By Teresa K. Attwood, Stephen R. Pettifer, David Thorne
This cutting edge ebook offers a totally clean exploration of bioinformatics, investigating its complicated interrelationship with biology and desktop technology. It techniques bioinformatics from a distinct standpoint, highlighting interdisciplinary gaps that frequently capture the unwary.
The booklet considers how the necessity for organic databases drove the evolution of bioinformatics; it reports bioinformatics fundamentals (including database codecs, data-types and present research methods), and examines key issues in computing device technology (including data-structures, identifiers and algorithms), reflecting on their use and abuse in bioinformatics.
Bringing those disciplines jointly, this ebook is a vital learn in case you desire to higher comprehend the demanding situations for bioinformatics on the interface of biology and machine technology, and the way to bridge the gaps. it will likely be a useful source for complicated undergraduate and postgraduate scholars, and for academics, researchers and pros with an curiosity during this attention-grabbing, fast-moving self-discipline and the knotty difficulties that encompass it.
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Extra info for Bioinformatics challenges at the interface of biology and computer science: mind the gap
Perhaps more importantly, researchers wanted to know how sequence and structure information could be used to elucidate the roles of particular genes and proteins in pathogenic processes, and how the assembled data could be used to design better, more efficacious drugs. Later, with the advent of the human genome‐sequencing project, the goals became increasingly ambitious, and the focus of attention turned more and more towards using bioinformatics to revolutionise molecular medicine. Researchers wanted to identify the Chapter 1 Introduction genetic determinants both of rare syndromes and of common, pervasive diseases like cancer; bioinformatics, it was claimed, would play a major role in the development of new approaches to eradicate such diseases, and would pave the way to personalised therapies, where an individual’s genome could be used to determine which drug regime would offer maximal benefit with the minimum of side‐effects.
Biochemical Journal, 60(4), 556–565. Cantor, C. (2000) Biotechnology in the 21st century. Trends in Biotechnology, 18, 6–7. A. R. (eds) (1965) Atlas of Protein Sequence and Structure. National Biomedical Research Foundation, Silver Spring, MD, USA. O. to Berkley, C. (1967) Margaret O. Dayhoff Papers, Archives of the National Biomedical Research Foundation, Washington, DC. Editorial. (2001) A cold dose of medicine. Nature Biotechnology, 19(3), 181. E. G. (1953) a) The structure of sodium thymonucleate fibres.
In the chapters that follow, we will explore some of the complexities. We’ll look at the transition from numeric to symbolic algorithms that was necessary to allow bioinformatics to move beyond the computation, say, of sequence comparison scores, to manipulation of concepts or entities, such as ‘prion’, ‘promoter’, ‘helix’, and so on (Attwood and Miller, 2001). We’ll touch on many of the emerging techniques that are being used to transform data into knowledge, exploring how ontologies can be used to give meaning to raw information, how semantic integration is beginning to make it possible to join up disparate data‐sets, and how visualisation techniques provide a way of harnessing human intuition in situations where computational techniques fall short.
Bioinformatics challenges at the interface of biology and computer science: mind the gap by Teresa K. Attwood, Stephen R. Pettifer, David Thorne