sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background
Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.

Results
This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies.

Conclusion
The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap

Proofreading Using an Assistive Software Homophone Tool Compensatory and Remedial Effects on the Literacy Skills of Students With Reading Difficulties

The present study investigated the effects of using an assistive software homophone tool on the assisted proofreading performance and unassisted basic skills of secondary-level students with reading difficulties. Students aged 13 to 15 years proofread passages for homophonic errors under three conditions: with the homophone tool, with homophones highlighted only, or with no help. The group using the homophone tool significantly outperformed the other two groups on assisted proofreading and outperformed the others on unassisted spelling, although not significantly. Remedial (unassisted) improvements in automaticity of word recognition, homophone proofreading, and basic reading were found over all groups. Results elucidate the differential contributions of each function of the homophone tool and suggest that with the proper training, assistive software can help not only students with diagnosed disabilities but also those with generally weak reading skills.