The conclusions we draw

Empirical Algorithmics: draw your own conclusions

In an empirical comparisons of algorithms we might compare run times over a set of benchmark problems to decide which one is fastest, i.e. an algorithmic horse race. Ideally we would like to download source code for the algorithms, compile and then run on our machine. Sometimes code isn't available to download and sometimes resource isn't available to implement all the algorithms we want to stu...

Bacterial virulence: can we draw the line?

The molecular approach to microbial pathogenesis has resulted in an impressive amount of data on bacterial virulence genes. Bacterial genome sequences rapidly add candidate virulence genes to electronic databases. The interpretation of this overwhelming information is obscured because every gene involved in pathogenicity is called a virulence gene, regardless of its function in the complex proc...

The role of heterosexual anal intercourse for HIV transmission in developing countries: are we ready to draw conclusions?

Treating prostate cancer: where do we draw the line?

The article by Drs. Lepor and Donin is a provocative look at a timely topic in urologic oncology.[1] There is little debate among experts in the field that we are overtreating prostate cancer at the current time. Studies are ongoing to evaluate active surveillance as an option for low-risk tumors, even in men with very long life expectancies. However, in this review, the authors have overreache...

Hierarchical statistical techniques are necessary to draw reliable conclusions from analysis of isolated cardiomyocyte studies

Aims It is generally accepted that post-MI heart failure (HF) changes a variety of aspects of sarcoplasmic reticular Ca2+ fluxes but for some aspects there is disagreement over whether there is an increase or decrease. The commonest statistical approach is to treat data collected from each cell as independent, even though they are really clustered with multiple likely similar cells from each he...