研究概要のページ

Research achievements

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

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

Researcher and instructorMachine consciousness / Neural network
PhD studentNeural network / 3D point cloud / Image processing
PhD studentGenerative adversarial network

    Peer reviewed journal papers in English

  1. Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, Frontiers in Artificial Intelligence, accepted, 2022
  2. 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
  3. 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
  4. Yamada KD, Baladram MS, Lin F, Progress in research on implementing machine consciousness, Interdisciplinary Information Sciences, 28(1):95-105, 2022
  5. 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
  6. 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
  7. Baladram MS, Koike A, Yamada KD, Introduction to supervised machine learning for data science, Interdisciplinary Information Sciences, 26(1):87-121, 2020
  8. 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
  9. 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
  10. 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
  11. Nakamura T, Yamada KD, Tomii K, Katoh K, Parallelization of MAFFT for large-scale multiple sequence alignments, Bioinformatics, 34(14):2490-2492, 2018
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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
  21. Tomii K, Yamada K, Systematic exploration of an efficient amino acid substitution matrix: MIQS, Methods in Molecular Biology, 1415:211-223, 2016
  22. 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
  23. 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
  24. 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
  25. 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
  26. Yamada K, Tomii K, Revisiting amino acid substitution matrices for identifying distantly related proteins, Bioinformatics, 30(3):317-325, 2014
  27. 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
  28. 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
  29. 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
  30. Peer reviewed journal papers in Japanese

  31. 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
  32. Preprint entries

  33. Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, bioRxiv, 2022.04.14.488336, 2022
  34. 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
  35. 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
  36. Yamada KD, Hyperparameter-free optimizer of gradient-descent method incorporating unit correction and moment estimation, bioRxiv, 348557, 2018
  37. Yamada KD, Kinoshita K, De novo profile generation based on sequence context specificity with the long short-term memory network, bioRxiv, 240515, 2018
  38. Yamada KD, Optimizing scoring function of dynamic programming of pairwise profile alignment using derivative free neural network, bioRxiv, 182493, 2018
  1. Research Award, Yamada KD, Kinoshita K, Development of de novo generator of amino acid sequence profile using LSTM framework, IIBMP2017, 2017
  2. Excellent Poster Award, Yamada K, Tomii K, Development of a novel amino acid substitution matrix for remote homology detection, IIBMP2013, 2013
  3. Poster Award, Yamada K, Tomii K, Developing a novel amino acid substitution matrix suitable for detecting distantly related proteins, BiWO2013, 2013
De novo profile generator based on recurrent neural network method, LSTM.
N-terminal acetylation predictor based on decision tree classification.
PSSM-PSSM pairwise aligner with neural network enhanced scoring function of dynamic programming.
Benchmark results of MAFFT-sparasecore and other methods on large scale dataset.

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

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

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

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

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

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

2015

  • Big-data skill-up training, Tohoku University, Fall semester
  • Data science training camp I, Tohoku University, Fall semester
  • 情報処理学会
  • 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)
  • 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.

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.