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Kazunori D. Yamada
Tohoku University
27Publications
10H-index
781Citations
Publications 27
Newest
#1Kazutaka KatohH-Index: 27
#2John RozewickiH-Index: 2
Last.Kazunori D. YamadaH-Index: 10
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420 CitationsSource
#1Keiji Yasukawa (Daiichi University of Pharmacy)H-Index: 12
#2Akinobu Hirago (Kyushu University)
Last.Hideo Utsumi (Kyushu University)H-Index: 43
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Abstract In ulcerative colitis, an inflammatory bowel disease of unknown cause, diagnosis of the degree and location of colitis at an early stage is required to control the symptoms. Changes in redox status, including the production of reactive oxygen and nitrogen species (RONS), have been associated with ulcerative colitis in humans and dextran sodium sulfate (DSS)-induced colitis in rodents. In this study, the in vivo redox status of colons of DSS-induced colitis mice were monitored by Overhau...
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#1Kazunori D. Yamada (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 10
#2Kengo Kinoshita (Tohoku University)H-Index: 35
Background Long short-term memory (LSTM) is one of the most attractive deep learning methods to learn time series or contexts of input data. Increasing studies, including biological sequence analyses in bioinformatics, utilize this architecture. Amino acid sequence profiles are widely used for bioinformatics studies, such as sequence similarity searches, multiple alignments, and evolutionary analyses. Currently, many biological sequences are becoming available, and the rapidly increasing amount ...
1 CitationsSource
#1Kazunori D. Yamada (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 10
Background A profile-comparison method with position-specific scoring matrix (PSSM) is among the most accurate alignment methods. Currently, cosine similarity and correlation coefficients are used as scoring functions of dynamic programming to calculate similarity between PSSMs. However, it is unclear whether these functions are optimal for profile alignment methods. By definition, these functions cannot capture nonlinear relationships between profiles. Therefore, we attempted to discover a nove...
2 CitationsSource
#1Tsukasa Nakamura (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 3
#2Kazunori D. Yamada (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 10
Last.Kazutaka Katoh (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 27
view all 4 authors...
66 CitationsSource
#1Kazunori D. Yamada (Tohoku University)H-Index: 10
In the deep learning era, a gradient descent method is the most common method to optimize parameters of neural networks. Among various mathematical optimization methods, a gradient descent method is the most naive method. Although controlling a learning rate of the method is necessary for quick convergence, the vanilla gradient descent method requires us to adjust it manually. In order to control the learning rate and accelerate converging speed of the method, a lot of optimizers were developed....
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#1Kazunori D. Yamada (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 10
#2Satoshi Omori (Tohoku University)H-Index: 2
Last.Masaru Miyagi (Case Western Reserve University)H-Index: 34
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Background N-terminal acetylation is one of the most common protein modifications in eukaryotes and occurs co-translationally when the N-terminus of the nascent polypeptide is still attached to the ribosome. This modification has been shown to be involved in a wide range of biological phenomena such as protein half-life regulation, protein-protein and protein-membrane interactions, and protein subcellular localization. Thus, accurately predicting which proteins receive an acetyl group based on t...
2 CitationsSource
#1Kazunori D. Yamada (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 10
#2Naoki KunishimaH-Index: 21
Last.Kentaro Tomii (AIST: National Institute of Advanced Industrial Science and Technology)H-Index: 20
view all 7 authors...
An alternative rational approach to improve protein crystals by using single-site mutation of surface residues is proposed based on the results of a statistical analysis using a compiled data set of 918 independent crystal structures, thereby reflecting not only the entropic effect but also other effects upon protein crystallization. This analysis reveals a clear difference in the crystal-packing propensity of amino acids depending on the secondary-structural class. To verify this result, a syst...
Source
A profile comparison method with position-specific scoring matrix (PSSM) is one of the most accurate alignment methods. Currently, cosine similarity and correlation coefficient are used as scoring functions of dynamic programming to calculate similarity between PSSMs. However, it is unclear that these functions are optimal for profile alignment methods. At least, by definition, these functions cannot capture non-linear relationships between profiles. Therefore, in this study, we attempted to dis...
#1Kazunori D. YamadaH-Index: 10
#2Naoki KunishimaH-Index: 21
Last.Kentaro TomiiH-Index: 20
view all 7 authors...
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