Tatsuya Akutsu

Tatsuya Akutsu

Kyoto University

H-index: 58

Asia-Japan

About Tatsuya Akutsu

Tatsuya Akutsu, With an exceptional h-index of 58 and a recent h-index of 39 (since 2020), a distinguished researcher at Kyoto University, specializes in the field of Bioinformatics, Discrete Algorithms.

His recent articles reflect a diverse array of research interests and contributions to the field:

DiCleave: a deep learning model for predicting human Dicer cleavage sites

On the Generative Power of ReLU Network for Generating Similar Strings

Computational Method for k-Distance Limited Minimum Feedback Vertex Set and Its Application to Biological Networks

Accurate Multi-view Clustering to Seek the Cross-viewed yet Uniform Sample Assignment via Tensor Feature Matching

Measuring criticality in control of complex biological networks

Multi-shelled ECIF: improved extended connectivity interaction features for accurate binding affinity prediction

Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes

ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction

Tatsuya Akutsu Information

University

Position

Professor Bioinformatics Center Institute for Chemical Research

Citations(all)

15231

Citations(since 2020)

5803

Cited By

12130

hIndex(all)

58

hIndex(since 2020)

39

i10Index(all)

244

i10Index(since 2020)

119

Email

University Profile Page

Kyoto University

Google Scholar

View Google Scholar Profile

Tatsuya Akutsu Skills & Research Interests

Bioinformatics

Discrete Algorithms

Top articles of Tatsuya Akutsu

Title

Journal

Author(s)

Publication Date

DiCleave: a deep learning model for predicting human Dicer cleavage sites

BMC bioinformatics

Lixuan Mu

Jiangning Song

Tatsuya Akutsu

Tomoya Mori

2024/1/9

On the Generative Power of ReLU Network for Generating Similar Strings

IEEE Access

Mamoona Ghafoor

Tatsuya Akutsu

2024/4/10

Computational Method for k-Distance Limited Minimum Feedback Vertex Set and Its Application to Biological Networks

Shogo Nakashima

Tatsuya Akutsu

2024/3/29

Accurate Multi-view Clustering to Seek the Cross-viewed yet Uniform Sample Assignment via Tensor Feature Matching

Information Sciences

Yue Zhang

Wuxiu Quan

Tatsuya Akutsu

Li Liu

Hongmin Cai

...

2024/2/15

Measuring criticality in control of complex biological networks

NPJ Systems Biology and Applications

Wataru Someya

Tatsuya Akutsu

Jean-Marc Schwartz

Jose C Nacher

2024/1/20

Multi-shelled ECIF: improved extended connectivity interaction features for accurate binding affinity prediction

Bioinformatics Advances

Koji Shiota

Tatsuya Akutsu

2023/1/1

Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes

arXiv preprint arXiv:2305.00801

Jianshen Zhu

Naveed Ahmed Azam

Kazuya Haraguchi

Liang Zhao

Hiroshi Nagamochi

...

2023/4/27

ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction

Briefings in Bioinformatics

Fuyi Li

Cong Wang

Xudong Guo

Tatsuya Akutsu

Geoffrey I Webb

...

2023/11/1

On the Size and Width of the Decoder of a Boolean Threshold Autoencoder

IEEE Transactions on Neural Networks and Learning Systems

Tatsuya Akutsu

Avraham A Melkman

2023/12/25

Common Attractors in Multiple Boolean Networks

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Yu Cao

Wenya Pi

Chun-Yu Lin

Ulrike Münzner

Masahiro Ohtomo

...

2023/4/20

Whole-Brain Evaluation of Cortical Microconnectomes

Eneuro

Kouki Matsuda

Arata Shirakami

Ryota Nakajima

Tatsuya Akutsu

Masanori Shimono

2023/10/1

On the Trade-off between the Number of Nodes and the Number of Trees in a Random Forest

arXiv preprint arXiv:2312.11540

Tatsuya Akutsu

Avraham A Melkman

Atsuhiro Takasu

2023/12/16

ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning

Briefings in Bioinformatics

Xiaoti Jia

Pei Zhao

Fuyi Li

Zhaohui Qin

Haoran Ren

...

2023/3

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities

Briefings in Bioinformatics

Jing Xu

Fuyi Li

Chen Li

Xudong Guo

Cornelia Landersdorfer

...

2023/7

2023 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 34

IEEE Transactions on Neural Networks and Learning Systems

M Abdel-Aty

M Abdizadeh

Abdul Hameed

A Abooee

M Abroshan

...

2023/12

PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships

Bioinformatics

Tong Pan

Chen Li

Yue Bi

Zhikang Wang

Robin B. Gasser

...

2023/3

AQDnet: Deep Neural Network for Protein–Ligand Docking Simulation

ACS omega

Koji Shiota

Akira Suma

Hiroyuki Ogawa

Takuya Yamaguchi

Akio Iida

...

2023/6/16

Foreword MedAI 2023

Ying Xu

Weiru Liu

Guoyin Wang

Shihua Zhang

Hong Yu

...

2023/11/18

Metrics for RNA Secondary Structure Comparison

Feiqi Wang

Tatsuya Akutsu

Tomoya Mori

2023/1/28

eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells

BMC bioinformatics

Tomoya Mori

Toshiro Takase

Kuan-Chun Lan

Junko Yamane

Cantas Alev

...

2023/6/15

See List of Professors in Tatsuya Akutsu University(Kyoto University)