The modern day advancement is increasingly digitizing our lives which has led to a rapid
growth of data. Such multidimensional datasets are precious due to the potential of …

The increasing adoption of Big Data analytics has led to a high demand for efficient
technologies in order to manage and process large datasets. Popular MapReduce …

Motivation We previously proposed a paradigm shift in genomic data management, based
on the Genomic Data Model (GDM) for mediating existing data formats and on the …

Scientific discoveries are increasingly driven by analyzing large volumes of image data.
Many new libraries and specialized database management systems (DBMSs) have …

This study compares the performance of Big Data Stream Processing frameworks including
Apache Spark, Flink, and Storm. Also, it measures the resource usage and performance …

Distributed data processing platforms for cloud computing are important tools for large-scale
data analytics. Apache Hadoop MapReduce has become the de facto standard in this …

As the size of Big Data workloads keeps increasing, the evaluation of distributed frameworks
becomes a crucial task in order to identify potential performance bottlenecks that may delay …

Next Generation Sequencing (NGS) is a family of technologies for reading the DNA or RNA,
capable of producing whole genome sequences at an impressive speed, and causing a …

Abstract Next Generation Sequencing is a 10-year old technology for reading the DNA,
capable of producing massive amounts of genomic data-in turn, reshaping genomic …

We highlight several challenges which are faced by data scientists who use public datasets
for solving biological and clinical problems. In spite of the large efforts in building such …