Two or three myths about bioinformatics

Editorial TWO OR THREE MYTHS ABOUT BIOINFORMATICS I could have started by describing the recent explosion in the analysis of biological information using computational approaches, how important the field of bioinformatics has become over the past few years and the like, but I will not. The chances are that even if you are reading this journal for the first time, you must have heard something about the field and therefore I consider this introduction unnecessary. What I would like to discuss here is a set of less obvious truths that unfortunately do not appear to be clearly understood by the majority. This new field that is now known as bioinformatics has excited academic boards and private investors alike. Bioinformatics has provided the basis for the future of large-scale biology: it is relatively inexpensive, research and development can be done with modest equipment and plenty of public resources, you can produce and publish results rapidly, it can generate predictions that should be tested in the lab, and last, but not least, this is a novel and exciting technology platform for the future. I will now take the opportunity to discuss the above (misconceptions s and examine how much truth they actually contain. These innocent-looking myths create problems in the field that can have fateful consequences, and they warrant some more attention by the community. MYTH #1 : " Anybody can do this! " COROLLARY 1. Bioinformatics is inexpensive. With so many plentiful resources, any person equipped with an introductory textbook in biology, the web and a PC online, is in principle a bioinformatician in the making. In a more realistic setting, a person with an overview of key resources and in-depth knowledge of ten unix commands in any biological laboratory becomes the de facto bioinformatics support person for the whole group. Even in professional settings, this concept of providing for people equipped with a workstation dominates the funding model. This deceptive readiness of entering the field permeates the whole structure of bioinformatics, including various industrial setups and research funding agencies. Costs associated with professional software development environments, adequately planned and properly structured disk space resources, number and speed of CPUs available to any given person, projected costs of activities over time (usually growing exponentially to follow the data), and in general the proper infrastructure for a professional practice of the field, are not always fully appreciated. As a matter of fact, …