Abstract: An object-based data storage system implemented by a computer for storing data in a plurality of objects (16A, 16B, 25A, 25B). The data storage system comprises a storage medium (80) configured to store said plurality of objects. Each one of the plurality of objects comprises a plurality of fields including a data field (18) configured for storing said data therein and, a separate object ID attribute field (17) configured for storing identification information associated with the object. The information stored within the object ID attribute field of at least one (16A, 16B) of the plurality of objects comprises metadata other than identification information associated with the at least one object. A processor is configured to access the at least one object (16A, 16B) from amongst the plurality of objects stored within the storage medium at least to retrieve information stored within an object ID attribute field (17) hereof thereby to retrieve the metadata.

Abstract: A data processing system includes a data processing arrangement, wherein the data processing arrangement includes computing hardware for executing one or more software products, wherein execution of the one or more software products configures the data processing arrangement to access data from a file system arrangement.

Abstract: A data processing system includes a data processing arrangement, wherein the data processing arrangement includes computing hardware for executing one or more software products, wherein execution of the one or more software products configures the data processing arrangement to access data from a file system arrangement.

Abstract: There is provided a system (900) for generating output genomics data (970) from biological genetic material (930).

Abstract: A data compression method using the range variant of asymmetric numeral systems to encode a data stream, where the probability distribution table is constructed using a Markov model. This type of encoding results in output that has higher compression ratios when compared to other compression algorithms and it performs particularly well with information that represents gene sequences or information related to gene sequences.

Abstract: This invention relates to the quality scores of bases produced from high throughput genomic sequencing, in particular to transforming the quality scores for improved compressibility. A method for transforming these quality scores is described whereby a quality score is modified by utilising a Bayesian model based on Coding Theory combined with search results from a genomic corpus. A related method is described for efficient searching for a Read in a genomic corpus so as to find all matching symbols up to a given Hamming-distance or Edit-distance.

Abstract: A data compression method using the range variant of asymmetric numeral systems to encode a data stream, where the probability distribution table is constructed using a Markov model. This type of encoding results in output that has higher compression ratios when compared to other compression algorithms and it performs particularly well with information that represents gene sequences or information related to gene sequences.