Permeable observations of multifactor database for transcription network

Miho Sera; Hisayoshi Zaima; Kazuho Ikeo; Takashi Gojobori

doi:10.1109/ICSENG.2005.67

Permeable observations of multifactor database for transcription network

Miho Sera^*, Hisayoshi Zaima, Kazuho Ikeo, Takashi Gojobori

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Systems biology is a research field where experimental and computational approaches are used in combination. Core experimental data tends to be multi-dimensional and large-scale. Consequently, the requirements for data processing are sensitive and intricate. Multiple data whose nature is not the same are difficult to deal with computationally, and dealing with a large amount of data that may not be of high quality is also difficult. We dealt with such complex data using a data analysis pipeline and show that transcription networks are a promising theme of systems biology.

Original language	English (US)
Title of host publication	18th International Conference on Systems Engineering, ICSEng 2005
Pages	313-319
Number of pages	7
Volume	2005
DOIs	https://doi.org/10.1109/ICSENG.2005.67
State	Published - 2005
Externally published	Yes
Event	18th International Conference on Systems Engineering, ICSEng 2005 - Las Vegas, NV, United States Duration: Aug 16 2005 → Aug 18 2005

Other

Other	18th International Conference on Systems Engineering, ICSEng 2005
Country	United States
City	Las Vegas, NV
Period	08/16/05 → 08/18/05

ASJC Scopus subject areas

Engineering(all)

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10.1109/ICSENG.2005.67

Cite this

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title = "Permeable observations of multifactor database for transcription network",

abstract = "Systems biology is a research field where experimental and computational approaches are used in combination. Core experimental data tends to be multi-dimensional and large-scale. Consequently, the requirements for data processing are sensitive and intricate. Multiple data whose nature is not the same are difficult to deal with computationally, and dealing with a large amount of data that may not be of high quality is also difficult. We dealt with such complex data using a data analysis pipeline and show that transcription networks are a promising theme of systems biology.",

author = "Miho Sera and Hisayoshi Zaima and Kazuho Ikeo and Takashi Gojobori",

year = "2005",

doi = "10.1109/ICSENG.2005.67",

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AU - Sera, Miho

AU - Zaima, Hisayoshi

AU - Ikeo, Kazuho

AU - Gojobori, Takashi

PY - 2005

Y1 - 2005

N2 - Systems biology is a research field where experimental and computational approaches are used in combination. Core experimental data tends to be multi-dimensional and large-scale. Consequently, the requirements for data processing are sensitive and intricate. Multiple data whose nature is not the same are difficult to deal with computationally, and dealing with a large amount of data that may not be of high quality is also difficult. We dealt with such complex data using a data analysis pipeline and show that transcription networks are a promising theme of systems biology.

AB - Systems biology is a research field where experimental and computational approaches are used in combination. Core experimental data tends to be multi-dimensional and large-scale. Consequently, the requirements for data processing are sensitive and intricate. Multiple data whose nature is not the same are difficult to deal with computationally, and dealing with a large amount of data that may not be of high quality is also difficult. We dealt with such complex data using a data analysis pipeline and show that transcription networks are a promising theme of systems biology.

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U2 - 10.1109/ICSENG.2005.67

DO - 10.1109/ICSENG.2005.67

M3 - Conference contribution

AN - SCOPUS:33845946234

SN - 0769523595

SN - 9780769523590

VL - 2005

SP - 313

EP - 319

BT - 18th International Conference on Systems Engineering, ICSEng 2005

T2 - 18th International Conference on Systems Engineering, ICSEng 2005

Y2 - 16 August 2005 through 18 August 2005

ER -

Permeable observations of multifactor database for transcription network

Abstract

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