Yazar "Otu, Hasan Hüseyin" seçeneğine göre listele

Listeleniyor 1 - 4 / 4
  • Küçük Resim Yok
    Öğe
    Bayes ağları kapsamında yüksek çıktılı biyolojik veri analizi: Sistem Biyolojisi Yaklaşımı
    (2013) Otu, Hasan Hüseyin
    [Abstract Not Available]
  • Küçük Resim
    Öğe
    Clustering of protein families into functional subtypes using Relative Complexity Measure with reduced amino acid alphabets
    (Bmc, 2010-08-18) Otu, Hasan Hüseyin; Albayrak, Aydın; Sezerman, Uğur
    Background: Phylogenetic analysis can be used to divide a protein family into subfamilies in the absence of experimental information. Most phylogenetic analysis methods utilize multiple alignment of sequences and are based on an evolutionary model. However, multiple alignment is not an automated procedure and requires human intervention to maintain alignment integrity and to produce phylogenies consistent with the functional splits in underlying sequences. To address this problem, we propose to use the alignment-free Relative Complexity Measure (RCM) combined with reduced amino acid alphabets to cluster protein families into functional subtypes purely on sequence criteria. Comparison with an alignment-based approach was also carried out to test the quality of the clustering. Results: We demonstrate the robustness of RCM with reduced alphabets in clustering of protein sequences into families in a simulated dataset and seven well-characterized protein datasets. On protein datasets, crotonases, mandelate racemases, nucleotidyl cyclases and glycoside hydrolase family 2 were clustered into subfamilies with 100% accuracy whereas acyl transferase domains, haloacid dehalogenases, and vicinal oxygen chelates could be assigned to subfamilies with 97.2%, 96.9% and 92.2% accuracies, respectively. Conclusions: The overall combination of methods in this paper is useful for clustering protein families into subtypes based on solely protein sequence information. The method is also flexible and computationally fast because it does not require multiple alignment of sequences.
  • Küçük Resim
    Öğe
    Pathway analysis of high-throughput biological data within a Bayesian network framework
    (Oxford Univ Press, 2011-06-15) Otu, Hasan Hüseyin; Jones, Jon; Öztürk, Cengizhan; İşçi, Şenol
    Motivation: Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and nonlinear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Results: Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC.
  • Küçük Resim
    Öğe
    Reprogrammed Transcriptome in Rhesus-Bovine Interspecies Somatic Cell Nuclear Transfer Embryos
    (Public Library Science, 2011-07-25) Otu, Hasan Hüseyin; Wang, Kai; Chen, Ying; Lee, Young; Latham, Keith; Cibelli, Jose B.
    Background: Global activation of the embryonic genome (EGA), one of the most critical steps in early mammalian embryo development, is recognized as the time when interspecies somatic cell nuclear transfer (iSCNT) embryos fail to thrive. Methodology/Principal Findings: In this study, we analyzed the EGA-related transcriptome of rhesus-bovine iSCNT 8-to 16-cell embryos and dissected the reprogramming process in terms of embryonic gene activation, somatic gene silencing, and maternal RNA degradation. Compared with fibroblast donor cells, two thousand and seven genes were activated in iSCNT embryos, one quarter of them reaching expression levels comparable to those found in in vitro fertilized (IVF) rhesus embryos. This suggested that EGA in iSCNT embryos had partially recapitulated rhesus embryonic development. Eight hundred and sixty somatic genes were not silenced properly and continued to be expressed in iSCNT embryos, which indicated incomplete nuclear reprogramming. We compared maternal RNA degradation in bovine oocytes between bovine-bovine SCNT and iSCNT embryos. While maternal RNA degradation occurred in both SCNT and iSCNT embryos, we saw more limited overall degradation of maternal RNA in iSCNT embryos than in SCNT embryos. Several important maternal RNAs, like GPF9, were not properly processed in SCNT embryos. Conclusions/Significance: Our data suggested that iSCNT embryos are capable of triggering EGA, while a portion of somatic cell-associated genes maintain their expression. Maternal RNA degradation seems to be impaired in iSCNT embryos. Further understanding of the biological roles of these genes, networks, and pathways revealed by iSCNT may expand our knowledge about cell reprogramming, pluripotency, and differentiation.