Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 368917

ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling


Starcevic, Antonio
ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling // Book of Abstracts - KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications / Gamberger, Dragan (ur.).
Zagreb: Institut Ruđer Bošković, 2008. (predavanje, nije recenziran, sažetak, znanstveni)


CROSBI ID: 368917 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling

Autori
Starcevic, Antonio

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of Abstracts - KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications / Gamberger, Dragan - Zagreb : Institut Ruđer Bošković, 2008

Skup
KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications

Mjesto i datum
Poreč, Hrvatska, 17.10.2008. - 19.10.2008

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
ClustScan; CompGen; gene-clusters; annotation; data mining; homologous recombination

Sažetak
ClustScan program package is a bioinformatic tool developed mainly for the collection, storage and precise annotation of polyketide, non-ribosomal peptide and other modular biosynthetic gene cluster data hidden in continuously increasing number of sequenced genomes. On the other hand, CompGen relies on ClustScan's data in order to simulate homologous recombination events that might happen between gene clusters sequences. We have succeeded to incorporate published and propriety knowledge about modular biosythetic gene clusters in an artificial environment defined by a consistent set of rules. These rules were used for the interpretation of components roles in this environment. The components are the DNA and protein sequences coming from genomes or generated by various programs used by ClustScan. The rules are empirical facts collected from the relevant published scientific papers. As far as we are aware, this system is unique in being able to predict chemical structures from gene cluster DNA sequences and to use known natural products to generate novel "un-natural" ones by homologous recombination simulation. Our future efforts will be to make ClustScan program package more generic, making it able to scan for gene clusters other than modular ones. Secondly, using CompGen, we will create a database of novel compounds which will allow screening of their biological activity using CADD technologies.

Izvorni jezik
Engleski

Znanstvena područja
Biotehnologija



POVEZANOST RADA


Projekti:
0982560
058-0000000-3475 - Generiranje potencijalnih lijekova u uvjetima in silico (Hranueli/Jurica Žučko, Daslav, MZOS ) ( CroRIS)

Ustanove:
Prehrambeno-biotehnološki fakultet, Zagreb

Profili:

Avatar Url Antonio Starčević (autor)


Citiraj ovu publikaciju:

Starcevic, Antonio
ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling // Book of Abstracts - KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications / Gamberger, Dragan (ur.).
Zagreb: Institut Ruđer Bošković, 2008. (predavanje, nije recenziran, sažetak, znanstveni)
Starcevic, A. (2008) ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling. U: Gamberger, D. (ur.)Book of Abstracts - KDSA 2008, Workshop on Knowledge Discovery in Scientific Applications.
@article{article, author = {Starcevic, Antonio}, editor = {Gamberger, D.}, year = {2008}, keywords = {ClustScan, CompGen, gene-clusters, annotation, data mining, homologous recombination}, title = {ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling}, keyword = {ClustScan, CompGen, gene-clusters, annotation, data mining, homologous recombination}, publisher = {Institut Ru\djer Bo\v{s}kovi\'{c}}, publisherplace = {Pore\v{c}, Hrvatska} }
@article{article, author = {Starcevic, Antonio}, editor = {Gamberger, D.}, year = {2008}, keywords = {ClustScan, CompGen, gene-clusters, annotation, data mining, homologous recombination}, title = {ClustScan and CompGen program packages: Semi-automated tools for data mining and homologous recombination modelling}, keyword = {ClustScan, CompGen, gene-clusters, annotation, data mining, homologous recombination}, publisher = {Institut Ru\djer Bo\v{s}kovi\'{c}}, publisherplace = {Pore\v{c}, Hrvatska} }




Contrast
Increase Font
Decrease Font
Dyslexic Font