Methods, The MyMiner system works with any input text and thus was not tailored to specific format of the set of articles proposed by the task organizers. It is based on a general 3 column tabulated input format that allows MyMiner to be utilized by users with limited computer skills. The recognition of bio entities is based on the integration of the named entity recognition tool ABNER, that automatically inhibitor order us tags mentions of proteins, genes, cell lines, cell types. LINNAEUS is used to recognize the species. In order to generate from an entity tagged text a ranked collection of database links, MyMiner proposes a list of database identifiers per bio entity mention. We use the UniProt query scoring mechanism for proteins and genes.

In this case, the protein mentions that are either automatically or manu ally tagged are used as direct queries within MyMiner to retrieve a ranked set of hits. Alternatively, organism query filters can be applied. The main features that influence the scoring ranking mechanism are, How often the term occurs in a given UniProt entry, Weighting depending on the field of the record in which the term was detected, Weighting depending on whether the record had been reviewed or not, scoring higher those records that have been reviewed, Weighting depending on how comprehensively annotated a record is, to delib erately bias the system for well annotated entries, which in general are also more likely to be the actual hit given an input article. Ajax requests are executed to query dis tant databases such as NCBI taxonomy, Uniprot and OMIM databases, using web services protocols or similar.

Results of theses queries are treated and dis played on the fly, on the webpage. Interface, The MyMiner application combines several standard web languages and techniques such as PHP, Javascript and Ajax to enhance user interactivity. MyMi ner is composed of four main application interfaces, File labelling, Entity tagging, Entity linking, and Compare file. MyMiner user interfaces offer options and tools to resolve a variety of limitations and bottle necks identified in each Drug_discovery task. To make this system flex ible and interactive, automatically generated tags can be corrected, edited or removed. Entities are highlighted using CSS and Javascript. When a tag is defined, a cor responding CSS style is dynamically created. Upon user actions, such as text selection and tagging, html tags are added using Document Object Model manipulation functions in Javascript. Each module provides an export option to save results. The time spent for processing a document is recorded and available on the export file. To enhance the user friendliness of interfaces, a com mon display layout has been adopted and conserved between applications.