Yasubumi Sakakibara

TL;DR: An important step in ‘metagenomics’ analysis is the assembly of multiple genomes from mixed sequence reads of multiple species in a microbial community, and a single-genome assembler for short reads was extended to metagenome assembly.

TL;DR: Results show that after having been trained on as few as 20 tRNA sequences from only two tRNA subfamilies, the model can discern general tRNA from similar-length RNA sequences of other kinds, can find secondary structure of new t RNA sequences, and can produce multiple alignments of large sets of tRNAs.

TL;DR: MetaVelvet succeeded to generate higher N50 scores and smaller chimeric scaffolds than any compared single-genome assemblers, produce high-quality scaffolds as well as the separate assembly using Velvet from isolated species sequence reads, and MetaVelvet reconstructed even relatively low-coverage genome sequences as scaffolds.

TL;DR: It is shown that the class of reversible context-free grammars can be identified in the limit frompositive samples of structural descriptions and there exists an efficient algorithm to identify them from positive samples ofStructural descriptions, where a structural description of a context- free grammar is an unlabelled derivation tree of the grammar.

TL;DR: In this paper, an efficient algorithm for learning context-free grammars using two types of queries, structural equivalence queries and structural membership queries, is presented. But it is not shown that a grammar learned by the algorithm is not only a correct grammar but also structurally equivalent to it.