In the last 20 years, biological sequence data have been accumulating at exponential rate under continuous improvement of sequencing technology, progress in computer science, and steady increase of funding. Molecular sequence databases (e.g., EMBL, Genbank, DDJB, Entrez, Swissprot, etc.) currently collect hundreds of thousands of sequences of nucleotides and amino acids from biological laboratories all over the world, reaching into the hundreds of terabytes. Such an exponential growth makes it increasingly important to have fast and automatic methods to process, analyze, and visualize massive amounts of data.

Computational Biology

Ferragina, Paolo;MANZINI, Giovanni
2018-01-01

Abstract

In the last 20 years, biological sequence data have been accumulating at exponential rate under continuous improvement of sequencing technology, progress in computer science, and steady increase of funding. Molecular sequence databases (e.g., EMBL, Genbank, DDJB, Entrez, Swissprot, etc.) currently collect hundreds of thousands of sequences of nucleotides and amino acids from biological laboratories all over the world, reaching into the hundreds of terabytes. Such an exponential growth makes it increasingly important to have fast and automatic methods to process, analyze, and visualize massive amounts of data.
2018
Kurtz, Stefan; Lonardi, Stefano; Ferragina, Paolo; Manzini, Giovanni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1097570
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