Literature DB >> 9822851

Using ARROWSMITH: a computer-assisted approach to formulating and assessing scientific hypotheses.

N R Smalheiser1, D R Swanson.   

Abstract

Conventional computer searches of the biomedical literature (e.g. MEDLINE) allow investigators to retrieve much of the information that has already been published on a given topic. However, these searches are of limited utility at the frontier of scientific discovery, when one wishes to identify and assess new, untested scientific hypotheses, or to uncover biologically significant relations between two previously disparate fields of inquiry. We have designed a set of interactive software and database search strategies, collectively called ARROWSMITH, that facilitate the discovery of plausible hypotheses linking findings across specialties (Artif. Intell. 91 (1997) 183-203). In the simplest implementation of ARROWSMITH, the user begins with an experimental finding or hypothesis that two items A and C are related in some way. The titles of papers indexed in MEDLINE which contain the word 'A' (or synonyms) are downloaded into a file A, and similarly a file C is created. The software constructs a list of words and phrases B common to files A and C; automatic and manual editing are used to filter out uninteresting B-terms. For each B-term, the software generates an AB file of titles containing both 'A' and 'B', and a BC file of titles containing both 'B' and 'C'; these titles are juxtaposed to facilitate the user judging whether there is likely to be a biologically significant relation among A, B and C. ARROWSMITH has been employed to analyze research problems relating to oxidative stress, brain damage, Alzheimer's disease and schizophrenia. Applications of ARROWSMITH include: anticipating adverse drug reactions, identifying mechanisms by which agents modulate cellular or organismal responses, suggesting new therapeutic approaches, identifying possible risk factors for diseases, and identifying potential animal models for human conditions. A simplified experimental version of ARROWSMITH is now freely accessible on the World Wide Web (http:@kiwi.uchicago.edu).

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Year:  1998        PMID: 9822851     DOI: 10.1016/s0169-2607(98)00033-9

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  33 in total

1.  Generating hypotheses by discovering implicit associations in the literature: a case report of a search for new potential therapeutic uses for thalidomide.

Authors:  Marc Weeber; Rein Vos; Henny Klein; Lolkje T W De Jong-Van Den Berg; Alan R Aronson; Grietje Molema
Journal:  J Am Med Inform Assoc       Date:  2003-01-28       Impact factor: 4.497

2.  Informatics and hypothesis-driven research.

Authors:  Neil R Smalheiser
Journal:  EMBO Rep       Date:  2002-08       Impact factor: 8.807

3.  Mining connections between chemicals, proteins, and diseases extracted from Medline annotations.

Authors:  Nancy C Baker; Bradley M Hemminger
Journal:  J Biomed Inform       Date:  2010-03-27       Impact factor: 6.317

4.  Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts.

Authors:  A M Cohen; W R Hersh; C Dubay; K Spackman
Journal:  BMC Bioinformatics       Date:  2005-04-22       Impact factor: 3.169

5.  Discovering synergistic qualities of published authors to enhance translational research.

Authors:  Nathan J Bahr; Aaron M Cohen
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

6.  Finding potentially new multimorbidity patterns of psychiatric and somatic diseases: exploring the use of literature-based discovery in primary care research.

Authors:  Rein Vos; Sil Aarts; Erik van Mulligen; Job Metsemakers; Martin P van Boxtel; Frans Verhey; Marjan van den Akker
Journal:  J Am Med Inform Assoc       Date:  2013-06-17       Impact factor: 4.497

7.  Predicting Adverse Drug Effects from Literature- and Database-Mined Assertions.

Authors:  Mary K La; Alexander Sedykh; Denis Fourches; Eugene Muratov; Alexander Tropsha
Journal:  Drug Saf       Date:  2018-11       Impact factor: 5.606

8.  Arrowsmith two-node search interface: a tutorial on finding meaningful links between two disparate sets of articles in MEDLINE.

Authors:  Neil R Smalheiser; Vetle I Torvik; Wei Zhou
Journal:  Comput Methods Programs Biomed       Date:  2009-01-30       Impact factor: 5.428

9.  Identification and analysis of co-occurrence networks with NetCutter.

Authors:  Heiko Müller; Francesco Mancuso
Journal:  PLoS One       Date:  2008-09-10       Impact factor: 3.240

10.  Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases.

Authors:  Douglas B Kell
Journal:  BMC Med Genomics       Date:  2009-01-08       Impact factor: 3.063

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