Research challenges of big data

Bioinformatic Challenges of Big Data in Non-Coding RNA Research

brought forth a new era of RNA research in which large sets of data are collected rapidly using the high-throughput next generation sequencing technology. Growing evidence suggests that only around 5% of nucleotides in the mammalian genomes are transcribed into protein-coding RNA, and large amount of transcripts are nonprotein-coding RNA (ncRNA). During the last decade, much information has bee...

Big Data? More Challenges!

Recent advances in data acquisition technologies have led to massive amount of data being collected routinely in the physical, chemical, and engineering sciences as well as information sciences and technology. In addition to volume, the data often have complicated structure. Examples of such Big Data include the data streams obtained from complex engineering systems, image sequences, climate da...

Task Scheduling in Big Data - Review, Research Challenges, and Prospects

In a Big data computing, the processing of data requires a large amount of CPU cycles and network bandwidth and disk I/O. Dataflow is a programming model for processing Big data which consists of tasks organized in a graph structure. Scheduling these tasks is one of the key active research areas which mainly aims to place the tasks on available resources. It is essential to effectively schedule...

Challenges and opportunities for analysis based research in big data

The challenges of big data

The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that cu...