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Search Results: 1 - 10 of 152567 matches for " Hasan H Otu "
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Whole Genome Sequence of a Turkish Individual
Haluk Dogan, Handan Can, Hasan H. Otu
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0085233
Abstract: Although whole human genome sequencing can be done with readily available technical and financial resources, the need for detailed analyses of genomes of certain populations still exists. Here we present, for the first time, sequencing and analysis of a Turkish human genome. We have performed 35x coverage using paired-end sequencing, where over 95% of sequencing reads are mapped to the reference genome covering more than 99% of the bases. The assembly of unmapped reads rendered 11,654 contigs, 2,168 of which did not reveal any homology to known sequences, resulting in ~1 Mbp of unmapped sequence. Single nucleotide polymorphism (SNP) discovery resulted in 3,537,794 SNP calls with 29,184 SNPs identified in coding regions, where 106 were nonsense and 259 were categorized as having a high-impact effect. The homo/hetero zygosity (1,415,123:2,122,671 or 1:1.5) and transition/transversion ratios (2,383,204:1,154,590 or 2.06:1) were within expected limits. Of the identified SNPs, 480,396 were potentially novel with 2,925 in coding regions, including 48 nonsense and 95 high-impact SNPs. Functional analysis of novel high-impact SNPs revealed various interaction networks, notably involving hereditary and neurological disorders or diseases. Assembly results indicated 713,640 indels (1:1.09 insertion/deletion ratio), ranging from ?52 bp to 34 bp in length and causing about 180 codon insertion/deletions and 246 frame shifts. Using paired-end- and read-depth-based methods, we discovered 9,109 structural variants and compared our variant findings with other populations. Our results suggest that whole genome sequencing is a valuable tool for understanding variations in the human genome across different populations. Detailed analyses of genomes of diverse origins greatly benefits research in genetics and medicine and should be conducted on a larger scale.
Clustering of protein families into functional subtypes using Relative Complexity Measure with reduced amino acid alphabets
Aydin Albayrak, Hasan H Otu, Ugur O Sezerman
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-428
Abstract: 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.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.Proteins that evolve from a common ancestor can change functionality over time [1] and produce highly divergent protein families that can be divided into subfamilies with similar but distinct functions (i.e., functional subfamilies or subtypes) [2]. Identification of subfamilies using protein sequence information can be carried out using phylogenetic methods that can reveal the evolutionary relationship between proteins by clustering similar proteins together in a phylogenetic tree [3-5]. The most common method for identifying similarities in sequences through phylogenetic analysis starts with the construction of a multiple alignment of homologous sequences using a substitution matrix. Multiple alignment scores are then transformed into a distance matrix to construct a phylogenetic tree. Often the branching order of a phylogenetic tree exactly matches the known functional split between proteins [1] and branch lengths are proportional to the extent of evolutionary changes since the last common ancestor.Multiple sequence alignment (MSA) is constructed using a scoring scheme which reward or penalize each substitution, insertion and deletion to get an optimum alignment of the given sequences. The quality of an
Grammar-based distance in progressive multiple sequence alignment
David J Russell, Hasan H Otu, Khalid Sayood
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-306
Abstract: The performance of the proposed algorithm is validated via comparison to popular progressive multiple alignment approaches, ClustalW and T-Coffee, and to the more recently developed algorithms MAFFT, MUSCLE, Kalign, and PSAlign using the BAliBASE 3.0 database of amino acid alignment files and a set of longer sequences generated by Rose software. The proposed algorithm has successfully built multiple alignments comparable to other programs with significant improvements in running time. The results are especially striking for large datasets.We introduce a computationally efficient progressive alignment algorithm using a grammar based sequence distance particularly useful in aligning large datasets.Generation of meaningful multiple sequence alignments (MSAs) of biological sequences is a well-studied NP-complete problem, which has significant implications for a wide spectrum of applications [1,2]. In general, the challenge is aligning N sequences of varying lengths by inserting gaps in the sequences so that in the end all sequences have the same length. Of particular interest to computational biology are DNA/RNA sequences and amino acid sequences, which are comprised of nucleotide and amino acid residues, respectively.MSAs are generally used in studying phylogeny of organisms, structure prediction, and identifying segments of interest among many other applications in computational biology [3].Given a scoring scheme to evaluate the fitness of an MSA, calculating the best MSA is an NP-complete problem [1]. Variances in scoring schemes, need for expert-hand analysis in most applications, and many-to-one mapping governing elements-to-functionality (codon mapping and function) make MSA a more challenging problem when considered from a biological context as well [4].Generally, three approaches are used to automate the generation of MSAs. The first offers a brute-force method of multidimensional dynamic programming [5], which may find a good alignment but is generally computat
Testing robustness of relative complexity measure method constructing robust phylogenetic trees for Galanthus L. Using the relative complexity measure
Bak?? Yasin,Otu Hasan H,Ta??? Nivart,Meydan Cem
BMC Bioinformatics , 2013, DOI: 10.1186/1471-2105-14-20
Abstract: Background Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. Result In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. Conclusions Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters.
Bayesian Pathway Analysis of Cancer Microarray Data
Melike Korucuoglu, Senol Isci, Arzucan Ozgur, Hasan H. Otu
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0102803
Abstract: High Throughput Biological Data (HTBD) requires detailed analysis methods and from a life science perspective, these analysis results make most sense when interpreted within the context of biological pathways. Bayesian Networks (BNs) capture both linear and nonlinear interactions and handle stochastic events in a probabilistic framework accounting for noise making them viable candidates for HTBD analysis. We have recently proposed an approach, called Bayesian Pathway Analysis (BPA), for analyzing HTBD using BNs in which known biological pathways are modeled as BNs and pathways that best explain the given HTBD are found. BPA uses the fold change information to obtain an input matrix to score each pathway modeled as a BN. Scoring is achieved using the Bayesian-Dirichlet Equivalent method and significance is assessed by randomization via bootstrapping of the columns of the input matrix. In this study, we improve on the BPA system by optimizing the steps involved in “Data Preprocessing and Discretization”, “Scoring”, “Significance Assessment”, and “Software and Web Application”. We tested the improved system on synthetic data sets and achieved over 98% accuracy in identifying the active pathways. The overall approach was applied on real cancer microarray data sets in order to investigate the pathways that are commonly active in different cancer types. We compared our findings on the real data sets with a relevant approach called the Signaling Pathway Impact Analysis (SPIA).
Reprogrammed Transcriptome in Rhesus-Bovine Interspecies Somatic Cell Nuclear Transfer Embryos
Kai Wang,Hasan H. Otu,Ying Chen,Young Lee,Keith Latham,Jose B. Cibelli
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0022197
Abstract: 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.
Gene expression analysis of embryonic stem cells expressing VE-cadherin (CD144) during endothelial differentiation
Vesna Nikolova-Krstevski, Manoj Bhasin, Hasan H Otu, Towia Libermann, Peter Oettgen
BMC Genomics , 2008, DOI: 10.1186/1471-2164-9-240
Abstract: Mouse embryonic stem (ES) cells were used to further define the molecular mechanisms of endothelial differentiation. By flow cytometry a population of VEGF-R2 positive cells was identified as early as 2.5 days after differentiation of ES cells, and a subset of VEGF-R2+ cells, that were CD41 positive at 3.5 days. A separate population of VEGF-R2+ stem cells expressing the endothelial-specific marker CD144 (VE-cadherin) was also identified at this same time point. Channels lined by VE-cadherin positive cells developed within the embryoid bodies (EBs) formed by differentiating ES cells. VE-cadherin and CD41 expressing cells differentiate in close proximity to each other within the EBs, supporting the concept of a common origin for cells of hematopoietic and endothelial lineages.Microarray analysis of >45,000 transcripts was performed on RNA obtained from cells expressing VEGF-R2+, CD41+, and CD144+ and VEGF-R2-, CD41-, and CD144-. All microarray experiments were performed in duplicate using RNA obtained from independent experiments, for each subset of cells. Expression profiling confirmed the role of several genes involved in hematopoiesis, and identified several putative genes involved in endothelial differentiation.The isolation of CD144+ cells during ES cell differentiation from embryoid bodies provides an excellent model system and method for identifying genes that are expressed during endothelial differentiation and that are distinct from hematopoiesis.A close temporal and spatial association exists between the development of hematopoietic and endothelial stem cells during embryogenesis. This is first observed in extra-embryonic mesodermal tissues such as the yolk sac. Within the developing yolk sac primitive erythrocytes are surrounded by a layer of angioblasts [1,2]. The close temporal and spatial association of these two lineages led to the hypothesis that they arise from a common precursor of mesodermal origin known as the hemangioblast [3]. Further support fo
Bioinformatic identification and characterization of human endothelial cell-restricted genes
Manoj Bhasin, Lei Yuan, Derin B Keskin, Hasan H Otu, Towia A Libermann, Peter Oettgen
BMC Genomics , 2010, DOI: 10.1186/1471-2164-11-342
Abstract: Using a high throughput microarray platform, a primary set of 1,191 transcripts that are enriched in different primary ECs compared to non-ECs was identified (LCB >3, FDR <2%). Further refinement of this initial subset of transcripts, using published data, yielded 152 transcripts (representing 109 genes) with different degrees of EC-specificity. Several interesting patterns emerged among these genes: some were expressed in all ECs and several were restricted to microvascular ECs. Pathway analysis and gene ontology demonstrated that several of the identified genes are known to be involved in vasculature development, angiogenesis, and endothelial function (P < 0.01). These genes are enriched in cardiovascular diseases, hemorrhage and ischemia gene sets (P < 0.001). Most of the identified genes are ubiquitously expressed in many different tissues. Analysis of the proximal promoter revealed the enrichment of conserved binding sites for 26 different transcription factors and analysis of the untranslated regions suggests that a subset of the EC-restricted genes are targets of 15 microRNAs. While many of the identified genes are known for their regulatory role in ECs, we have also identified several novel EC-restricted genes, the function of which have yet to be fully defined.The study provides an initial catalogue of EC-restricted genes most of which are ubiquitously expressed in different endothelial cells.The endothelium, which lines the inner surface of all blood vessels, participates in several normal physiological functions including control of vasomotor tone, the maintenance of blood fluidity, regulation of permeability, formation of new blood vessels, and trafficking of cells [1]. The endothelium also plays an important role in several human diseases. In the setting of inflammation several genes become activated within the endothelium to facilitate the recruitment, attachment, and transmigration of inflammatory cells. Over time, however, in chronic inflammatory dis
Genomic Counter-Stress Changes Induced by the Relaxation Response
Jeffery A. Dusek, Hasan H. Otu, Ann L. Wohlhueter, Manoj Bhasin, Luiz F. Zerbini, Marie G. Joseph, Herbert Benson, Towia A. Libermann
PLOS ONE , 2008, DOI: 10.1371/journal.pone.0002576
Abstract: Background Mind-body practices that elicit the relaxation response (RR) have been used worldwide for millennia to prevent and treat disease. The RR is characterized by decreased oxygen consumption, increased exhaled nitric oxide, and reduced psychological distress. It is believed to be the counterpart of the stress response that exhibits a distinct pattern of physiology and transcriptional profile. We hypothesized that RR elicitation results in characteristic gene expression changes that can be used to measure physiological responses elicited by the RR in an unbiased fashion. Methods/Principal Findings We assessed whole blood transcriptional profiles in 19 healthy, long-term practitioners of daily RR practice (group M), 19 healthy controls (group N1), and 20 N1 individuals who completed 8 weeks of RR training (group N2). 2209 genes were differentially expressed in group M relative to group N1 (p<0.05) and 1561 genes in group N2 compared to group N1 (p<0.05). Importantly, 433 (p<10?10) of 2209 and 1561 differentially expressed genes were shared among long-term (M) and short-term practitioners (N2). Gene ontology and gene set enrichment analyses revealed significant alterations in cellular metabolism, oxidative phosphorylation, generation of reactive oxygen species and response to oxidative stress in long-term and short-term practitioners of daily RR practice that may counteract cellular damage related to chronic psychological stress. A significant number of genes and pathways were confirmed in an independent validation set containing 5 N1 controls, 5 N2 short-term and 6 M long-term practitioners. Conclusions/Significance This study provides the first compelling evidence that the RR elicits specific gene expression changes in short-term and long-term practitioners. Our results suggest consistent and constitutive changes in gene expression resulting from RR may relate to long term physiological effects. Our study may stimulate new investigations into applying transcriptional profiling for accurately measuring RR and stress related responses in multiple disease settings.
Fast Handoff for 802.11 Wireless Network  [PDF]
Obay H. Sabrie, Hasan S. Hasan, Rosli Salleh
Communications and Network (CN) , 2011, DOI: 10.4236/cn.2011.34029
Abstract: Whenever the mobile station moves from the range of one access point and comes to the range of another access point a handoff process is occurred. This process takes a long time when using the IEEE 802.11 standard handoff and this delay affect the real time and multimedia applications. This paper provides a layer 2 handoff process for the IEEE 802.11 that is able to eliminate the scanning delay and reduce the total handoff delay.
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