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. 2008 Feb 13;3(2):e1570. doi: 10.1371/journal.pone.0001570

Figure 2. An automatic pipeline for malaria literature mining.

Figure 2

Approach A, full text search by literature search engines: A1) All P. falciparum and P. yoelii locus names were downloaded from PlasmoDB and searched against Google Scholar and SCIRUS one at a time; A2) URL hits were then mapped to PubMed entries. Approach B, NCBI database mining: B1) Mapping between GenBank sequence entries and PubMed entries were systematically retrieved from NCBI for four Plasmodium species; B2) Sequences were mapped to malaria locus names by BLAST alignment. The pipeline resulted in 6,428 functional associations between 3,262 malaria proteins and 1,278 PubMed papers.