overview results also contained chemicals which live either in symbiosis or as parasites. An additional fulltext search obtained 224 matches with links to possible parasites and bacteria related to rice. Only by evaluating each single source it is possible to filter those out. An example would be the Bisbynin [25] which is a metabolite of the fungus Stachybotrys bisbyi from seeds of Oryza sativa (see Figure 1). Chemical Abstracts Database and SciFinder The Chemical Abstracts Database is the largest curated database of chemical and biomedical literature [7]. As of October 2008 it contains 39 million organic and inorganic substances, 60 million protein sequences and additionally paper abstracts. The major difference to open abstracts databases like PubMed is that not only abstracts are covered but all chemical and biochemical literature is read in full text by computer algorithms to detect chemicals structures in text and pictures. Trained chemists further curate those structures. The CAS database has no direct taxonomic annotation but has a specialized index database which also includes taxonomy names. More than unique 42,115 literature abstracts were obtained by searching for oryza sativa, but only 5,000 records at one time can be used and stored for obtaining chemical structures by the license agreement. Addition- ally, these results must be deleted after the research project is finished. These constraints limit the use of SciFinder for metabolic profiling approaches despite the good data quality. Moreover, chemical structures can only be manually downloaded one-by-one. No list matching (batch approach) for structure search is possible. The number of structures obtained from CAS queries is depending on the exact search terms and refinements. For example, constraining the search using ‘‘golden rice’’ as search term resulted in only twenty-seven chemicals, among them beta- carotene, trans-luteine, cholesterol and other terpenoids. Impor- tantly, metabolite structures are mixed up with pesticides like Malathion and Chlorpyrifos. Refinement of such lists is very difficult as cross-referencing CAS hits and links to compound identifiers in other databases (such as KEGG, PubChem) are not given. It also must be mentioned that although the CAS DB has the largest coverage of substances from the chemical and bio- chemical literature it is by no means complete [26]. In many instances the original publication contained multiple structures which could not be found in the database. The SciFinder 2007 version has a much finer grained and useful categorization tool however that does not solve the problem of results mixed with drugs, protein sequences and pesticides. Furthermore CAS numbers may change without notice. For example, the rice metabolite Ribosylnicotinamide had been assigned with more than one CAS number, i.e. 19131-72-7, 20299-13-2, 954368-04-8 and 1341-23-7. Many outdated CAS numbers can be still found through internet or DB queries even they are no longer supported by CAS itself. PubChem PubChem is the largest open access database for small molecules. It is part of a set of life sciences databases hosted at the US National Center for Biotechnology Information [27]. As of October 2008 PubChem contained 47 million substance records and 19 million unique compound records. It is regarded as a premier database for small molecule research. Structures can be freely downloaded and links to relevant databases are provided. One major drawback is that PubChem and PubMed lack chemical information from full text chemical publications as provided in the Chemical Abstracts Database. A general overview about pointers to gene sequence, protein and small molecule resources can be Data Exchange in Chemistry obtained at NCBI Entrez which also links to PubChem and many other NCBI databases. Entrez lists 1,232,016 expressed sequence tag records (EST), 355,026 Genome Survey Sequence records (GSS) and 231,927 records in protein sequence databases for rice but no chemical substances in the PubChem record. Furthermore taxonomy-related queries cannot directly be submitted to PubChem. Instead, PubMed and PubMed Central need to be searched for taxonomy data, and subsequently, related substance records need to be displayed. Unfortunately, the results present all substances retrieved from the research papers but do not detail whether or not the compounds occur as genuine metabolites of the queried organism. For example the hit ‘Omeprazol’ is clearly not a rice metabolite as it refers a synthetic drug for acid reflux treatment. Furthermore the 11,490 articles in PubMed and the 4,472 open access article in PubMed Central reflect only one third of the chemical literature covering rice research as retrieved from CAS searches. Beilstein database The Beilstein database covers 10 million compounds and organic reactions and contains 500 million experimental chemical property values (factual information). Export of chemical struc- tures as chemical structure file (SDF) file is possible. Only one hundred records can be exported at a time. 554 substance records were retrieved from querying the Beilstein DB with ‘oryza sativa’ but results were mixed with hits on pesticides and growth inhibitors. Dr. Duke’s Dr. Duke’s Phytochemical and Ethnobotanical Database contains 201 organic and inorganic chemicals found specifically only in rice. Structures are presented as names only. Taxonomy searches are possible for a variety of plants. Concentrations for chemicals in different compartments (fruit, hay, juice, leaf, petiole, plant, protoplast, root, seed, shoot, sprout seedling, stem, tissue culture, wax) are given. Concentrations are recorded in parts per million (ppm). No external links or cross-references to other databases and other compound identifiers exist and the database is not updated anymore. SetupX SetupX/BinBase comprises 268 unique metabolites for oryza sativa. The data was obtained from the non-public part of the database from GC-MS metabolic profiling experiments. The datasets contain 108 primary metabolites with relative concentra- tions which were identified by authentic chemical standards. Additionally around 160 unique unknown metabolites could be assigned with help of the BinBase algorithm via mass spectral and retention index matching. Raw and processed experimental datasets can be downloaded concomitant with a complete experimental description and report. Exploring phylogenetic relationships in SetupX/BinBase is facilitated as the taxonomic structure is based on NCBI taxonomy database [29] while allowing manual curation of entries. Hence, SetupX/BinBase database requests enable querying which unique substances were experimentally determined in two different subspecies and which metabolites were fully unique in a specific taxonomy kingdom. Apart from NCBI, SetupX uses further plant [30] and animal ontologies [31]. All hits with identified structures are referenced to PubChem and KEGG. However, few secondary metabolites are included, and the abundance of metabolites without elucidated chemical structures limits use of SetupX/BinBase for further biochemical or physiological interpretations. PLoS ONE | www.plosone.org 4 May 2009 | Volume 4 | Issue 5 | e5440