Pregled bibliografske jedinice broj: 468579
Bioinformatics study of nuclear receptor superfamily relation to UniProt data
Bioinformatics study of nuclear receptor superfamily relation to UniProt data // EMBO conference on nuclear receptors
Cavtat, Hrvatska, 2009. (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 468579 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Bioinformatics study of nuclear receptor superfamily relation to UniProt data
Autori
Jeričević, Željko
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
EMBO conference on nuclear receptors
/ - , 2009
Skup
EMBO conference on nuclear receptors
Mjesto i datum
Cavtat, Hrvatska, 25.09.2009. - 29.09.2009
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Nuclear receptors; bioinformatics; classification; eigenanalysis; clustering
Sažetak
Nuclear receptors (NR) classification is based on sequence comparison for conserved domains responsible for the DNA binding and the ligand binding, (C and E domain, respectively.) This well developed system for classification inside the superfamily of nuclear receptors can not be used to relate NR to the rest of protein universe, but we developed a general classification method based on size invariant represenation of the sequence which can do that. The size invariant representation used is of adjacency histogram type with user controlled amount of information, which makes the method of adaptable resolution in space between seqence and motif based classifications. The adjacency histogram is constructed using controlled number and positions of neigbours in the sequence. Inside this representation the neigbours can be amino acids themselves or some combination of their characteristic physicochemical properties, like acidity, hidrofobicity, polarity, aromacity, size, etc. In the first step, the classification parameters were optimized to repeat the results of sequence based classification inside the superfamily of nuclear receptors. The analyis and optimization of representations are done using eigenanalyis and clustering methods. The same representations are then constructed for proteins from UniProt data base and relation of nuclear receptors to the rest of the universe was analysed finding closest negbours to nuclear receptor superfamily.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Računarstvo
POVEZANOST RADA
Projekti:
062-0000000-3179 - Klasifikacija proteina metodama eigen-analize
098-0982915-2942 - Razvoj matematičkih metoda za opis strukture, dinamike i reaktivnosti molekula (Babić, Darko, MZOS ) ( CroRIS)
Ustanove:
Medicinski fakultet, Rijeka,
Tehnički fakultet, Rijeka
Profili:
Željko Jeričević
(autor)