OReFiL: an online resource finder for life sciences.
BACKGROUND
Many online resources for the life sciences have been developed and introduced in peer-reviewed papers recently, ranging from databases and web applications to data-analysis software. Some have been introduced in special journal issues or websites with a search function, but others remain scattered throughout the Internet and in the published literature. The searchable resources on these sites are collected and maintained manually and are therefore of higher quality than automatically updated sites, but also require more time and effort.


METHODS
We developed an online resource search system called OReFiL to address these issues. We developed a crawler to gather all of the web pages whose URLs appear in MEDLINE abstracts and full-text papers on the BioMed Central open-access journals. The URLs were extracted using regular expressions and rules based on our heuristic knowledge. We then indexed the online resources to facilitate their retrieval and comparison by researchers. Because every online resource has at least one PubMed ID, we can easily acquire its summary with Medical Subject Headings (MeSH) terms and confirm its credibility through reference to the corresponding PubMed entry. In addition, because OReFiL automatically extracts URLs and updates the index, minimal time and effort is needed to maintain the system.


CONCLUSIONS
We developed OReFiL, a search system for online life science resources, which is freely available. The system's distinctive features include the ability to return up-to-date query-relevant online resources introduced in peer-reviewed papers; the ability to search using free words, MeSH terms, or author names; easy verification of each hit following links to the corresponding PubMed entry or to papers citing the URL through the search systems of BioMed Central, Scirus, HighWire Press, or Google Scholar; and quick confirmation of the existence of an online resource web page.
Yamamoto
Yasunori
Y
Department of Computational Biology, University of Tokyo, Kashiwanoha, Kashiwa, Chiba, Japan. yayamamo@cb.k.u-tokyo.ac.jp
Takagi
Toshihisa
T
D000043:Abstracting and Indexing / Q000379:methods / Q000639:trends; D001690:Biological Science Disciplines / Q000639:trends; D016247:Information Storage and Retrieval / Q000379:methods* / Q000639:trends; D020407:Internet / Q000639:trends; D046650:Medical Subject Headings; D009862:Online Systems / Q000639:trends; D010506:Periodicals as Topic / Q000639:trends