Your Passport to a Career in Bioinformatics (eBook, PDF)
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The book is a ready reckoner aimed at the student community aspiring to take up a career in bioinformatics. The book firstly provides a perspective on the domain and addresses the challenges faced by community namely the attempts to understand data produced by genome sequencing projects. It then brings to light High Performance Computing (HPC) as it helps in interpreting and analyzing genome sequences. The book also dwells on how interactions in a systems (organism), the components that interact with each other and the outcome of such interactions. It then calls for a consensus on the tools li...
The book is a ready reckoner aimed at the student community aspiring to take up a career in bioinformatics. The book firstly provides a perspective on the domain and addresses the challenges faced by community namely the attempts to understand data produced by genome sequencing projects. It then brings to light High Performance Computing (HPC) as it helps in interpreting and analyzing genome sequences. The book also dwells on how interactions in a systems (organism), the components that interact with each other and the outcome of such interactions. It then calls for a consensus on the tools like rapid and inexpensive DNA sequencing technologies, HAPMAP projects, Dollar One Genome (DOG), to enable a reader understand how bioinformatics transits from research, to vocation and avocation. Further it extols the virtues of in silico for bioinformatical predictions as it helps wet-lab biologists reduce time for experiments. Also it describes the intricacies of bioinformatics and its usefulness to wet-based biologists and other cross-disciplinarians. The book lists out 10 reasons for taking up bioinformatics as a career, and includes insights from global experts on the domain. It also makes a case for a mediocre student getting into bioinformatics with discipline, determination, dynamism and diligence. The book further describes BioinformaTICKS a tool for emerging as a winner in bioinformatics.
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