教員紹介 複雑系知能学科

ホセ・ナチェル   （准教授）

Jose Nacher

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■所属学科：

複雑系知能学科

■専門分野：

バイオインフォマティクス、システム生物学、複雑ネットワークの科学、スケールフリーネットワーク、確率過程理論

■担当科目：

生体情報処理、データベース工学、複雑系科学実験、数学総合演習

プロフィール

2001年夏にバレンシア大学にて理論物理学博士号を取得。2003年6月より2007年3月まで、京都大学化学研究所バイオインフォマティクスセンター生物情報ネットワーク領域に所属。バ イオインフォマティクス、システム生物学の研究に従事。特に生物学的ネットワークの解析と数理モデル化に興味を持って研究。

・最終学歴：バレンシア大学
・学位　　：博士(理論物理学)
・前歴　　：日本学術振興会　外国人特別研究員　(京都大学)
・着任時期：2007年4月1日

  ホームページ (Home page):  http://www.fun.ac.jp/~nacher

略歴 

2009年4月      　公立はこだて未来大学システム情報科学部准教授
2007年4月      　公立はこだて未来大学システム情報科学部講師
2005年11月      京都大学化学研究所バイオインフォマティクスセンター日本学術振興会外国人特別研究員
2003年6月      　京都大学化学研究所バイオインフォマティクスセンター博士研究員
2001年7月      　GMV/ISDEFE シニアプログラマー
2001年7月      　バレンシア大学大学院理学系研究科理論物理学専攻博士課程修了(理学博士)
2000年7-8月     Thomas Jefferson Lab. National Accelerator Facility, Newport News, Virginia, U.S.A. 博士留学研究生
1998年9月-1999年3月  　大阪大学核物理研究センター 博士留学研究生
1998年9月      　バレンシア大学大学院理学系研究科理論物理学専攻修士課程修了
1996年7月　      バレンシア大学理学部理論物理学科卒業

兼職

2011年4月                京都大学化学研究所客員准教授
2011年4月                京都大学大学院薬学研究科非常勤講師
2010年4月-2011年3月 京都大学大学院薬学研究科非常勤講師
2009年4月-2010年3月 京都大学大学院薬学研究科非常勤講師
 

賞罰
 

2011年02月     BICB 2011 Annual International Conference on Computational Biology, Singapore, Best Paper Award.
2004年12月　   Oxford University Press Bioinformatics 賞　
               　　　　　日本バイオインフォマティクス学会 ゲノムインフォマティクスコンファレンス(2004年)
 

科学研究費補助金
2011-2013年 　科研費 文部科学省若手研究(B) 代表者
2009-2014年 　科研費 文部科学省基盤(C) 分担者
2009-2011年 　科研費 文部科学省若手研究(B) 代表者
2005-2007年　　日本学術振興会研究費 (JSPS)
1998-2001年　　国費研究奨学金スペイン科学文部省　

英文誌編集委員
2009年～現在     International Editorial Review Board
         　　　　　　　　 International Journal of Knowledge Discovery in Bioinformatics (IJKDB)
         　　　　　　　　DOI: 10.4018/IJKDB ISSN: 1947-9115

仕事の紹介

During the second half of the 20th century, biology has provided a wealth of knowledge about individual chemical components of life and genomic and proteomic data that have enormously increased our understanding of biological systems at the molecular level. However, after completion of genome sequencing for many species and with the advent of genome-scale high-throughput technologies, the 21st century biology is shifting the focus to a systems understanding of cell physiology. This huge conceptual change represents a paradigm shift in biology, from basic molecules of life to systems biology approach.

Systems Biology modeling aims to understand how individual components interact and function to form a complex organism, and spans the biological space from genes, chemicals and proteins to networks and pathways, from cells to organs, and even from organisms to populations and ecosystems. In this context, my bioinformatics research interests deal with a variety of issues, including the structure and dynamics of complex biological networks, evolutionary studies, modeling of gene regulatory modules and analysis of gene expression profiles of normal and diseased tissues. Examples of research lines:

(1) Structure and Dynamics of Complex Cellular Networks: Cellular networks are highly complex systems, formed by several tens thousands of extremely inter-connected molecules of life, such as DNA, mRNA, proteins and chemical compounds. Rapid advances in theoretical modeling and experimental analyses have shown that drastically different biological and non-biological networks exhibit a scale-free architecture. This finding has definitely opened an intense research and debate on the origin and implications of this ubiquitous pattern and suggests the existence of generic laws and organizing principles behind the cellular networks.

(2) Dynamical Modeling and Stochastic Processes: The cell is a highly dynamic and regulated system, and topological analysis alone is not sufficient. For example, cells continually need to adapt the activity levels to changes in their living environment. Furthermore, there are intrinsic fluctuations due to the stochastic nature of biochemical reactions and gene expression regulatory mechanisms. Hence, mathematical models must include in the network’s construction, dynamical ingredients to simulate the real system.

(3) Integrative Data Analysis: Integrative studies can be carried out not only considering different types of nodes (e.g. metabolites, enzymes, proteins or genes) but also using comprehensive data sets at different temporal states and with a rich variety of environmental conditions, drug responses and disease states. This integration is aimed at identifying potential drug targets for therapeutic intervention.

最近の著作

（2004年以降） 

J.C. Nacher and T. Akutsu
On the degree distribution of projected networks mapped from bipartite networks
Physica A, in press, (2011)

J.C. Nacher and T. Ochiai
Plus-Minus construction leads to perfect invisibility
Journal of Mathematical Physics., 52, 012903 (17 pp.), (2011)

J.C. Nacher, M. Hayashida, T. Akutsu
The role of internal duplication in the evolution of multi-domain proteins
BioSystems Elsevier,  101, 127-135, (2010)   - Includes Supplementary Material (34 pp.)-

J.C. Nacher and T. Ochai
Emergent principles in gene expression dynamics,
The Open Bioinformatics Journal, 5, 34-41, (2011)

J.C. Nacher and N. Araki
Structural characterization and modeling of ncRNA-proten interactions,
BioSystems Elsevier, 101, 10-19, (2010).

J.C. Nacher, T. Ochiai, M. Hayashida and T. Akutsu
A mathematical model for generating bipartite graphs and its application to protein networks,
Journal of Physics A: Mathematical and Theoretical, 42, 485005 (10pp), (2009).

J.-M. Schwartz and J. C. Nacher
Local and global modes of drug action in biochemical networks
BMC Chemical Biology 9, 1-15 (2009).

T. Ochiai and J.C. Nacher
On the construction of Complex Networks with optimal Tsallis information Entropy
Physica A, 388, 4887-4892, (2009)

K. Mouri , J.C. Nacher and T. Akutsu
A Mathematical model for the detection mechanism of DNA double-strand breaks depending on autophosphorylation.
PLoS ONE 4, 5131-5145, (2009)

J.C. Nacher, T. Ochiai, M. Hayashida and T. Akutsu
A bipartite graph based model for protein domain networks.
Springer Lecture Notes of the Institute for Computer Sciences,
Social Informatics and Telecommunications Engineering (Complex '09), 
4, 525-535, (2009) 

J.C. Nacher, M. Hayashida and T. Akutsu 
Emergence of scale-free distribution in protein-protein interaction networks based on random selection of interacting domain pairs
BioSystems, 95, 155-159,  (2009)

J.C. Nacher and T. Ochiai.
Power-law of gene expression fluctuations
Physics Letters A, 372, 6202-6206, (2008)

J.C. Nacher and J-M. Schwartz
A global view of drug-therapy interactions
BMC Pharmacology, 8:5, 1-14, (2008)

J.C. Nacher and T. Ochiai
Transcription and regulation in negative feed-back loops,
BioSystems, 91, 1, 76-82 (2008)

T. Ochiai, U. Leonhardt, J.C. Nacher 
A novel design of dielectric perfect invisibility devices
J. Math. Phys. 49, 032903, (2008)

T. Takemoto, J.C. Nacher and T, Akutsu
Correlation between structure and temperature in prokaryotic metabolic networks
BMC Bioinformatics, 8 (1): 303, 1-17, (2007)

T. Ochiai and J.C. Nacher
Stochastic analysis of auto-regulatory gene expression dynamics,
Mathematical and Computer Modelling of Dynamical Systems, Vol. 14, 377–388, (2008),

J.C. Nacher and T. Akutsu
Recent progress on the analysis of power-law features in complex cellular networks,
Cell Biochemistry and Biophysics, 49, 37-47, (2007).

T. Akutsu and J.C. Nacher
生体内ネットワーク構造の数理モデルと情報解析,
Biophysics 47(2), 086-092, (2007).

M. Itoh, J.C. Nacher, K. Kuma, S. Goto and M. Kanehisa
Evolutionary history and functional implications of protein domains and their combinations in eukaryotes,
Genome Biology, 8 (6): R121, 1-16 (2007)

J-M. Schwartz, C. Gaugain, J.C. Nacher, A. de Daruvar, M. Kanehisa
Observing metabolic functions at the genome scale,
Genome Biology, 8 (6): R123, 1-15 (2007)

T. Ochiai, J.C. Nacher and T. Akutsu
Emergence of the self-similarity principle in gene expression dynamics,
Physica A, 382, 739-752 (2007)

J.C. Nacher, J-M. Schwartz, M. Kanehisa and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
Identification of metabolic units induced by environmental signals,
Bioinformatics (ISMB) 22(14), e375-83, 2006

J.C. Nacher and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
Sensitivity of the power-law exponent in gene expression distribution to mRNA decay rate,
Physics Letters A, 360 , 174-178, 2006

J.C. Nacher, T. Ochiai, T. Yamada, M. Kanehisa and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
The role of log-normal dynamics in the evolution of metabolic pathways,
BioSystems 83, 26-37, 2006

J.C. Nacher, M. Hayashida and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
Protein domain networks: scale-free mixing of positive and negative exponents,
Physica A 367, 538-552, 2006

T. Akutsu, T. Ochiai and J.C. Nacher (Kyoto U, Bioinformatics Ctr.).
生物情報ネットワークの構造およびダイナミクス解析、
Protein, Nucleic Acid and Enzyme  50, 16: 2288-2293, 2005

J.C. Nacher, T. Ochiai, and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
On the relation between fluctuation and scaling-law in gene expression time series from yeast to human.
Modern Physics Letters B 19, 1169-1177, 2005

T.Ochiai, J.C. Nacher and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
A stochastic approach to multi-gene expression dynamics,
Physics Letters A 339, 1-9, 2005

J.C. Nacher, N. Ueda, M. Kanehisa and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
Flexible construction of hierarchical scale-free networks with general exponent,
Physical Review E 71:036132 (1-7), 2005

T.Ochiai, J.C. Nacher　and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
A constructive approach to gene expression dynamics
Physics Letters A 330, 313-321, 2004

J.C. Nacher, N. Ueda, T. Yamada, M. Kanehisa and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
Clustering under the line graph transformation:　Application to enzymes network.
BMC Bioinformatics, 5, 207:1-17, 2004

J.C. Nacher, T. Yamada, S. Goto, M. Kanehisa and T. Akutsu (Kyoto U, Bioinformatics Ctr.).
Two complementary representations of a scale-free network,
Physica A 349, 349-363, 2005

More details at http://www.fun.ac.jp/~nacher