Text mining from categorized stem cell documents to infer developmental stage-specific expression and regulation patterns of stem cells

Hyun Seok Park; Min Kyung Kim; Eun Jeong Choi; Young Joo Seol

doi:10.1007/11428817_35

Text mining from categorized stem cell documents to infer developmental stage-specific expression and regulation patterns of stem cells

Hyun Seok Park, Min Kyung Kim, Eun Jeong Choi, Young Joo Seol

Department of Computer Science & Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

Exponentially increasing stem cell data provide means to elucidate the system level understanding of differentiation. Given the existing information on biological networks combined with huge amount of literature data, inferring stem cell information through scientific reasoning of data from on-line documents would get great attention. In this paper, we describe the STEMWAY system for combining known interaction informatics with text mining techniques. Especially, recent advances in natural language processing technique raise new challenges and opportunities for extracting valuable information from literature classified by the developmental stages of stem cells.

Original language	English
Pages (from-to)	353-356
Number of pages	4
Journal	Lecture Notes in Computer Science
Volume	3513
DOIs	https://doi.org/10.1007/11428817_35
State	Published - 2005
Event	10th International Conference on Applications of Natural Language to Information Systems, NLDB 2005: Natural Language Processing and Information Systems - Alicante, Spain Duration: 15 Jun 2005 → 17 Jun 2005

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abstract = "Exponentially increasing stem cell data provide means to elucidate the system level understanding of differentiation. Given the existing information on biological networks combined with huge amount of literature data, inferring stem cell information through scientific reasoning of data from on-line documents would get great attention. In this paper, we describe the STEMWAY system for combining known interaction informatics with text mining techniques. Especially, recent advances in natural language processing technique raise new challenges and opportunities for extracting valuable information from literature classified by the developmental stages of stem cells.",

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AU - Kim, Min Kyung

AU - Choi, Eun Jeong

AU - Seol, Young Joo

PY - 2005

Y1 - 2005

N2 - Exponentially increasing stem cell data provide means to elucidate the system level understanding of differentiation. Given the existing information on biological networks combined with huge amount of literature data, inferring stem cell information through scientific reasoning of data from on-line documents would get great attention. In this paper, we describe the STEMWAY system for combining known interaction informatics with text mining techniques. Especially, recent advances in natural language processing technique raise new challenges and opportunities for extracting valuable information from literature classified by the developmental stages of stem cells.

AB - Exponentially increasing stem cell data provide means to elucidate the system level understanding of differentiation. Given the existing information on biological networks combined with huge amount of literature data, inferring stem cell information through scientific reasoning of data from on-line documents would get great attention. In this paper, we describe the STEMWAY system for combining known interaction informatics with text mining techniques. Especially, recent advances in natural language processing technique raise new challenges and opportunities for extracting valuable information from literature classified by the developmental stages of stem cells.

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Y2 - 15 June 2005 through 17 June 2005

ER -

Text mining from categorized stem cell documents to infer developmental stage-specific expression and regulation patterns of stem cells

Abstract

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