最終更新日2017年02月01日

氏名

ハマダ ミチアキ

浜田 道昭

職名

准教授

所属理工学術院

(先進理工学部)

連絡先

メールアドレス

メールアドレス
mhamada@waseda.jp

URL等

WebページURL

https://sites.google.com/site/hamabioinflab/(浜田道昭(バイオインフォマティクス)研究室)

https://sites.google.com/site/michiakihamada/(個人)

https://sites.google.com/site/wasedabioinf/(早稲田バイオインフォマティクスコミュニティ)

本属以外の学内所属

兼担

理工学術院(大学院先進理工学研究科)

学内研究所等

構造生物・創薬研究所

研究所員 2015年-

ヒューマンパフォーマンス研究所

研究所員 2017年-

早稲田バイオサイエンスシンガポール研究所

研究所員 2017年-

学歴・学位

学歴

2000年04月-2002年03月 東北大学 理学研究科 数学専攻

学位

博士(理学) 課程 東京工業大学 生命・健康・医療情報学

経歴

2002年04月-2004年09月株式会社富士総合研究所(現:みずほ情報総研株式会社) 研究員
2004年10月-2006年07月(社名変更により) みずほ情報総研株式会社 研究員
2006年07月-2010年09月みずほ情報総研株式会社 コンサルタント
2010年10月-2014年03月東京大学大学院新領域創成科学研究科情報生命科学専攻 特任准教授
2014年04月-現在 早稲田大学 理工学術院 先進理工学研究科 電気・情報生命専攻 准教授

所属学協会

日本バイオインフォマティクス学会 理事

日本分子生物学会

日本RNA学会

委員歴・役員歴(学外)

2014年04月-日〜 日本バイオインフォマティクス学会 理事

研究分野

キーワード

バイオインフォマティクス;ゲノム科学;データマイニング;機械学習;プライバシー保護;

科研費分類

情報学 / 情報学フロンティア / 生命・健康・医療情報学

論文

Efficient calculation of exact probability distributions of integer features on RNA secondary structures

Mori, Ryota;Hamada, Michiaki;Asai, Kiyoshi

BMC GENOMICS15p.S62014年-2014年

DOIWoS

詳細

ISSN:1471-2164

RNA structural alignments part II: non-Sankoff approaches for structural alignments

Asai K. and Hamada M.

Methods Mol. Biol.1097p.291 - 3012014年-

Analysis of base-pairing probabilities of RNA molecules involved in protein-RNA interactions

Iwakiri J. and Kameda T. and Asai K. and Hamada M.

Bioinformatics29p.2524 - 25282013年-

Fighting against uncertainty: an essential issue in bioinformatics

Hamada M.

Brief. Bioinformatics15p.748 - 7672014年-

CentroidAlign-Web: A Fast and Accurate Multiple Aligner for Long Non-Coding RNAs

Yonemoto H. and Asai K. and Hamada M.

Int J Mol Sci14p.6144 - 61562013年-

Direct updating of an RNA base-pairing probability matrix with marginal probability constraints

Hamada M.

J. Comput. Biol.19p.1265 - 12762012年-

PBSIM: PacBio reads simulator--toward accurate genome assembly

Ono Y. and Asai K. and Hamada M.

Bioinformatics29p.119 - 1212013年-

Shape-based alignment of genomic landscapes in multi-scale resolution

Ashida H. and Asai K. and Hamada M.

Nucleic Acids Res.40p.6435 - 64482012年-

A classification of bioinformatics algorithms from the viewpoint of maximizing expected accuracy (MEA)

Hamada M. and Asai K.

J. Comput. Biol.19p.532 - 5492012年-

Probabilistic alignments with quality scores: an application to short-read mapping toward accurate SNP/indel detection

Hamada M. and Wijaya E. and Frith M. C. and Asai K.

Bioinformatics27p.3085 - 30922011年-

IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming

Sato K. and Kato Y. and Hamada M. and Akutsu T. and Asai K.

Bioinformatics27p.85 - 932011年-

CentroidHomfold-LAST: accurate prediction of RNA secondary structure using automatically collected homologous sequences

Hamada M. and Yamada K. and Sato K. and Frith M. C. and Asai K.

Nucleic Acids Res.39p.W100 - 1062011年-

Antagonistic RNA aptamer specific to a heterodimeric form of human interleukin-17A/F

Adachi H. and Ishiguro A. and Hamada M. and Sakota E. and Asai K. and Nakamura Y.

Biochimie93p.1081 - 10882011年-

Generalized centroid estimators in bioinformatics

Hamada M. and Kiryu H. and Iwasaki W. and Asai K.

PLoS ONE6p.e164502011年-

Prediction of RNA secondary structure by maximizing pseudo-expected accuracy

Hamada M. and Sato K. and Asai K.

BMC Bioinformatics11p.5862010年-

Improving the accuracy of predicting secondary structure for aligned RNA sequences

Hamada M. and Sato K. and Asai K.

Nucleic Acids Res.39p.393 - 4022011年-

RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming

Kato Y. and Sato K. and Hamada M. and Watanabe Y. and Asai K. and Akutsu T.

Bioinformatics26p.i460 - 4662010年-

Parameters for accurate genome alignment

Frith M. C. and Hamada M. and Horton P.

BMC Bioinformatics11p.802010年-

CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score

Hamada M. and Sato K. and Kiryu H. and Mituyama T. and Asai K.

Bioinformatics25p.3236 - 32432009年-

Predictions of RNA secondary structure by combining homologous sequence information

Hamada M. and Sato K. and Kiryu H. and Mituyama T. and Asai K.

Bioinformatics25p.i330 - 3382009年-

CENTROIDFOLD: a web server for RNA secondary structure prediction

Sato K. and Hamada M. and Asai K. and Mituyama T.

Nucleic Acids Res.37p.W277 - 2802009年-

Prediction of RNA secondary structure using generalized centroid estimators

Hamada M. and Kiryu H. and Sato K. and Mituyama T. and Asai K.

Bioinformatics25p.465 - 4732009年-

Software.ncrna.org: web servers for analyses of RNA sequences

Asai K. and Kiryu H. and Hamada M. and Tabei Y. and Sato K. and Matsui H. and Sakakibara Y. and Terai G. and Mituyama T.

Nucleic Acids Res.36p.W75 - 782008年-

Mining frequent stem patterns from unaligned RNA sequences

Hamada M. and Tsuda K. and Kudo T. and Kin T. and Asai K.

Bioinformatics22p.2480 - 24872006年-

Reference-free prediction of rearrangement breakpoint reads

Wijaya, Edward;Shimizu, Kana;Asai, Kiyoshi;Hamada, Michiaki

BIOINFORMATICS30(18)p.2559 - 25672014年-2014年

DOIWoS

詳細

ISSN:1367-4803

Privacy-preserving search for chemical compound databases

Shimizu, Kana; Nuida, Koji; Nuida, Koji; Arai, Hiromi; Mitsunari, Shigeo; Attrapadung, Nuttapong; Hamada, Michiaki; Tsuda, Koji; Hirokawa, Takatsugu; Sakuma, Jun; Hanaoka, Goichiro; Asai, Kiyoshi

BMC Bioinformatics16(18)2015年12月-2015年12月 

DOIScopus

詳細

概要:© 2015 Shimizu et al. Background: Searching for similar compounds in a database is the most important process for in-silico drug screening. Since a query compound is an important starting point for the new drug, a query holder, who is afraid of the query being monitored by the database server, usually downloads all the records in the database and uses them in a closed network. However, a serious dilemma arises when the database holder also wants to output no information except for the search results, and such a dilemma prevents the use of many important data resources. Results: In order to overcome this dilemma, we developed a novel cryptographic protocol that enables database searching while keeping both the query holder's privacy and database holder's privacy. Generally, the application of cryptographic techniques to practical problems is difficult because versatile techniques are computationally expensive while computationally inexpensive techniques can perform only trivial computation tasks. In this study, our protocol is successfully built only from an additive-homomorphic cryptosystem, which allows only addition performed on encrypted values but is computationally efficient compared with versatile techniques such as general purpose multi-party computation. In an experiment searching ChEMBL, which consists of more than 1,200,000 compounds, the proposed method was 36,900 times faster in CPU time and 12,000 times as efficient in communication size compared with general purpose multi-party computation. Conclusion: We proposed a novel privacy-preserving protocol for searching chemical compound databases. The proposed method, easily scaling for large-scale databases, may help to accelerate drug discovery research by making full use of unused but valuable data that includes sensitive information.

AMAP: A pipeline for whole-genome mutation detection in Arabidopsis thaliana

Kotaro Ishii, Yusuke Kazama, Tomonari Hirano, Michiaki Hamada, Yukiteru Ono, Mieko Yamada, Tomoko Abe

Genes & Genetic Systems査読有りin press(4)p.229 - 2332016年-2016年

CiNii

詳細

ISSN:1341-7568

概要:

Detection of mutations at the whole-genome level is now possible by the use of high-throughput sequencing. However, determining mutations is a time-consuming process due to the number of false positives provided by mutation-detecting programs. AMAP (automated mutation analysis pipeline) was developed to overcome this issue. AMAP integrates a set of well-validated programs for mapping (BWA), removal of potential PCR duplicates (Picard), realignment (GATK) and detection of mutations (SAMtools, GATK, Pindel, BreakDancer and CNVnator). Thus, all types of mutations such as base substitution, deletion, insertion, translocation and chromosomal rearrangement can be detected by AMAP. In addition, AMAP automatically distinguishes false positives by comparing lists of candidate mutations in sequenced mutants. We tested AMAP by inputting already analyzed read data derived from three individual Arabidopsis thaliana mutants and confirmed that all true mutations were included in the list of candidate mutations. The result showed that the number of false positives was reduced to 12% of that obtained in a previous analysis that lacked a process of reducing false positives. Thus, AMAP will accelerate not only the analysis of mutation induction by individual mutagens but also the process of forward genetics.

長鎖ノンコーディングRNAのためのバイオインフォマティクス

岩切 淳一;浜田 道昭

生物物理56(4)p.217 - 2202016年-2016年

CiNii

詳細

ISSN:0582-4052

概要:

Recent advances in high throughput sequencing technologies unveiled that large number of long non-coding RNAs (lncRNAs) are transcribed from human genome. Currently, these emerging transcripts are needed to be functionally classified and annotated. Here we review several bioinformatic approaches for analyzing the important characteristics of the lncRNAs toward discovering their functions: 1) tissue specificities of lncRNA expressions, 2) two types of macromolecular interactions (RNA-RNA and RNA-protein interactions), 3) secondary structures of lncRNAs.

Training alignment parameters for arbitrary sequencers with LAST-TRAIN

Hamada, Michiaki; Hamada, Michiaki; Hamada, Michiaki; Ono, Yukiteru; Asai, Kiyoshi; Asai, Kiyoshi; Frith, Martin C.; Frith, Martin C.; Frith, Martin C.; Hancock, John

Bioinformatics33(6)p.926 - 9282017年01月-2017年01月 

PubMedDOIScopus

詳細

ISSN:13674803

概要:© The Author 2016.LAST-TRAIN improves sequence alignment accuracy by inferring substitution and gap scores that fit the frequencies of substitutions, insertions, and deletions in a given dataset. We have applied it to mapping DNA reads from IonTorrent and PacBio RS, and we show that it reduces reference bias for Oxford Nanopore reads.

Computational prediction of lncRNA-mRNA interactionsby integrating tissue specificity in human transcriptome.

Iwakiri Junichi;Terai Goro;Hamada Michiaki

Biology direct12(1)2017年-2017年

PubMedDOI

詳細

ISSN:1745-6150

概要::Long noncoding RNAs (lncRNAs) play a key role in normal tissue differentiation and cancer development through their tissue-specific expression in the human transcriptome. Recent investigations of macromolecular interactions have shown that tissue-specific lncRNAs form base-pairing interactions with various mRNAs associated with tissue-differentiation, suggesting that tissue specificity is an important factor controlling human lncRNA-mRNA interactions.Here, we report investigations of the tissue specificities of lncRNAs and mRNAs by using RNA-seq data across various human tissues as well as computational predictions of tissue-specific lncRNA-mRNA interactions inferred by integrating the tissue specificity of lncRNAs and mRNAs into our comprehensive prediction of human lncRNA-RNA interactions. Our predicted lncRNA-mRNA interactions were evaluated by comparisons with experimentally validated lncRNA-mRNA interactions (between the TINCR lncRNA and mRNAs), showing the improvement of prediction accuracy over previous prediction methods that did not account for tissue specificities of lncRNAs and mRNAs. In addition, our predictions suggest that the potential functions of TINCR lncRNA not only for epidermal differentiation but also for esophageal development through lncRNA-mRNA interactions.;REVIEWERS:This article was reviewed by Dr. Weixiong Zhang and Dr. Bojan Zagrovic.

RIblast: An ultrafast RNA-RNA interaction prediction system based on a seed-and-extension approach.

Fukunaga Tsukasa;Hamada Michiaki

Bioinformatics (Oxford, England)2017年-2017年

PubMedDOI

詳細

ISSN:1367-4811

概要:Motivation:LncRNAs play important roles in various biological processes. Although more than 58,000 human lncRNA genes have been discovered, most known lncRNAs are still poorly characterised. One approach to understanding the functions of lncRNAs is the detection of the interacting RNA target of each lncRNA. Because experimental detections of comprehensive lncRNA-RNA interactions are difficult, computational prediction of lncRNA-RNA interactions is an indispensable technique. However, the high computational costs of existing RNA-RNA interaction prediction tools prevent their application to largescale lncRNA datasets.;Results:Here, we present "RIblast", an ultrafast RNA-RNA interaction prediction method based on the seed-and-extension approach. RIblast discovers seed regions using suffix arrays and subsequently extends seed regions based on an RNA secondary structure energy model. Computational experiments indicate that RIblast achieves a level of prediction accuracy similar to those of existing programs, but at speeds over 64 times faster than existing programs.;Availability:The source code of RIblast is freely available at https://github.com/fukunagatsu/RIblast .;Contact:t.fukunaga@kurenai.waseda.jp , mhamada@waseda.jp.;Supplementary information:Supplementary data are available at Bioinformatics online.

RNA secondary structure prediction from multi-aligned sequences.

Hamada Michiaki

Methods in molecular biology (Clifton, N.J.)12692015年-2015年

PubMedDOI

詳細

ISSN:1940-6029

概要::It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.

A semi-supervised learning approach for RNA secondary structure prediction.

Yonemoto Haruka;Asai Kiyoshi;Hamada Michiaki

Computational biology and chemistry572015年-2015年

PubMedDOI

詳細

ISSN:1476-928X

概要::RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited.

Learning chromatin states with factorized information criteria.

Hamada Michiaki;Ono Yukiteru;Fujimaki Ryohei;Asai Kiyoshi

Bioinformatics (Oxford, England)31(15)2015年-2015年

PubMedDOI

詳細

ISSN:1367-4811

概要:MOTIVATION:Recent studies have suggested that both the genome and the genome with epigenetic modifications, the so-called epigenome, play important roles in various biological functions, such as transcription and DNA replication, repair, and recombination. It is well known that specific combinations of histone modifications (e.g. methylations and acetylations) of nucleosomes induce chromatin states that correspond to specific functions of chromatin. Although the advent of next-generation sequencing (NGS) technologies enables measurement of epigenetic information for entire genomes at high-resolution, the variety of chromatin states has not been completely characterized.;RESULTS:In this study, we propose a method to estimate the chromatin states indicated by genome-wide chromatin marks identified by NGS technologies. The proposed method automatically estimates the number of chromatin states and characterize each state on the basis of a hidden Markov model (HMM) in combination with a recently proposed model selection technique, factorized information criteria. The method is expected to provide an unbiased model because it relies on only two adjustable parameters and avoids heuristic procedures as much as possible. Computational experiments with simulated datasets show that our method automatically learns an appropriate model, even in cases where methods that rely on Bayesian information criteria fail to learn the model structures. In addition, we comprehensively compare our method to ChromHMM on three real datasets and show that our method estimates more chromatin states than ChromHMM for those datasets.

Bioinformatics tools for lncRNA research.

Iwakiri Junichi;Hamada Michiaki;Asai Kiyoshi

Biochimica et biophysica acta1859(1)2016年-2016年

PubMedDOI

詳細

ISSN:0006-3002

概要::Current experimental methods to identify the functions of a large number of the candidates of long non-coding RNAs (lncRNAs) are limited in their throughput. Therefore, it is essential to know which tools are effective for understanding lncRNAs so that reasonable speed and accuracy can be achieved. In this paper, we review the currently available bioinformatics tools and databases that are useful for finding non-coding RNAs and analyzing their structures, conservation, interactions, co-expressions and localization. This article is part of a Special Issue entitled: Clues to long noncoding RNA taxonomy1, edited by Dr. Tetsuro Hirose and Dr. Shinichi Nakagawa.

Comprehensive prediction of lncRNA-RNA interactions in human transcriptome.

Terai Goro;Iwakiri Junichi;Kameda Tomoshi;Hamada Michiaki;Asai Kiyoshi

BMC genomics17 Suppl 12016年-2016年

PubMedDOI

詳細

ISSN:1471-2164

概要:MOTIVATION:Recent studies have revealed that large numbers of non-coding RNAs are transcribed in humans, but only a few of them have been identified with their functions. Identification of the interaction target RNAs of the non-coding RNAs is an important step in predicting their functions. The current experimental methods to identify RNA-RNA interactions, however, are not fast enough to apply to a whole human transcriptome. Therefore, computational predictions of RNA-RNA interactions are desirable, but this is a challenging task due to the huge computational costs involved.;RESULTS:Here, we report comprehensive predictions of the interaction targets of lncRNAs in a whole human transcriptome for the first time. To achieve this, we developed an integrated pipeline for predicting RNA-RNA interactions on the K computer, which is one of the fastest super-computers in the world. Comparisons with experimentally-validated lncRNA-RNA interactions support the quality of the predictions. Additionally, we have developed a database that catalogs the predicted lncRNA-RNA interactions to provide fundamental information about the targets of lncRNAs.

Rtools: a web server for various secondary structural analyses on single RNA sequences.

Hamada Michiaki;Ono Yukiteru;Kiryu Hisanori;Sato Kengo;Kato Yuki;Fukunaga Tsukasa;Mori Ryota;Asai Kiyoshi

Nucleic acids research44(W1)2016年-2016年

PubMedDOI

詳細

ISSN:1362-4962

概要::The secondary structures, as well as the nucleotide sequences, are the important features of RNA molecules to characterize their functions. According to the thermodynamic model, however, the probability of any secondary structure is very small. As a consequence, any tool to predict the secondary structures of RNAs has limited accuracy. On the other hand, there are a few tools to compensate the imperfect predictions by calculating and visualizing the secondary structural information from RNA sequences. It is desirable to obtain the rich information from those tools through a friendly interface. We implemented a web server of the tools to predict secondary structures and to calculate various structural features based on the energy models of secondary structures. By just giving an RNA sequence to the web server, the user can get the different types of solutions of the secondary structures, the marginal probabilities such as base-paring probabilities, loop probabilities and accessibilities of the local bases, the energy changes by arbitrary base mutations as well as the measures for validations of the predicted secondary structures. The web server is available at http://rtools.cbrc.jp, which integrates software tools, CentroidFold, CentroidHomfold, IPKnot, CapR, Raccess, Rchange and RintD.

Improved Accuracy in RNA-Protein Rigid Body Docking by Incorporating Force Field for Molecular Dynamics Simulation into the Scoring Function

Iwakiri, Junichi; Hamada, Michiaki; Hamada, Michiaki; Asai, Kiyoshi; Asai, Kiyoshi; Kameda, Tomoshi

Journal of Chemical Theory and Computation12(9)p.4688 - 46972016年09月-2016年09月 

DOIScopus

詳細

ISSN:15499618

概要:© 2016 American Chemical Society.RNA-protein interactions play fundamental roles in many biological processes. To understand these interactions, it is necessary to know the three-dimensional structures of RNA-protein complexes. However, determining the tertiary structure of these complexes is often difficult, suggesting that an accurate rigid body docking for RNA-protein complexes is needed. In general, the rigid body docking process is divided into two steps: generating candidate structures from the individual RNA and protein structures and then narrowing down the candidates. In this study, we focus on the former problem to improve the prediction accuracy in RNA-protein docking. Our method is based on the integration of physicochemical information about RNA into ZDOCK, which is known as one of the most successful computer programs for protein-protein docking. Because recent studies showed the current force field for molecular dynamics simulation of protein and nucleic acids is quite accurate, we modeled the physicochemical information about RNA by force fields such as AMBER and CHARMM. A comprehensive benchmark of RNA-protein docking, using three recently developed data sets, reveals the remarkable prediction accuracy of the proposed method compared with existing programs for docking: the highest success rate is 34.7% for the predicted structure of the RNA-protein complex with the best score and 79.2% for 3,600 predicted ones. Three full atomistic force fields for RNA (AMBER94, AMBER99, and CHARMM22) produced almost the same accurate result, which showed current force fields for nucleic acids are quite accurate. In addition, we found that the electrostatic interaction and the representation of shape complementary between protein and RNA plays the important roles for accurate prediction of the native structures of RNA-protein complexes.

Computational prediction of lncRNA-mRNA interactionsby integrating tissue specificity in human transcriptome

Iwakiri, Junichi; Terai, Goro; Hamada, Michiaki; Hamada, Michiaki; Hamada, Michiaki; Hamada, Michiaki; Hamada, Michiaki

Biology Direct12(1)2017年06月-2017年06月 

DOIScopus

詳細

概要:© 2017 The Author(s). Long noncoding RNAs (lncRNAs) play a key role in normal tissue differentiation and cancer development through their tissue-specific expression in the human transcriptome. Recent investigations of macromolecular interactions have shown that tissue-specific lncRNAs form base-pairing interactions with various mRNAs associated with tissue-differentiation, suggesting that tissue specificity is an important factor controlling human lncRNA-mRNA interactions. Here, we report investigations of the tissue specificities of lncRNAs and mRNAs by using RNA-seq data across various human tissues as well as computational predictions of tissue-specific lncRNA-mRNA interactions inferred by integrating the tissue specificity of lncRNAs and mRNAs into our comprehensive prediction of human lncRNA-RNA interactions. Our predicted lncRNA-mRNA interactions were evaluated by comparisons with experimentally validated lncRNA-mRNA interactions (between the TINCR lncRNA and mRNAs), showing the improvement of prediction accuracy over previous prediction methods that did not account for tissue specificities of lncRNAs and mRNAs. In addition, our predictions suggest that the potential functions of TINCR lncRNA not only for epidermal differentiation but also for esophageal development through lncRNA-mRNA interactions. Reviewers: This article was reviewed by Dr. Weixiong Zhang and Dr. Bojan Zagrovic.

書籍等出版物

生命情報処理における機械学習 : 多重検定と推定量設計 = Machine learning in bioinformatics

瀬々潤, 浜田道昭著

講談社2015年-2015年

LINK

詳細

ISBN:9784061529113;

講演・口頭発表等

ヒトトランスクリプトームにおける網羅的 lncRNA-RNA 相互作用予測

第17回日本RNA学会年会2015年07月

詳細

ポスター発表

次世代バイオインフォマティクス技術の研究開発

医薬会セミナー

詳細

口頭発表(一般)

【特別講演】正確な塩基対推定のためのRNAの2次構造予測--分布を考えることの重要性--

分子計算研究会

詳細

口頭発表(一般)

【オーガナイズド講演】非整列RNA配列群からの頻出ステムパターンのマイニング

第9回情報論的学習理論ワークショップ (IBIS 2006)

詳細

口頭発表(一般)

ヒトトランスクリプトームにおける網羅的lncRNA-RNA 相互作用予測

第17回日本RNA学会年会

詳細

ポスター発表

RNA 発現量を用いた組織特異的 lncRNA-mRNA 相互作用予測

第17回日本RNA学会年会

詳細

ポスター発表

分子動力学計算を用いた蛋白質・RNA 複合体立体構 予測

第17回日本RNA学会年会

詳細

ポスター発表

早稲田大学理工学術院バイオインフォマティクス研究室におけるNGS関連研究の紹介

第4回NGS現場の会

詳細

ポスター発表

Pipeline for whole-genome analysis of heavy-ion-induced mutants in Arabidopsis thaliana

The 26th international conference on arabidopsis research

詳細

ポスター発表

全ゲノム変異解析のためのパイプラインの構築

日本育種学会 第127回講演会プログラム 2015年春季

詳細

ポスター発表

Pipeline for whole-genome analysis of heavy-ion-induced mutants

International Symposium on Genome Science 2015

詳細

ポスター発表

Prediction of joint RNA secondary structure by using their homologous sequence information

GIW2014

詳細

ポスター発表

Learning chromatin states with factorized information criteria

生命医薬情報学連合大会2014年大会

詳細

ポスター発表

A comprehensive prediction of RNA-RNA interactions from human transcriptome

2014RNAインフォマティクス道場

詳細

ポスター発表

RNA2次構造情報解析のための統合ウェブ

第16回日本RNA学会

詳細

ポスター発表

Credibility Limit は推定二次構造の定量的な信頼度を示す

第16回日本RNA学会

詳細

ポスター発表

RNA-タンパク質相互作用予測手法の開発

第16回日本RNA学会

詳細

ポスター発表

分子動力学計算を用いた蛋白質・RNA 複合体立体構造予測

第16回日本RNA学会

詳細

ポスター発表

Centroid series: fundamental programs of sequence analysis for non‐coding RNAs

バイオインフォマティクスとゲノム医療─その課題と将来展望─

詳細

ポスター発表

Using Deep Learning as a Classi er for Biological Datasets --Hepatitis Dataset as an example--

JSBi2013

詳細

ポスター発表

A method for calculating stability of RNA secondary structure

JSBi2013

詳細

ポスター発表

Inferring constraints on amino acids from protein sequence alignment

BIWO2013

詳細

ポスター発表

A fast and exact calculation for various score distributions of RNA secondary structure

BIWO2013

詳細

ポスター発表

The 3D structure prediction of Protein and RNA complex

BIWO2013

詳細

ポスター発表

Goichiro Hanaoka, Kiyoshi Asail

An efficient privacy-preserving similarity search protocol for chemical compound databases

詳細

ポスター発表

2次構造情報を基盤とした RNA バイオインフォマティクス技 術・ツールの最近の進展,第15回日本RNA学会

2013年7月

詳細

ポスター発表

タンパク質-RNA相互作用におけるRNA2次構造認識機構:塩基対確率に基づく解析

第15回日本RNA学会

詳細

ポスター発表

蛋白質-RNA の複合体立体構造予測

第15回日本RNA学会

詳細

ポスター発表

Privacy-preserving search for a chemical compound database

ISMB/ECCB 2013

詳細

ポスター発表

半教師あり学習を用いたRNA二次構造予測アルゴリズムの提案

第35回日本分子生物学会

詳細

ポスター発表

カノニカル分布に基づくRNA二次構造の存在確率分布記述手法の開発

第35回日本分子生物学会

詳細

ポスター発表

Developing Privacy-preserving database search protocol for chemical compound libraries

BIWO2012

詳細

ポスター発表

Reference Free Approach for Detecting Chromosomal Rearrangement

BIWO2012

詳細

ポスター発表

Semi-supervised Learning Approach to Predict RNA Secondary Structure

BIWO2012

詳細

ポスター発表

PBSIM: PacBio reads simulator - toward accurate genome assembly

BIWO2012

詳細

ポスター発表

A quantitation and visualization technique for understanding high dimensional distribution of RNA structures

BIWO2012

詳細

ポスター発表

BIWO2012

2012.

詳細

ポスター発表

BIWO2012

2012.

詳細

ポスター発表

Reference Free Approach for Detecting Chromosomal Rearrangement

IIBMP2012 (CBI/JSBi/Omix)

詳細

ポスター発表

A Method for Measuring RNA Secondary Structure Stability and Reliability Based on Canonical Distribution

IIBMP2012 (CBI/JSBi/Omix)

詳細

ポスター発表

Semi-supervised Learning Approach to Predict RNA Secondary Structure

IIBMP2012 (CBI/JSBi/Omix)

詳細

ポスター発表

A Classification of Bioinformatics Algorithms from the Viewpoint of Maximizing Expected Accuracy (MEA)

IIBMP2012 (CBI/JSBi/Omix)

詳細

ポスター発表

PBSIM: PacBio reads simulator - toward accurate genome assembly

IIBMP2012 (CBI/JSBi/Omix)

詳細

ポスター発表

カノニカル分布に基づいたRNAの2次構造安定性解析の開発

第14回日本RNA学会

詳細

ポスター発表

半教師あり学習を用いたRNAの2次構造予測アルゴリズムの提案

第14回日本RNA学会

詳細

ポスター発表

検索行動におけるプライバシ保護

2012年度人工知能学会全国大会(第26回)

詳細

ポスター発表

A CLASSIFICATION OF BIOINFORMATICS ALGORITHMS FROM THE VIEWPOINT OF MAXIMIZING EXPECTED ACCURACY (MEA)

BIWO2011 (Jan, 2012).

詳細

ポスター発表

PROBABILISTIC ALIGNMENTS WITH QUALITY SCORES: AN APPLICATION TO SHORT-READ MAPPING TOWARD ACCURATE SNP/INDEL DETECTION

BIWO2011 (Jan, 2012)

詳細

ポスター発表

DEVELOPING NOVEL PROTOCOL FOR PRIVACY-PRESERVING SEARCH OF BIT-VECTORS AND ITS APPLICATION TO THE CHEMICAL COMPOUNDS LIBRARY SEARCH

BIWO2011 (Jan, 2012)

詳細

ポスター発表

Introduction to RNA informatics and maximum expected accuracy (MEA) principle

東京大学医科学研究所中井研究室セミナー

詳細

ポスター発表

Protein-Coding Based Assembly of Metagenomic Next-Generation Sequencing Data

CBI/JSBi2011

詳細

ポスター発表

Privacy preserving search for chemical compound libraries

CBI/JSBi2011

詳細

ポスター発表

2次構造情報に基づくRNA情報解析技術の現在と今後

RNA/RNPを見つける会2011

詳細

口頭発表(一般)

A New Approach to Elucidate Genomic Landscapes in MultiscaleResolution

5th Asian Young Researchers Conferenceon Computational and Omics Biology(AYRCOB)

詳細

ポスター発表

Centroidシリーズ:2次構造を基盤としたRNA情報解析ツール群

次世代バイオインフォマティクス研究会2011

詳細

ポスター発表

リードのクオリティ情報を考慮したNGSデータ解析技術

次世代バイオインフォマティクス研究会2011

詳細

ポスター発表

プライバシー保護配列解析技術の開発に向けて

次世代バイオインフォマティクス研究会2011

詳細

ポスター発表

Centroid series: fundamental programs of sequence analysis for non-coding RNAs

The 16th Annual Meeting of the RNA Society (RNA2011)

詳細

ポスター発表

Antagonistic RNA Aptamer Specific to a Heterodimeric Form of Human Interleukin-17 A/F

The 16th Annual Meeting of the RNA Society (RNA2011)

詳細

ポスター発表

Binary Estimation Problems in Structural Information Analysis of RNA

The 16th Annual Meeting of the RNA Society (RNA2011). Jun 2011.

詳細

ポスター発表

RactIP: Fast and Accurate Prediction of RNA-RNA Interaction Using Integer Programming

The 16th Annual Meeting of the RNA Society (RNA2011). Jun 2011.

詳細

ポスター発表

IPknot: Fast and Accurate Prediction of RNA Secondary Structures with Pseudoknots Using Integer Programming

The 16th Annual Meeting of the RNA Society (RNA2011). Jun 2011.

詳細

ポスター発表

Probabilistic alignments with quality scores: An application to short-read mapping toward accurate SNP/indel detection

第一回NGS現場の会研究会

詳細

ポスター発表

Software tools for RNA sequence analysis in ncrna.org

PSB2011.

詳細

ポスター発表

Centroid series: fundamental programs of sequence analysis for non-coding RNAs

ISMB2010. [Poster

詳細

ポスター発表

RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming

ISMB2010(Poster).

詳細

ポスター発表

How (not) to Align Genomes

The 20th International Conference on Genome Informatics December 14-16

詳細

ポスター発表

CentroidFold: Predictions of RNA Secondary Structure for Estimating Accurate Base-pairs

第32回日本分子生物学会

詳細

ポスター発表

CentroidHomfold: Prediction of RNA secondary structure by combining homologous sequence information

第32回日本分子生物学会

詳細

ポスター発表

CentroidHomfold: 相同配列群の情報を利用したRNAの2次構造予測

CBRC 2009

詳細

口頭発表(一般)

CBRC 2009

2009/12/04. (ポスター発表

詳細

ポスター発表

CentroidHomfold: 相同配列群の情報を利用したRNAの2次構造予測

生命情報科学研究セミナー

詳細

口頭発表(一般)

期待精度最大化推定とバイオインフォマティクス

第21回T-PRIMALセミナー

詳細

口頭発表(一般)

Centroid シリーズ:RNA の2構造予測/アラインメントのためのツール群

第 8 回 新しい RNA/RNP を見つける会

詳細

口頭発表(一般)

CentroidFold: Predictions of RNA Secondary Structure for Estimating Accurate Base-pairs

The 9th Workshop on Algorithms in Bioinformatics (WABI 2009). (Poster presentation

詳細

ポスター発表

CentroidFold: RNA 二次構造予測ウェブサーバー

第11回RNAミーティング

詳細

口頭発表(一般)

Predictions of RNA secondary structure by combining homologous sequence information

IThe 17th Annual International Conference on Intelligent Systems for Molecular Biology and 7th Annual European Conference on Computational Biology (ISMB/ECCB 2009). (Oral presentation

詳細

ポスター発表

CentroidFold: Predictions of RNA Secondary Structure for Estimating Accurate Base-pairs,The 17th Annual International Conference on Intelligent Systems for Molecular Biology and 7th Annual European Conference on Computational Biology (ISMB/ECCB 2009). (poster presentation

Reviewed international conference)

詳細

ポスター発表

正確な塩基対推定のためのRNAの2次構造予測 分布を考えることの重要性

第1回生命情報科学若手の会

詳細

口頭発表(一般)

A Non-Parametric Bayesian Approach for Predicting RNA Secondary Structures

The 2008 Annual Conference of the Japanese Society for Bioinformatics (JSBi2008). (poster presentation

詳細

ポスター発表

期待精度を最大化するRNA情報解析手法の開発

第31回日本分子生物学会(BMB2008)

詳細

ポスター発表

期待精度を最大化するRNAの2次構造予測手法

CBRC2008

詳細

口頭発表(一般)

第26回生命情報科学研究セミナー

2008/9/26.(口頭発表

詳細

口頭発表(一般)

期待精度を最大化するRNA情報解析手法の開発

新しいRNA/RNPを見つける会

詳細

口頭発表(一般)

RNA配列群に現れる局所安定2次構造の大規模類似性探索

CBRC 2007

詳細

ポスター発表

Large-Scale Similarity Search for Locally Stable Secondary Structures among RNA Sequences

JSBI2007. (poster presentation)

詳細

ポスター発表

RNA配列群に現われる局所安定2 次構造の大規模類似性探索

第6回新しいRNA/RNPを見つける会

詳細

口頭発表(一般)

Mining Local Secondary Structure Motifs from Unaligned RNA Sequences Using Graph Mining Techniques

5th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB)

詳細

ポスター発表

RNAmine: Frequent Stem Pattern Miner from RNAs

The 17th International Conference on Genome Informatics (GIW2006).(poster presentation)

詳細

ポスター発表

非整列RNA配列群からの頻出ステムパターンのマイニング

東北大学理学部数学科情報学セミナー

詳細

口頭発表(一般)

RNA配列群からの頻出ステムパターンの抽出

新しいRNA/RNPを見つける会 in お台場

詳細

口頭発表(一般)

サポートベクトルマシンを用いた機能性RNAファミリーの分類

新しいRNA/RNPを見つける会 in 鶴岡

詳細

口頭発表(一般)

Support Vector Machineを用いた機能性RNAファミリーの分類

第7回日本RNA学会

詳細

口頭発表(一般)

DrugMLとGrid創薬

日本コンピュータ化学会2004春季年会

詳細

ポスター発表

Grid技術とXMLデータベースを用いた創薬プラットフォームの構築とその応用

32回構造活性相関シンポジウム

詳細

ポスター発表

DrugMLとグリッド創薬

31回構造活性相関シンポジウム

詳細

ポスター発表

「ナレッジ活用による研究支援環境 知見プラットフォーム」のご紹介 3次元SEM像シミュレータへの適用

XSLSI テスティングシンポジウム/2002. (口頭発表)

詳細

口頭発表(一般)

外部研究資金

科学研究費採択状況

研究種別:若手研究(A)

機能エレメントと深層学習に基づく長鎖ノンコーディングRNAの機能分類

2016年04月-2020年03月

研究分野:生命・健康・医療情報学

配分額:¥23400000

研究種別:新学術領域研究(研究領域提案型)

ヒストンバリアントに基づくクロマチンの機能の推定

2016年04月-2018年03月

配分額:¥2730000

研究種別:挑戦的萌芽研究

プライバシー保護バイオインフォマティクス基盤技術の開発と応用

2013年-2015年

研究分野:生命・健康・医療情報学

配分額:¥3770000

研究種別:若手研究(A)

修飾・編集RNAの構造予測手法の研究開発

2012年-2014年

研究分野:生体生命情報学

配分額:¥14300000

学内研究制度

特定課題研究

エピジェネティクスデータからクロマチン状態を推定する方法論の研究と応用

2014年度

研究成果概要:Motivation: Recent studies have suggested that both the genome and the genome with epigenetic modifications, the so...Motivation: Recent studies have suggested that both the genome and the genome with epigenetic modifications, the so-called epigenome, play important roles in various biological functions, such as transcription and DNA replication, repair, and recombination. It is well known that specific combinations of histone modifications (e.g. methylations and acetylations) of nucleosomes induce chromatin states that correspond to specific functions of chromatin. Although the advent of next-generation sequencing (NGS) technologies enables measurement of epigenetic information for entire genomes at high-resolution, the variety of chromatin states has not been completely characterized. Results: In this study, we propose a method to estimate the chromatin states indicated by genome-wide chromatin marks identified by NGS technologies. The proposed method automatically estimates the number of chromatin states and characterize each state on the basis of a hidden Markov model (HMM) in combination with a recently proposed model selection technique, factorized information criteria. The method is expected to provide an unbiased model because it relies on only two adjustable parameters and avoids heuristic procedures as much as possible. Computational experiments with simulated datasets show that our method automatically learns an appropriate model, even in cases where methods that rely on Bayesian information criteria fail to learn the model structures. In addition, we comprehensively compare our method to ChromHMM on three real datasets and show that our method estimates more chromatin states than ChromHMM for those datasets.

lncRNA-RNA相互作用の網羅的予測と実験情報を統合したデータベースの構築

2015年度

研究成果概要:本研究では、第一に、高速にRNA-RNAの相互作用を予測するためのパイプラインシステムを構築した。さらに、パイプラインシステムを京コンピュータに実装した。第2に、このパイプラインを用いてヒトのlncRNAを対象に網羅的な相互作用相...本研究では、第一に、高速にRNA-RNAの相互作用を予測するためのパイプラインシステムを構築した。さらに、パイプラインシステムを京コンピュータに実装した。第2に、このパイプラインを用いてヒトのlncRNAを対象に網羅的な相互作用相手の予測を行い、得られた結果をデータベースとして公開を行った。APBC2016において、浜田が口頭発表を行うと同時に、ジャーナル論文(BMC Genomics)に論文が掲載された。

エピゲノムの統合的理解に向けた情報技術の開発とデータ駆動型生物学の実践

2015年度

研究成果概要:今年度は、昨年度発表した論文[1]のプログラムの、ソースコードの一般公開に向けて、プログラムの整理、および、改良を行った。具体的には、各位置においてクロマチン状態の事後確率が出力可能となるように変更を行った。[1] Michiak...今年度は、昨年度発表した論文[1]のプログラムの、ソースコードの一般公開に向けて、プログラムの整理、および、改良を行った。具体的には、各位置においてクロマチン状態の事後確率が出力可能となるように変更を行った。[1] Michiaki Hamada*, Yukiteru Ono, Ryohei Fujimaki, Kiyoshi Asai, Learning chromatin states with factorized information criteria, Bioinformatics, Bioinformatics (2015) doi: 10.1093/bioinformatics/btv163 First published online: March 24, 2015

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