2016/05/26 by Camille Marchet, Marchet, Camille, Antoine Limasset +5
Computer Science · #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #Evolutionary Algorithms and Applications #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Metaheuristic Optimization Algorithms Research
paper · pdf · doi:10.48550/arxiv.1605.08319
openalex publication_date 2016/05/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Genomic and metagenomic fields, generating huge sets of short genomic sequences, brought their own share of high performance problems. To extract relevant pieces of information from the huge data sets generated by current sequencing techniques, one must rely on extremely scalable methods and solutions. Indexing billions of objects is a task considered too expensive while being a fundamental need in this field. In this paper we propose a straightforward indexing structure that scales to billions of element and we propose two direct applications in genomics and metagenomics. We show that our proposal solves problem instances for which no other known solution scales-up. We believe that many tools and applications could benefit from either the fundamental data structure we provide or from the applications developed from this structure.