TMBETA-GENOME: database for annotated beta-barrel membrane proteins in genomic sequences.
We have developed the database, TMBETA-GENOME, for annotated beta-barrel membrane proteins in genomic sequences using statistical methods and machine learning algorithms. The statistical methods are based on amino acid composition, reside pair preference and motifs. In machine learning techniques, the combination of amino acid and dipeptide compositions has been used as main attributes. In addition, annotations have been made using the criterion based on the identification of beta-barrel membrane proteins and exclusion of globular and transmembrane helical proteins. A web interface has been developed for identifying the annotated beta-barrel membrane proteins in all known genomes. The users have the feasibility of selecting the genome from the three kingdoms of life, archaea, bacteria and eukaryote, and five different methods. Further, the statistics for all genomes have been provided along with the links to different algorithms and related databases. It is freely available at http://tmbeta-genome.cbrc.jp/annotation/.
Gromiha
M Michael
MM
Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) AIST Tokyo Waterfront Bio-IT Research Building, 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan. michael-gromiha@aist.go.jp
Yabuki
Yukimitsu
Y
Kundu
Srinesh
S
Suharnan
Sivasundaram
S
Suwa
Makiko
M
D000465:Algorithms; D001185:Artificial Intelligence; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D023281:Genomics; D020407:Internet; D008565:Membrane Proteins / Q000737:chemistry* / Q000235:genetics*; D017433:Protein Structure, Secondary; D020539:Sequence Analysis, Protein; D014584:User-Computer Interface
D008565:Membrane Proteins