Zobrazeno 1 - 10
of 825
pro vyhledávání: '"Akutsu, Tatsuya"'
Autor:
Batool, Muniba, Azam, Naveed Ahmed, Zhu, Jianshen, Haraguchi, Kazuya, Zhao, Liang, Akutsu, Tatsuya
Aqueous solubility (AS) is a key physiochemical property that plays a crucial role in drug discovery and material design. We report a novel unified approach to predict and infer chemical compounds with the desired AS based on simple deterministic gra
Externí odkaz:
http://arxiv.org/abs/2409.04301
Autor:
Song, Bowen, Zhu, Jianshen, Azam, Naveed Ahmed, Haraguchi, Kazuya, Zhao, Liang, Akutsu, Tatsuya
In this paper, we propose a novel family of descriptors of chemical graphs, named cycle-configuration (CC), that can be used in the standard "two-layered (2L) model" of mol-infer, a molecular inference framework based on mixed integer linear programm
Externí odkaz:
http://arxiv.org/abs/2408.05136
A Boolean network (BN) is called observable if any initial state can be uniquely determined from the output sequence. In the existing literature on observability of BNs, there is almost no research on the relationship between the number of observatio
Externí odkaz:
http://arxiv.org/abs/2407.18560
In this paper, we focus on the prediction phase of a random forest and study the problem of representing a bag of decision trees using a smaller bag of decision trees, where we only consider binary decision problems on the binary domain and simple de
Externí odkaz:
http://arxiv.org/abs/2312.11540
Autor:
Zhu, Jianshen, Azam, Naveed Ahmed, Haraguchi, Kazuya, Zhao, Liang, Nagamochi, Hiroshi, Akutsu, Tatsuya
A novel framework for designing the molecular structure of chemical compounds with a desired chemical property has recently been proposed. The framework infers a desired chemical graph by solving a mixed integer linear program (MILP) that simulates t
Externí odkaz:
http://arxiv.org/abs/2305.00801
Autor:
Tokuhara, Yusuke1 (AUTHOR), Akutsu, Tatsuya2 (AUTHOR), Schwartz, Jean-Marc3 (AUTHOR), Nacher, Jose C.1 (AUTHOR) nacher@is.sci.toho-u.ac.jp
Publikováno v:
NPJ Systems Biology & Applications. 8/12/2024, Vol. 10 Issue 1, p1-12. 12p.
Autor:
Zhu, Jianshen, Azam, Naveed Ahmed, Cao, Shengjuan, Ido, Ryota, Haraguchi, Kazuya, Zhao, Liang, Nagamochi, Hiroshi, Akutsu, Tatsuya
A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property, where design of novel drugs is an important topic in bioinformatics and chemo-informatics. The framework infers
Externí odkaz:
http://arxiv.org/abs/2209.13527
Autor:
Akutsu, Tatsuya, Melkman, Avraham A.
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems, 2023
In this paper, we study the size and width of autoencoders consisting of Boolean threshold functions, where an autoencoder is a layered neural network whose structure can be viewed as consisting of an encoder, which compresses an input vector to a lo
Externí odkaz:
http://arxiv.org/abs/2112.10933
Autor:
Someya, Wataru1 (AUTHOR), Akutsu, Tatsuya2 (AUTHOR), Nacher, Jose C.1 (AUTHOR) nacher@is.sci.toho-u.ac.jp
Publikováno v:
Scientific Reports. 7/23/2024, Vol. 14 Issue 1, p1-12. 12p.
Autor:
Ido, Ryota, Cao, Shengjuan, Zhu, Jianshen, Azam, Naveed Ahmed, Haraguchi, Kazuya, Zhao, Liang, Nagamochi, Hiroshi, Akutsu, Tatsuya
A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In this paper, we design a new metho
Externí odkaz:
http://arxiv.org/abs/2109.02628