu

  • A novel representation of protein sequences for prediction of subcellular location using support vector machines

    Setsuro Matsuda;Jean Philippe Vert;Hiroto Saigo;Nobuhisa Ueda

  • Identification of gene regulatory networks by strategic gene disruptions and gene overexpressions

    Tatsuya Akutsu;Satoru Kuhara;Osamu Maruyama;Satoru Miyano

  • Cascleave: towards more accurate prediction of caspase substrate cleavage sites.

    Jiangning Song;Hao Tan;Hongbin Shen;Khalid Mahmood

  • A System for Identifying Genetic Networks from Gene Expression Patterns Produced by Gene Disruptions and Overexpressions.

    Tatsuya Akutsu;Satoru Kuhara;Osamu Maruyama;Satoru Miyano

  • Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.

    Fuyi Li;Chen Li;Chen Li;Tatiana T Marquez-Lago;André Leier

  • A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction

    Shutao Mei;Fuyi Li;André Leier;Tatiana T Marquez-Lago

  • PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.

    Jiangning Song;Fuyi Li;Andre Leier;Tatiana Marquez-Lago

  • Algorithms for inferring qualitative models of biological networks.

    Tatsuya Akutsu;Satoru Miyano;Satoru Kuhara

Frequent Co-Authors

Jiangning Song
Jiangning Song Monash University
Wai-Ki Ching
Wai-Ki Ching University of Hong Kong
Hiroshi Nagamochi
Hiroshi Nagamochi Kyoto University
Satoru Miyano
Satoru Miyano Tokyo Medical and Dental University
Geoffrey I. Webb
Geoffrey I. Webb Monash University
Minoru Kanehisa
Minoru Kanehisa Kyoto University
André Leier
André Leier University of Alabama at Birmingham
Kuo-Chen Chou
Kuo-Chen Chou The Gordon Life Science Institute
Satoru Kuhara
Satoru Kuhara Kyushu University
Jean-Philippe Vert
Jean-Philippe Vert Google (United States)

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