Every fresh scientific discipline or methodology reaches a point in its maturation where it is fruitful for it to turn its gaze inward, and also backward. segment of science, for the benefit of current and long term workers. Upcoming content articles, already commissioned, will cover the roots of bioinformatics in structural biology, in evolutionary biology, and in artificial intelligence, with more in the works. These topics are obviously very broad, and so are likely to be subdivided or otherwise revisited in upcoming installments by authors with varying perspectives. Topics and authors will end up being selected at the discretion of the editors along lines broadly corresponding to the most common content of the journal. The writer, having been asked to provide as Series Editor by the Editor-in-Chief, will try to maintain a uniform stream of content solicited from luminaries in the field. As a starting place to the series, I give below several vignettes and reflections on some longer-term influences which have designed the self-discipline. I first consider the initial position of bioinformatics vis–vis technology and technology, and explore historical tendencies in biology and related areas that anticipated and ready just how for bioinformatics. Examining the context of essential moments when computer systems were first adopted by early adopters reveals how deep the roots of bioinformatics move. THE TYPE of Bioinformatics Many who pull a distinction between bioinformatics and computational biology portray the previous as an instrument package and the latter as technology. All allows that the technology informs the various tools and the various tools enable the technology; regardless, bioinformatics and computational biology are near more than enough cousins that their origins and early influences are likely to be commingled as well. Therefore, this article and series will construe bioinformatics RAD001 inhibition broadly, bearing in mind it can thus be expected to possess a dual nature. This duality echoes another that goes back to Aristotle, between episteme (knowledge, especially scientific) and techne (know-how, in the sense of craft or technology). The power of bioinformatics might be seen as arising from their harmonious combination, in the Greek tradition, lending it emergent capabilities beyond the simple intersection of computers and biology, or indeed of science and engineering. A Bioinformatics Revolution? Many commentators refer to the bioinformatics revolution. If there has been one, was it a revolution in techne, like the Industrial RAD001 inhibition Revolution, or in episteme, like the Scientific Revolution? Or was it both? The former suggests quantum leaps in scale and ability through automation, which seems to apply to bioinformatics almost by definition, while the latter implies an actual shift in worldview, raising a more philosophical query. In Thomas Kuhn’s popular conception of scientific revolutions, the early phases of paradigm formation are freewheeling and unstructured, while becoming effectively cut off from the pre-existing scientific milieu by their very novelty and an inherent incommensurability [1]. (The overused term paradigm can be excused in this context RAD001 inhibition because it was Kuhn who instigated its overuse.) At some point, such RAD001 inhibition pre-science becomes consolidated, establishes norms and templates, and settles into a normal science phase that allows for efficient discovery within a prevailing paradigm. Many would agree that the heady early days of bioinformatics experienced a makeshift feel, which has since matured into a more coherent, productive discipline with an established canon. But before claiming the exalted status of a Kuhnian paradigm shift, it should be mentioned that Kuhn experienced in mind rather broader disciplines of science than bioinformatics, which was erected within and in relation to the comprehensive pre-existing scaffoldings of biology and computer science. To the degree that bioinformatics is definitely a subsidiary or derivative field, it might call more for an evolutionary than a revolutionary model of development, of a type some critics of Kuhn possess advocated [2], [3]. From this perspective, its novelty and force maybe derive from hybrid vigor rather than spontaneous generation, and it would seem to be more enabling than overturningthus, primarily an advance in techne. Whether its quick uptake and considerable effect qualify it as a technical revolution, or simply an evolutionary saltation, could very well be just a matter of semantics. In Rabbit Polyclonal to RRAGA/B Kuhn’s semantics, though, scientific revolutions make profound shifts inside our literal perception of truth. A.