Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Petescia, Alessia"'
Autor:
Baláz, Andrej, Gagie, Travis, Goga, Adrián, Heumos, Simon, Navarro, Gonzalo, Petescia, Alessia, Sirén, Jouni
Motivated by challenges in pangenomic read alignment, we propose a generalization of Wheeler graphs that we call Wheeler maps. A Wheeler map stores a text $T[1..n]$ and an assignment of tags to the characters of $T$ such that we can preprocess a patt
Externí odkaz:
http://arxiv.org/abs/2308.09836
Autor:
Baláž, Andrej, Petescia, Alessia
A recent paradigm shift in bioinformatics from a single reference genome to a pangenome brought with it several graph structures. These graph structures must implement operations, such as efficient construction from multiple genomes and read mapping.
Externí odkaz:
http://arxiv.org/abs/2306.14689
There now exist compact indexes that can efficiently list all the occurrences of a pattern in a dataset consisting of thousands of genomes, or even all the occurrences of all the pattern's maximal exact matches (MEMs) with respect to the dataset. Unl
Externí odkaz:
http://arxiv.org/abs/2209.09218
Autor:
Bonizzoni, Paola, Costantini, Matteo, De Felice, Clelia, Petescia, Alessia, Pirola, Yuri, Previtali, Marco, Rizzi, Raffaella, Stoye, Jens, Zaccagnino, Rocco, Zizza, Rosalba
Publikováno v:
Information Sciences 607 (2022) 458-476
Feature embedding methods have been proposed in literature to represent sequences as numeric vectors to be used in some bioinformatics investigations, such as family classification and protein structure prediction. Recent theoretical results showed t
Externí odkaz:
http://arxiv.org/abs/2202.13884
Autor:
Bonizzoni, Paola, Costantini, Matteo, De Felice, Clelia, Petescia, Alessia, Pirola, Yuri, Previtali, Marco, Rizzi, Raffaela, Stoye, Jens, Zaccagnino, Rocco, Zizza, Rosalba
Publikováno v:
arXiv.org e-Print Archive
Publications at Bielefeld University
Datacite
Publications at Bielefeld University
Datacite
Feature embedding methods have been proposed in the literature to represent sequences as numeric vectors to be used in some bioinformatics investigations, such as family classification and protein structure prediction. Recent theoretical results show