Pregled bibliografske jedinice broj: 202507
INCA: synonymous codon usage analysis and clustering by means of self-organizing map
INCA: synonymous codon usage analysis and clustering by means of self-organizing map // Bioinformatics, 20 (2004), 14; 2329-2330 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 202507 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
INCA: synonymous codon usage analysis and clustering by means of self-organizing map
Autori
Supek, Fran ; Vlahoviček, Kristian
Izvornik
Bioinformatics (1367-4803) 20
(2004), 14;
2329-2330
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
codon usage; software; cai; codon bias
Sažetak
SUMMARY: INteractive Codon usage Analysis (INCA) provides an array of features useful in analysis of synonymous codon usage in whole genomes. In addition to computing codon frequencies and several usage indices, such as 'codon bias', effective Nc and CAI, the primary strength of INCA has numerous options for the interactive graphical display of calculated values, thus allowing visual detection of various trends in codon usage. Finally, INCA includes a specific unsupervised neural network algorithm, the self-organizing map, used for gene clustering according to the preferred utilization of codons. AVAILABILITY: INCA is available for the Win32 platform and is free of charge for academic use. For details, visit the web page http://www.bioinfo-hr.org/inca or contact the author directly. SUPPLEMENTARY INFORMATION: Software is accompanied with a user manual and a short tutorial.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Računarstvo, Biotehnologija
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE
Uključenost u ostale bibliografske baze podataka::
- Chemical Abstracts
- Index Medicus
- BIOSIS