Bias is ubiquitous in research. The advent of the molecular era provides a unique opportunity to study the consequences of bias with large-scale empirical evidence accumulated in the massive data produced by the current discovery-oriented scientific effort, rather than just with theoretical speculations and constructs. Here I discuss some empirical evidence about manifestations of bias in molecular epidemiology. Bias may manifest as either heterogeneity or as deviation from the true estimates. The failure to translate molecular knowledge and the failure to replicate information are some typical hallmarks of bias at action. The acquired knowledge about the behaviour and manifestations of bias in molecular fields can be transferred back also to more traditional fields of epidemiology and medical research. Getting rid of false claims of the past is at least as important as producing new scientific discoveries. In many fields, the observed effects sizes that circulate as established knowledge are practically estimating only the net bias that has operated in the field all along. Issues of plausibility (in particular biological plausibility), replication, and credibility that form the theoretical basis of epidemiology and etiological inference can now be approached with large-scale empirical data.