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As I review the material presented in the fourth edition of Bioinformatics I am moved in two ways, related to both the past and the future.

Looking to the past, I am moved by the amazing evolution that has occurred in our field since the first edition of this book appeared in 1998. Twenty-one years is a long, long time in any scientific field, but especially so in the agile field of bioinformatics. To use the well-trodden metaphor of the “biology moonshot,” the launchpad at the beginning of the twenty-first century was the determination of the human genome. Discovery is not the right word for what transpired – we knew it was there and what was needed. Synergy is perhaps a better word; synergy of technological development, experiment, computation, and policy. A truly collaborative effort to continuously share, in a reusable way, the collective efforts of many scientists. Bioinformatics was born from this synergy and has continued to grow and flourish based on these principles.

That growth is reflected in both the scope and depth of what is covered in these pages. These attributes are a reflection of the increased complexity of the biological systems that we study (moving from “simple” model organisms to the human condition) and the scales at which those studies take place. As a community we have professed multiscale modeling without much to show for it, but it would seem to be finally here. We now have the ability to connect the dots from molecular interactions, through the pathways to which those molecules belong to the cells they affect, to the interactions between those cells through to the effects they have on individuals within a population. Tools and methodologies that were novel in earlier editions of this book are now routine or obsolete, and newer, faster, and more accurate procedures are now with us. This will continue, and as such this book provides a valuable snapshot of the scope and depth of the field as it exists today.

Looking to the future, this book provides a foundation for what is to come. For me this is a field more aptly referred to (and perhaps a new subtitle for the next edition) as Biomedical Data Science. Sitting as I do now, as Dean of a School of Data Science which collaborates openly across all disciplines, I see rapid change akin to what happened to birth bioinformatics 20 or more years ago. It will not take 20 years for other disciplines to catch up; I predict it will take 2! The accomplishments outlined in this book can help define what other disciplines will accomplish with their own data in the years to come. Statistical methods, cloud computing, data analytics, notably deep learning, the management of large data, visualization, ethics policy, and the law surrounding data are generic. Bioinformatics has so much to offer, yet it will also be influenced by other fields in a way that has not happened before. Forty-five years in academia tells me that there is nothing to compare across campuses to what is happening today. This is both an opportunity and a threat. The editors and authors of this edition should be complimented for setting the stage for what is to come.

Philip E. Bourne, University of Virginia