Automated classification of alternative splicing and transcriptional initiation and construction of visual database of classified patterns.
BACKGROUND
Large-scale detection and classification of alternative splicing and transcriptional initiation (ASTI) is the first step towards detailed studies of the functional implication and mechanisms of these phenomena.


RESULTS
We have developed an algorithm that classifies all observed units of ASTI into an extendable set of distinct types (e.g. cassette type) by converting a collection of alignments between a genomic DNA sequence and cDNA sequences into binary description. This description system can uniquely and compactly encode not only typical patterns but also any rare patterns that are usually collectively assigned to 'others.' More than 150 distinct ASTI types were found when this system was applied to genome-wide detection of ASTI units in human and five other eukaryotes.


BACKGROUND
The data detected by this system are available through ASTRA (http://alterna.cbrc.jp/), a database equipped with a Java-based browser that can interactively reorganize the order of displayed splicing patterns on demand.
Nagasaki
Hideki
H
Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology Tokyo 135-0064, Japan. h-nagasaki@aist.go.jp
Arita
Masanori
M
Nishizawa
Tatsuya
T
Suwa
Makiko
M
Gotoh
Osamu
O
D000465:Algorithms; D017398:Alternative Splicing / Q000235:genetics*; D001185:Artificial Intelligence; D001483:Base Sequence; D003196:Computer Graphics; D030541:Databases, Genetic; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D024363:Transcription Initiation Site; D014584:User-Computer Interface