As analysts are expected to process a greater amount of information in a shorter amount of time, creators of big data software are challenged with the need for improved efficiency. Ray, our group's usable, scalable genome assembler, addresses big data problems by using optimal resources and producing one, correct and conservative, timely solution. Only by abstracting the size of the data from both the computers and the humans can the real scientific question, often complex in itself, eventually be solved.
View Article and Find Full Text PDF