Data structures and compression algorithms for genomic sequence data

Data structures and compression algorithms for genomic sequence data

MOTIVATION The continuing exponential accumulation of full genome data, including full diploid human genomes, creates new challenges not only for understanding genomic structure, function and evolution, but also for the storage, navigation and privacy of genomic data. Here, we develop data structures and algorithms for the efficient storage of genomic and other sequence data that may also facil...

Algorithms and Data Structures for Sequence Analysis in the Pan-Genomic Era

The advent of Next-Generation Sequencing brought new challenges for biological sequence analysis: larger volumes of sequencing data, a proliferation of research projects relying on genomic analysis, and the materialization of rich genomic databases, to name a few. A recent example of the latter, gnomeAD, contains more than 15,000 whole human genomes from unrelated individuals. Today a pressing ...

“ Algorithms for Genomic Data ”

Algorithms and Data Structures For

With the advent of multigrid iteration, the large linear systems arising in numerical treatment of elliptic boundary value problems can be solved quickly and reliably. This frees the researcher to focus on the other issues involved in numerical solution of elliptic problems: adaptive refinement, error estimation and control, and grid generation. Progress is being made on each of these issues an...

Parsing Algorithms for Data Compression

The task of parsing consists of splitting an input text into a sequence of contiguous phrases. Several classes of data compression algorithms rely on parsing techniques either to identify repetitions inside the input string (dictionary-based compression) or to locate homogeneous pieces of data which are separately compressed (PermutePartition-Compress paradigm). In these applications, the choic...