Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 6 von 669
International journal of biomathematics, 2014-09, Vol.7 (5), p.1450053
2014
Volltextzugriff (PDF)

Details

Autor(en) / Beteiligte
Titel
Chapman–Kolmogorov equations for global PPIs with Discriminant-EM
Ist Teil von
  • International journal of biomathematics, 2014-09, Vol.7 (5), p.1450053
Erscheinungsjahr
2014
Beschreibungen/Notizen
  • Ongoing improvements in Computational Biology research have generated massive amounts of Protein–Protein Interactions (PPIs) dataset. In this regard, the availability of PPI data for several organisms provoke the discovery of computational methods for measurements, analysis, modeling, comparisons, clustering and alignments of biological data networks. Nevertheless, fixed network comparison is computationally stubborn and as a result several methods have been used instead. We illustrate a probabilistic approach among proteins nodes that are part of various networks by using Chapman–Kolmogorov (CK) formula. We have compared CK formula with semi-Markov random method, SMETANA. We significantly noticed that CK outperforms the SMETANA in all respects such as efficiency, speed, space and complexity. We have modified the SMETANA source codes available in MATLAB in the light of CK formula. Discriminant-Expectation Maximization (D-EM) accesses the parameters of a protein network datasets and determines a linear transformation to simplify the assumption of probabilistic format of data distributions and find good features dynamically. Our implementation finds that D-EM has a satisfactory performance in protein network alignment applications.
Sprache
Englisch
Identifikatoren
ISSN: 1793-5245
eISSN: 1793-7159
DOI: 10.1142/S1793524514500533
Titel-ID: cdi_crossref_primary_10_1142_S1793524514500533
Format

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX