Publication

Abstract : Biological data has more variation in type and format compared to other types of data. Thus, it poses new challenges. However, it encapsulates critical information; thus, handling it is of primary interest. Data handling includes storage and retrieval of data with associated formats and methods of data transfer, data format conversion, algorithms that run on the data and the output methods including visualization of the results. High throughput methods have been yielding biological data at a fast pace. This data includes protein-protein interactions, gene sequences, gene co-expressions, and protein sequences. This data is supplemented with huge amounts of clinical data conveniently captured in electronic medical records and the wet lab data. We describe the current approaches, each with a model system and identify its key contributions. We propose some ideas for biological data handling in the future.