Pregled bibliografske jedinice broj: 72026
Symbolic Cantor algorithm defines secondary protein structure of eukaryotes, prokaryotes and viruses
Symbolic Cantor algorithm defines secondary protein structure of eukaryotes, prokaryotes and viruses // Book of Abstracts MATH/CHEM/COMP/2001 / Graovac, Ante; Pokrić, Biserka; Smrečki, Vilko (ur.).
Zagreb: Institut Ruđer Bošković, 2001. (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 72026 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Symbolic Cantor algorithm defines secondary
protein structure of eukaryotes, prokaryotes and
viruses
Autori
Štambuk, Nikola ; Konjevoda, Paško ; Pokrić, Biserka
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
Book of Abstracts MATH/CHEM/COMP/2001
/ Graovac, Ante; Pokrić, Biserka; Smrečki, Vilko - Zagreb : Institut Ruđer Bošković, 2001
Skup
MATH/CHEM/COMP/2001 - The 16th Dubrovnik
International Course & Conference on the
Interfaces among Mathematics, Chemistry and
Computer Sciences
Mjesto i datum
Dubrovnik, Hrvatska, 25.06.2001. - 30.06.2001
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
amino acids; Cantor; coding; computational algorithm; eukaryotes; machine learning; nucleotides; prokaryotes; protein folding; structure; viruses
Sažetak
We present new computational algorithm for the
secondary protein structure prediction. The method
is named Symbolic Cantor Algorithm (SCA), and it
is based on the symbolic dynamics and Cantor set
coding of the nucleotide and amino acid addresses
on the binary tree (Štambuk, N. (2000) Croat.
Chem. Acta 73, 1123). The algorithm has two steps.
Protein or gene sequence is first transformed into
a numerical series of the symbolic coding
addresses. The second step of the model involves
the extraction of the rules for the recognition of
particular folding type by means of the machine
learning and spectral analyses of different string
parameters. The method was tested on nonhomologous
alpha- and beta-protein folds obtained from the
Jpred database. It is shown that SCA enables
quick, simple and accurate prediction of the
secondary protein folding types on a personal
computer.
Izvorni jezik
Engleski
Znanstvena područja
Temeljne medicinske znanosti