Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0

'Big data', Hadoop and cloud computing in genomics

A novel features ranking metric with application to scalable visual and bioinformatics data classification

The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges

Various microRNAs have been demonstrated to play roles in a number of human diseases. Several microRNA-disease network reconstruction methods have been used to describe the association from a systems biology perspective. The key problem for the network is the similarity computation model. In this article, we reviewed the main similarity computation methods and discussed these methods and future works. This survey may prompt and guide systems biology and bioinformatics researchers to build more perfect microRNA-disease associations and may make the network relationship clear for medical researchers.

Similarity computation strategies in the microRNA-disease network: a survey

Bioinformatics is challenged by the fact that traditional analysis tools have difficulty in processing large-scale data from high-throughput sequencing. The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services. In this article, we present MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains. In addition, we discuss the challenges faced by this field as well as the future works on parallel computing in bioinformatics.

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Xubin Li

Papers

Survey of MapReduce frame operation in bioinformatics

BinMemPredict: a Web Server and Software for Predicting Membrane Protein Types

Research of Efficient C/S Model Based File Transfer Method