by George M Church, Senior Editor
Image manipulation and selective reporting of images have been recently in the focus of a healthy debate on the issue of scientific data manipulation. Of course, as editors tell us how they detect fakes (“What’s in a picture? The temptation of image manipulation”, Rossner and Yamada, JCB 2004 166:11), there is a danger that authors will be tempted to upgrade their ploys. More importantly, I think that these issues are symptomatic of a much larger problem in Cell & Molecular Biology which is the lack of protocols for getting from raw data to conclusions. Contrast this with genomics and 3D-structural biology where raw data are available in databases, not just a few typical photos, but every scrap of data (e.g. sequence trace data, diffraction intensities, raw RNA array data). The algorithms for getting to the conclusions are public and other labs are encouraged to redo the trajectories from data to conclusions using the original or new algorithms. This is mostly missing from Cell & Molecular Biology papers, with some excuse like “too expensive”. Maybe it’s too expensive NOT to do it – not just because of data faking, but because it sends the message that we’re too lazy (or too busy) to describe in detail how we do our science and how to systematically improve it.
Molecular Systems Biology would like to encourage anyone who has creative and concrete ideas how to get Molecular and Cell Biology up to the standards of genomics and structural biology.