Abstract
The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses. More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines. The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share. We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches. In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios. For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry-identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation. Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated. One can also employ two-node searches to search for novel hypotheses. Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 190-197 |
| Number of pages | 8 |
| Journal | Computer Methods and Programs in Biomedicine |
| Volume | 94 |
| Issue number | 2 |
| DOIs | |
| State | Published - May 1 2009 |
| Externally published | Yes |
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Keywords
- Hypothesis
- Literature-based discovery
- Text mining
- Web server
ASJC Scopus subject areas
- Computer Science Applications
- Software
- Health Informatics
Cite this
Arrowsmith two-node search interface : A tutorial on finding meaningful links between two disparate sets of articles in MEDLINE. / Smalheiser, Neil R.; Torvik, Vetle Ingvald; Zhou, Wei.
In: Computer Methods and Programs in Biomedicine, Vol. 94, No. 2, 01.05.2009, p. 190-197.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Arrowsmith two-node search interface
T2 - A tutorial on finding meaningful links between two disparate sets of articles in MEDLINE
AU - Smalheiser, Neil R.
AU - Torvik, Vetle Ingvald
AU - Zhou, Wei
PY - 2009/5/1
Y1 - 2009/5/1
N2 - The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses. More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines. The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share. We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches. In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios. For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry-identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation. Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated. One can also employ two-node searches to search for novel hypotheses. Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools.
AB - The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses. More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines. The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share. We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches. In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios. For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry-identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation. Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated. One can also employ two-node searches to search for novel hypotheses. Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools.
KW - Hypothesis
KW - Literature-based discovery
KW - Text mining
KW - Web server
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U2 - 10.1016/j.cmpb.2008.12.006
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VL - 94
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JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
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