Service Support for Bioinformatics

With the advancement of biology and computer science, the amount of bioinformatics data has grown at a rapid rate. Due to this increasing demand for performance and testing of new algorithms, bioinformaticians are required to maintain efficient technological infrastructures. Hence, the adoption of such novel technologies is necessary to handle the increasing demand of the industry. The workflow management systems have shifted towards executing processes on top of distributed and parallel information systems, resulting in distributed workflow management systems.

In the present, developers tend to use existing software components or cloud services to build applications rather than developing as all new code. One such requirement in distributed workflow management systems is the monitoring of the progress and state of each of the tasks from a central location. End users should be able to track information of workflows such as real-time status, anomalies and failures. However, it is challenging to find such platforms or services to remotely observe the progress or the state of a distributed workflow execution. Developers are required to build such monitoring modules from the ground up.

Web services have become a common means of addressing distributed task execution. Web services play a significant role to maintain infrastructure in the healthcare domain due to the increasing demand for performance. There are several such services available at present that cater to the requirements in the domain of bioinformatics. However, it is challenging to find efforts made to utilize the Graphics Processing Unit (GPU) accelerated binaries to optimize web services for bioinformatics analyses. Most of the bioinformatics related algorithms are compute-intensive due to their exponential time complexities. Corresponding execution times are further increased as the sequence databases grow rapidly. However, harnessing parallel computational power gives us a pathway to execute these algorithms and allows us to obtain results from web services more efficiently.

The adoption of novel technologies is necessary to increase productivity and reduce the burden of maintenance associated with legacy systems. Microservices architecture has become prominent in deploying server-side enterprise applications by allowing maintainable functionalities. However, it is challenging to utilize microservices in the domain of bioinformatics, although it enables independent process execution and maintenance.

The research addresses a cloud service, which provides real-time monitoring for distributed workflow executions. The proposed solution provides a pluggable service module which enables remote monitoring of workflow execution, observation of current state and debugging of the service from a central location. The solution is presented as a simple API, where the developer is only required to invoke methods and publish the state, followed by the reception of such broadcasts from a remote user interface for monitoring.

In another direction, the research addresses the utilization of web services to provide GPU accelerated bioinformatics computations for analytical purposes. A unified service platform is developed in the form of a collection of web services. It utilizes both GPU and CPU processing in order to perform compute-intensive tasks related to biological data analysis.

Another research addresses the utilization of microservices architecture to build an optimized platform for bioinformatics analyses. We present a hybrid architecture that consists of different hardware platforms to execute accelerated computational services, independently. The core communication is based on an Application Programming Interface (API) gateway.

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