Mark Gerstein has helped pen an article appearing in this week's PLoS Computational Biology that follows up on an article in the January 2008 issue, Getting Started in Text Mining. While that was an introduction, this overview looks at the major stages of the current text-processing pipelines out there as well as the downstream questions scientists can ask using text-mining and literature-mining engines, the story says.
Also in PLoS Computational Biology, Lin He at Shanghai Jiao Tong University is lead author on a paper that investigates the nature of serious adverse drug reactions. Considering that unexpected binding between drugs and random proteins might cause these reactions, they created the "first chemical-protein interactome in the form of the interaction strength among FDA-approved drugs and human proteins." Binding 162 drugs known to cause adverse events to 845 proteins, they were able to map these binding patterns for several commonly taken drugs.
In PLoS One, scientists at the University of Toronto employed micro-contact printing, used to restrict colony diameter, separation, and degree of clustering, in mouse embryonic stem cells to see how niche size controls stem cell fate. They found that the Jak-Stat pathway is under spatial control, and that the size of the colony affects targets of Stat3. "These results define parameter boundaries for the use of ESCs in screening studies, demonstrate the importance of context in stem cell responsiveness to exogenous cues, and suggest that niche size is an important parameter in stem cell fate control," they write in the abstract.
Finally, Pat Brown and Chana Palmer of the Canary Foundation developed a method to look at preclinical, serous ovarian tumors before they become deadly. They found that most early-stage ovarian tumors exist for years at a size that is 1,000 times smaller than existing tests can detect. Though they say there is a four-year window for detection, they estimated that the tumors they would need to detect "to achieve even 50 [percent] sensitivity are more than 200 times smaller than the clinically apparent serous cancers typically used to evaluate performance of candidate biomarkers; none of the biomarker assays reported to date comes close to the required level of performance," they write. The study was published this week in PLoS Medicine.