data interpretation

Automated analysis minimizes error risk, analysis time, and technician variation.

Pioneering nurse Florence Nightingale had an eye for creating memorable graphics that helped convince the general population that including sanitation reforms as part of public health policy would save British soldiers’ lives.

A technique for quantifying tumor mRNA production from messy tissue sample data uncovers an unexpected correlation between it and disease stage in 15 cancer types.

The journal Ethology is the first to adopt the guidelines, aimed at clarifying experimental design and the potential biases within.

Identical datasets yield opposite conclusions on the use of mice as models of human inflammation.

With scientific budgets eroding, the biomedical community needs to get more return from the data it has already generated.

Researchers must be wary of the common mistakes of correlation analysis when drawing conclusions about the nature of their data.