Our approach has some pitfalls. Although we use the DAG as causal model, it is well-known that there are many feedback and undirected relations in actual biological systems. The limitaiton of our method due to structual restriction may overlook important discoveries. Thus, what remain to be done is development of an improved method appicable for various types of network structures.
According to progress of measurement technologies, ChIP data for a lot of transcription factors are measuring simultaneously. In the ENCODE (the Encyclopedia Of DNA Elements) project, one of large international consortium with a goal of cataloguing all the functional elements in the human genome; ChIP analysis to define binding sites for a lot of transcription factors has been examined [141]. Currently, several resources for the ChIP data are available as open sources. In the hmChIP database, there are 2016 samples from 492 ChIP experiments, representing a total of 170 proteins and 11,069,914 protein-DNA interactions [142]. The ChEA database contains 189,933 interactions, manually extracted from 87 publications, describing the binding of 92 transcription factors to 31,932 target genes [143]. These numbers are anticipated to rise more and more. Thus, it is expected that the network screening enable us to identify master transcriptional regulatory networks controlling the biological phenomena using vast amount of resources for the ChIP data and global gene expression profiles.
102 5 Acknowledgements
I am very grateful to Prof. Masahiro Okamoto at the Laboratory for Biological Information Systems, Department of Bioscience and Biotechnology, Faculty of Agriculture, Kyushu University, not only for taking over the duty of supervising my thesis work, but also for providing me with valuable comments and suggestions. I am indebted to Prof. Satoru Kuhara at the Laboratory for Gene Control, Department of Bioscience and Biotechnology, Faculty of Agriculture, Kyushu University, to be the co-reviewer of my thesis. Moreover, I am deeply indebted to Dr. Katsuhisa Horimoto at the Biological Network Team, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, for the supervising my thesis work and the enlightening discussions have had a major impact on this thesis.
For T2DM analysis, I would like to thank Prof. Huarong Zhou, Dr. Guanying Piao, Dr. Zhi-Ping Liu, Dr. Jiguang Wang and Prof. Luonan Chen at the Chinese Academy of Science, for providing challenging theme.
For research for induced pluripotent stem cell, I would like to thank Dr. Yasuko Onuma, Dr. Yuzuru Ito and Prof. Makoto Asashima at the Research Center for Stem Cell Engineering, National Institute of Advanced Industrial Science and Technology, Dr.
Hiroaki Tateno, Dr. Yohichi Shimma and Dr. Jun Hirabayashi at the Research Center for Medical Glycoscience, National Institute of Advanced Industrial Science and Technology, Dr. Masashi Toyoda, Dr. Hidenori Akutsu, Dr. Koichiro Nishino, Dr. Emi Chikazawa, Dr. Yoshihiro Fukawatase and Dr. Akihiro Umezawa at the Department of Reproductive Biology, National Research Institute for Child Health and Development, Dr. Yoshitaka Miyagawa, Dr. Hajime Okita and Dr. Nobutaka Kiyokawa at the Department of Developmental Biology and Pathology, National Research Institute for Child Health and Development, for giving valuable data for molecular profiles of stem cells.
For glioblastoma analysis, I would like to thank Dr. Xinrong Zhou at the Tonji Hospital, Dr. Taejeong Bae and Prof. Sunghoon Kim at the Soul National University, for providing exciting experience of collaboration. And I would like to thank Dr. Takatsugu Hirokawa at the Molecular Modeling & Drug Design Team, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology.
Moreover, I would like to thank Dr. Yong Wang at the Institute of Applied Mathematics, Academy of Mathematics & Systems Science, Chinese Academy of Science, for the instructive discussions.
Finally, I would like to thank my wife, my son and my parents, having supported and encouraged me.
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