Affiliation
東北大学・未踏スケールデータアナリティクスセンター・教授
Professor, Unprecedented-scale Data Analytics Center, Tohoku University
東北大学・情報科学研究科（兼務）
Graduate School of Information Sciences, Tohoku University
産業技術総合研究所・人工知能研究センター・協力研究員
Visiting Researcher, Artificial Intelligence Research Center, AIST
Research Interests
人工知能と意識 / 文脈情報処理のためのニューラルネットワークと対話エージェント / テレビゲームとエンターテイメント
strong AI and machine consciousness / neural network for sequence processing and dialogue agent / video game and entertainment
Our Research Team
| Kazunori Yamada | Researcher and instructor | Machine consciousness / Neural network |
| Fangzhou Lin | PhD student | Neural network / 3D point cloud / Image processing |
| Xia Tian | PhD student | Generative adversarial network |
Research Achievements
- Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, Frontiers in Artificial Intelligence, accepted, 2022
- Yasukawa K, Yamada K, Tokuda H, Koyama S, Utsumi H, Redox imaging of dextran sodium sulfate-induced colitis mice treated with nitric oxide synthase inhibitors, Advances in Redox Research, 6, 2022
- Lin F, Xu Y, Zhang Z, Gao C, Yamada KD, Cosmos Propagation Network: Deep learning model for point cloud completion, Neurocomputing, 507:221-234, 2022
- Yamada KD, Baladram MS, Lin F, Progress in research on implementing machine consciousness, Interdisciplinary Information Sciences, 28(1):95-105, 2022
- Lin F, Gao C, Yamada KD, An effective convolutional neural network for visualized understanding transboundary air pollution based on Himawari-8 satellite images, IEEE Geoscience and Remote Sensing Letters, 19:1-5, 2022
- Yamada KD, Lin F, Nakamura T, Developing a novel recurrent neural network architecture with fewer parameters and good learning performance, Interdisciplinary Information Sciences, 27(1):25-40, 2021
- Baladram MS, Koike A, Yamada KD, Introduction to supervised machine learning for data science, Interdisciplinary Information Sciences, 26(1):87-121, 2020
- Katoh K, Rozewicki J, Yamada KD, MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization, Briefings in Bioinformatics, 20(4):1160-1166, 2019
- Yasukawa K, Hirago A, Yamada K, Tun X, Ohkuma K, Utsumi H, In vivo redox imaging of dextran sodium sulfate-induced colitis in mice using Overhauser-enhanced magnetic resonance imaging, Free Radical Biology and Medicine, 136:1-11, 2019
- Yamada KD, Kinoshita K, De novo profile generation based on sequence context specificity with the long short-term memory network, BMC Bioinformatics, 19(1):272, 2018
- Nakamura T, Yamada KD, Tomii K, Katoh K, Parallelization of MAFFT for large-scale multiple sequence alignments, Bioinformatics, 34(14):2490-2492, 2018
- Yamada KD, Derivative-free neural network for optimizing the scoring functions associated with dynamic programming of pairwise-profile alignment, Algorithms for Molecular Biology, 13:5, 2018
- Yamada KD, Kunishima N, Matsuura Y, Nakai K, Naitow H, Fukasawa Y, Tomii K, Designing better diffracting crystals of biotin carboxyl carrier protein from Pyrococcus horikoshii by a mutation based on crystal-packing propensity of amino acids, Acta Crystallographica Section D, 73(9):757-766, 2017
- Yamada KD, Omori S, Nish H, Miyagi M, Identification of the sequence determinants of protein N-terminal acetylation through a decision tree approach, BMC Bioinformatics, 18(1):289, 2017
- Lim K, Yamada KD, Frith MC, Tomii K, Protein sequence-similarity search acceleration using a heuristic algorithm with a sensitive matrix, Journal of Structural and Functional Genomics, 17(4):147-154, 2016
- Yamada KD, Tomii K, Katoh K, Application of the MAFFT sequence alignment program to large data - reexamination of the usefulness of chained guide trees, Bioinformatics, 32(21):3246-3251, 2016
- Imamura T, Fujita K, Tagawa K, Ikura T, Chen X, Homma H, Tamura T, Mao Y, Taniguchi JB, Motoki K, Nakabayashi M, Ito N, Yamada K, Tomii K, Okano H, Kaye J, Finkbeiner S, Okazawa H, Identification of hepta-histidine as a candidate drug for Huntington’s disease by in silico-in vitro-in vivo-integrated screens of chemical libraries, Scientific Reports, 6:33861, 2016
- Lensink MF, Velankar S, Kryshtafovych A, Huang SY, Schneidman-Duhovny D, Sali A, Segura J, Fernandez-Fuentes N, Viswanath S, Elber R, Grudinin S, Popov P, Neveu E, Lee H, Baek M, Park S, Heo L, Rie Lee G, Seok C, Qin S, Zhou HX, Ritchie DW, Maigret B, Devignes MD, Ghoorah A, Torchala M, Chaleil RA, Bates PA, Ben-Zeev E, Eisenstein M, Negi SS, Weng Z, Vreven T, Pierce BG, Borrman TM, Yu J, Ochsenbein F, Guerois R, Vangone A, Rodrigues JP, van Zundert G, Nellen M, Xue L, Karaca E, Melquiond AS, Visscher K, Kastritis PL, Bonvin AM, Xu X, Qiu L, Yan C, Li J, Ma Z, Cheng J, Zou X, Shen Y, Peterson LX, Kim HR, Roy A, Han X, Esquivel-Rodriguez J, Kihara D, Yu X, Bruce NJ, Fuller JC, Wade RC, Anishchenko I, Kundrotas PJ, Vakser IA, Imai K, Yamada K, Oda T, Nakamura T, Tomii K, Pallara C, Romero-Durana M, Jiménez-García B, Moal IH, Férnandez-Recio J, Joung JY, Kim JY, Joo K, Lee J, Kozakov D, Vajda S, Mottarella S, Hall DR, Beglov D, Mamonov A, Xia B, Bohnuud T, Del Carpio CA, Ichiishi E, Marze N, Kuroda D, Roy Burman SS, Gray JJ, Chermak E, Cavallo L, Oliva R, Tovchigrechko A, Wodak SJ, Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment, Proteins, 84(S1):323-348, 2016
- Kakisaka M, Yamada K, Yamaji-Hasegawa A, Kobayashi T, Aida Y, Intrinsically disordered region of influenza A NP regulates viral genome packaging via interactions with viral RNA and host PI(4,5)P2, Virology, 496:116-126, 2016
- Yamada KD, Nishi H, Nakata J, Kinoshita K, Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins, Biophysics and Physicobiology, 13:157-163, 2016
- Tomii K, Yamada K, Systematic exploration of an efficient amino acid substitution matrix: MIQS, Methods in Molecular Biology, 1415:211-223, 2016
- Polat M, Takeshima SN, Hosomichi K, Kim J, Miyasaka T, Yamada K, Arainga M, Murakami T, Matsumoto Y, de la Barra Diaz V, Panei CJ, González ET, Kanemaki M, Onuma M, Giovambattista G, Aida Y, A new genotype of bovine leukemia virus in South America identified by NGS-based whole genome sequencing and molecular evolutionary genetic analysis, Retrovirology, 13(1):4, 2016
- Kakisaka M, Sasaki Y, Yamada K, Kondoh Y, Hikono H, Osada H, Tomii K, Saito T, Aida Y, A novel antiviral target structure involved in the RNA binding, dimerization, and nuclear export functions of the influenza A virus nucleoprotein, PLOS Pathogens, 11(7):e1005062, 2015
- Ito JI, Ikeda K, Yamada K, Mizuguchi K, Tomii K, PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs, Nucleic Acids Research, 43(D1):D392-D398, 2015
- Chutiwitoonchai N, Kakisaka M, Yamada K, Aida Y, Comparative analysis of seven viral nuclear export signals (NESs) reveals the crucial role of nuclear export mediated by the third NES consensus sequence of nucleoprotein (NP) in influenza A virus replication, PLOS ONE, 9(8):e105081, 2014
- Yamada K, Tomii K, Revisiting amino acid substitution matrices for identifying distantly related proteins, Bioinformatics, 30(3):317-325, 2014
- Sasaki Y, Hagiwara K, Kakisaka M, Yamada K, Murakami T, Aida Y, Importin α3/Qip1 is involved in multiplication of mutant influenza virus with alanine mutation at amino acid 9 independently of nuclear transport function, PLOS ONE, 8(1):e55765, 2013
- Yamada K, Koyama H, Hagiwara K, Ueda A, Sasaki Y, Kanesashi SN, Ueno R, Nakamura HK, Kuwata K, Shimizu K, Suzuki M, Aida Y, Identification of a novel compound with antiviral activity against influenza A virus depending on PA subunit of viral RNA polymerase, Microbes and Infection, 14(9):740-747, 2012
- Hagiwara K, Kondoh Y, Ueda A, Yamada K, Goto H, Watanabe T, Nakata T, Osada H, Aida Y, Discovery of novel antiviral agents directed against the influenza A virus nucleoprotein using photo-cross-linked chemical arrays, Biochemical and Biophysical Research Communications, 394:721-727, 2010
- 山田和範, 富井健太郎, 遠縁タンパク質検索に適した新規アミノ酸置換行列, 生物物理, 55(3):133-136, 2015
- Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, bioRxiv, 2022.04.14.488336, 2022
- Yan Z, Omori S, Yamada KD, Nishi H, Kinoshita K, Prediction and characterization of disorder-order transition regions in proteins by deep learning, bioRxiv, 2021.06.11.448022, 2021
- Yamada KD, Lin F, Nakamura T, Developing a novel recurrent neural network architecture with fewer parameters and good learning performance, bioRxiv, 2020.04.08.031484, 2020
- Yamada KD, Hyperparameter-free optimizer of gradient-descent method incorporating unit correction and moment estimation, bioRxiv, 348557, 2018
- Yamada KD, Kinoshita K, De novo profile generation based on sequence context specificity with the long short-term memory network, bioRxiv, 240515, 2018
- Yamada KD, Optimizing scoring function of dynamic programming of pairwise profile alignment using derivative free neural network, bioRxiv, 182493, 2018
Peer reviewed journal papers in English
Peer reviewed journal papers in Japanese
Preprint entries
Awards & Honors
- Research Award, Yamada KD, Kinoshita K, Development of de novo generator of amino acid sequence profile using LSTM framework, IIBMP2017, 2017
- Excellent Poster Award, Yamada K, Tomii K, Development of a novel amino acid substitution matrix for remote homology detection, IIBMP2013, 2013
- Poster Award, Yamada K, Tomii K, Developing a novel amino acid substitution matrix suitable for detecting distantly related proteins, BiWO2013, 2013
Research Product
| SPBuild | De novo profile generator based on recurrent neural network method, LSTM. |
| NT-AcPredictor | N-terminal acetylation predictor based on decision tree classification. |
| Nepal | PSSM-PSSM pairwise aligner with neural network enhanced scoring function of dynamic programming. |
| MAFFT-sparsecore | Benchmark results of MAFFT-sparasecore and other methods on large scale dataset. |
Classes
2021
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Interdisciplinary Information Science, Tohoku University, Fall semester
- Project based learning on Sendai X-Tech, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Interdisciplinary Information Science, Tohoku University, Fall semester
- Project based learning on Sendai X-Tech, Tohoku University, Fall semester
2020
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Interdisciplinary Information Science, Tohoku University, Fall semester
- Machine learning and natural language processing, Osaka University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Interdisciplinary Information Science, Tohoku University, Fall semester
- Machine learning and natural language processing, Osaka University, Fall semester
2019
- Big-data skill-up training, Tohoku University, Spring semester
- Data science training camp I, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Applied data science, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Data science basic, Tohoku University, Fall semester
- Interdisciplinary Information Science, Tohoku University, Fall semester
- Deep learning analysis on supercomputer system, Osaka University, Fall semester
- Big-data skill-up training, Tohoku University, Spring semester
- Data science training camp I, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Applied data science, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Data science basic, Tohoku University, Fall semester
- Interdisciplinary Information Science, Tohoku University, Fall semester
- Deep learning analysis on supercomputer system, Osaka University, Fall semester
2018
- Big-data skill-up training, Tohoku University, Spring semester
- Data science training camp I, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- GPU computing for Python users, Osaka University, Fall semester
- Big-data skill-up training, Tohoku University, Spring semester
- Data science training camp I, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- GPU computing for Python users, Osaka University, Fall semester
2017
- Data science training camp I, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Spring semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Fall semester
2016
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Data science training camp II / Big-data challenge, Tohoku University, Spring semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
2015
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
- Big-data skill-up training, Tohoku University, Fall semester
- Data science training camp I, Tohoku University, Fall semester
Professional Memberships
- 情報処理学会
Grants
- 人工知能で目指すアミノ酸配列類似性検索法の高速化および高感度化研究，科研費・若手研究 (2018 - 2020)，研究課題番号：18K18143，(代表)
- MAFFT多重アラインメントプログラムの大量配列データへの対応と機能拡張，科研費・基盤研究C (2016 - 2020)，研究課題番号：16K07464，(分担)
Temporarily Suspended Studies
- 一本のベクトルに様々な情報をエンコードして．また，そのベクトルから目的の情報だけを自在にとりだすことが可能な人工知能の開発．色々試したものの実現に至らず．
Contact
Email: y[a-z]ma[a-z]a@tohoku.ac.jp
ハンター試験なのですがメールアドレスの2個の[a-z]はそれぞれ英語アルファベットの内の互いに異なる小文字1個です．