Abstract:
Bioinformatics is a growing field focused on both
the domains of computer science and biology. A range of
bioinformatics data processing tools exists at present, which
takes inputs and produces outputs in varying formats depending
on the algorithms and processes being used. The undesirable
situation where such processes would produce outputs that may
not allow the pipelining of other processes, calls for a generic
bioinformatics data format converter. Though such converters
currently exist, most of them are limited to text conversions and
provide limited functionality. In addition, such functions have
the potential capability of supporting parallelism to increase the
overall throughput. A solution that can provide the said
conversion functions as well as utility functions, while
processing with a high throughput via parallelism is proposed
through this paper. A utility function of this system requires
storing bioinformatics data locally. In addition to facilitating
this, an average compression rate of 26% achieved in data
storage. Evaluation of the system using a set of 7,000,000 gene
data showed the maximum time consumption for retrieval as
400ms.
