title: EMMA: an efficient massive mapping algorithm using improved approximate mapping filtering.
abstract: Efficient massive mapping algorithm (EMMA), an algorithm on efficiently mapping massive cDNAs onto genomic sequences, has recently been developed. The process of mapping massive cDNAs onto genomic sequences has been improved using more approximate mapping filtering based on an enhanced suffix array coupled with a pruned fast hash table, algorithms of block alignment extensions, and k-longest paths. When compared with the classical BLAT software in this field, the computing of EMMA ranges from two to forty-one times faster under similar prediction precisions.
authors.affiliation: Institute of Micro/Nano Science and Technology, Shanghai Jiaotong University, Shanghai 200030, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Zhang
authors.forename: Zhi-Wei
authors.initials: ZW
authors.lastname: Cao
authors.forename: Zhi-Xin
authors.initials: ZX
authors.lastname: Lin
authors.forename: Qing-Kang
authors.initials: QK
authors.lastname: Wang
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D018076:DNA, Complementary / Q000378:metabolism; D030541:Databases, Genetic; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011381:Programming Languages; D015203:Reproducibility of Results; D012984:Software
chemical_list: D018076:DNA, Complementary