113 research outputs found
On Eschatological Problematics in the works of Kyrylo Tranquillon Stavrovetsky
No full textУ статті представлено деякі аспекти богословської думки Кирила Транквіліона Ставровецького, які стосуються остаточного призначення людини й усього сотвореного. На підставі аналізу текстів усіх трьох книг Ставровецького зроблено спробу показати основні есхатологічні поняття і концепти, якими він оперував, а також приклади їхнього використання в душпастирській практиці його доби. Після перегляду основних есхатологічних топосів Кирилової есхатології розглянуто
есхатологічну проблематику в контексті рецепції та критики творів Кирила Ставровецького.The article presents some aspects of theological thought of Kyrylo Tranquillon Stavrovetsky that pertain to the final purpose of man and all the creation. Pivoting on the analysis of all three Stavrovetsky’s books, the author of this article tried to present the main notions and eschatological concepts applied by Kyrylo, as well as examples of their use in pastoral practice of his days. Aft er examining the major eschatological topoi of Kyrylo’s eschatology, eschatological issues are discussed in the context of the reception and critique of Kyrylo Stavrovetsky’s works
To the problem of Ioann Zolotoust's writing as a sourse of "Word on limp man" by Kyrylo Turovskyi
No full textУ статті порівнюються два схожі твори Иоанна Золотоустого й Кирила Туровського. Авторка
намагається довести, що давньоруський письменник створив оригінальну інтерпретацію
візантійського джерела.The article compares two similar texts by Іoann Zolotoust and Kyrylo Turovskyi. The author is trying
to prove that the Old Rus s writer made an original interpretation of the Byzantine sourse
A comparative Genome-Wide Association Interaction study using BOOST and MB-MDR algorithms on Ankylosing Spondylitis
No full textGenome-Wide Association (GWA) studies have gained popularity after the completion of the Human Genome Project and advancement of high-throughput technologies. These studies aim to scan thousands of genomic variations (e.g., SNPs) for their association to phenotypic variables (i.e. traits), such as disease related phenotypes, with the hope of extracting biologically and clinically relevant information. Understanding of genetic, environmental as well as other components of the disease brings the key insights into disease pathology and approaches us closer to the ultimate goal - personalized medicine.
In this work we rely on a minimal GWAI protocol for genome-wide epistasis detection using SNPs, as developed in our lab [6][9]. Using the advanced non-parametric Model-Based Multifactor Dimensionality Reduction (MB-MDR) method [1] and BOolean Operation-based Screening and Testing (BOOST) algorithms [4][*] for detection of statistically significant epistatic SNP-SNP interactions, we investigate the effect of exhaustive (BOOST) and non-exhaustive (MB-MDR) marker processing strategies, LD effects, as well as different adjustment schemes for lower-order effects (i.e. epistasis).
Our approach was tested on Ankylosing Spondylitis (AS) data as provided by the WTCCC2 consortium [1]. AS is a long-term / chronic disease characterized by inflammation of the joints between the spinal bones. Non-steroidal anti-inflammatory drugs calming down the immune system inflammatory responses are used as a treatment but there is no permanent cure for AS. The disease has also a strong environmental component and affects 3.5 - 13 per 1,000 people in USA [5
Identification of asthma-related trans-acting epistatic eQTLs using Model-Based Multifactor Dimensionality Reduction (MB-MDR)
No full textEpistasis is likely to underlie most complex traits, including gene expression, yet it is very difficult to detect using standard approaches. SNPs located inside a gene coding region or in its vicinity (i.e. ≤2 Mb from each 5’ and 3’ side) can influence the corresponding gene expression levels. These expression quantitative trait loci (eQTLs) are referred to as cisSNPs. In contrast, eQTLs that are outside the aforementioned gene range can also influence the gene’s expression, in which case, they are called transSNPS to that gene. In this study we considered significant cisSNPs previously identified via generalized least squares (GLS) regression modeling. We then identified those genes transcripts whose expression is regulated by cis/transSNP interaction. In this work we aimed at identifying transcripts whose expression is regulated by a cis/transSNP interactions using Model-Based Multifactor Dimensionality Reduction (MB-MDR) [2]. This model-free approach to detect trans-epistasis involves reducing a high-dimensional GxG space to GxG factor levels that either exhibit high evidence, low evidence or no evidence at all for their association to gene expression levels of interest.
Our protocol was applied on real-life data from the childhood asthma management program (CAMP) [1]. It involved coupling a traditional a priori eQTL search to an a posteriori trans-epistasis analysis to identify genetic modifiers to statistically significant cisSNPs. Such an approach allows to reveal previously unreported inter-dependencies that may be important in understanding of biological mechanisms underlying human complex diseases such as asthma.
The proposed protocol identified a large number trans-epistasis gene-gene effects of eQTLs
In silico study of the interaction of the Myelin Basic Protein C-terminal a-helical peptide with DMPC and mixed DMPC/DMPE lipid bilayers
No full textBiological membranes continue to be extensively investigated in different ways. This paper presents the benefits of Molecular Dynamics (MD) approaches to study the properties of biological membranes and proteins using the freely available GROMACS package, in the context of the Myelin Basic Protein (MBP) C-terminal a-helical peptide. A mixed membrane consisting of 2-Dimyristoyl-sn-Glycero-3-phosphocholine/1,2-Dimyristoyl-sn-Glycero-3- phosphoethanolamine (DMPC/DMPE), and pure DMPC membranes, composed of 188 and 248 lipids, respectively, were simulated for 200 ns at 309 K. The DMPC membrane was approximately three times more fluid compared to the DMPC/DMPE system, with the diffusion coefficients (D) being 0.0207x10-5 cm2/s and 0.0068x10-5 cm2/s, respectively. In addition, the 14-residue peptide representing the C-terminal a-helical region of murine Myelin Basic Protein (MBP), with amino acid sequence NH2-A141YDAQGTLSKIFKL154-COOH , was simulated in both membrane systems for 200 ns. The peptide penetrated further into the DMPC bilayer compared to the mixed DMPC/DMPE bilayer, potentially because of the reduced accessibility of the charged peptide amino acid side chains to the formal positive charge of the amine N atom surrounded by methyl and methylene groups in DMPC, that might have resulted in greater overall peptide mobility [3]. These findings are significant in their implication that membrane composition affects the behavior of MBP, providing further insights into myelin structure. Our preliminary results suggest that local changes in membrane composition (e.g. enrichment in DMPE molecules), as well as, electrostatic nature of primary amino acid sequence could cause localized denaturation / instability of external MBP a-helices possibly augmenting the degradation of myelin in multiple sclerosis (MS), resulting in a subsequent decrease of nerve impulse propagation efficiency
On collaboration and competition in scientific community
No full textCompetition in sciences is increasing today to the levels that it becomes damaging to the scientific progress. In this talk we will talk about benefits of collaboration of healthy competition. Will also concentrate on negative aspects of competition and will provide detailed examples illustrating each of the negative points of stiff competition. In addition historical outlook of the scientific community organization and formalization of science will be briefly touched upon in the tal
Functional Characterization of the NSF1 (YPL230W) Gene using Correlation Clustering and Genetic Analysis in Saccharomyces Cerevisiae
No full textThe pdf file contains numerous hyperlinks and bookmarks to facilitate navigation. This thesis will be of interest to those working with topics such as data mining of microarray data, novel gene function discovery and prediction, and genome-wide responses to fermentation stresses.High throughput technologies such as microarrays and modern genome sequencers produce enormous amounts of data that require novel data processing. This thesis proposes a method called Interdependent Correlation Cluster (ICC) to analyze the relations between genes represented by microarray data that are conditioned on a specific target gene. Based on Correlation Clustering, the proposed method analyzes a large set of correlation values related to the gene expression profiles extracted from given microarray datasets. The proposed method works on any size microarray datasets and could be applied to any target gene. In this study the selected target gene, NSF1 /USV1 / YPL230W, encodes a poorly characterized C2H2 zinc finger transcription factor (TF) involved in stress responses in yeast. The method is successful in the identification of novel NSF1 functional roles during fermentation stress conditions in the M2 industrial yeast strain. The new identified functions include regulation of energy and sulfur metabolism, protein synthesis, ribosomal assembly and protein trafficking as well as other processes. NSF1 involvement in sulfur metabolism was experimentally confirmed using biological laboratory techniques. Importantly, implication of NSF1 in sulfur metabolism regulation has highly relevant implications to wine and beer production industries concerned with production of compounds having sulfur-like off odour (SLO) and toxic properties. The correlation clustering also provides a means of understanding complex interactions existing between genes.Ontario Ministry of Training, Colleges and UniversitiesOntario Graduate ScholarshipOntario Graduate Scholarship in Science and TechnologyNatural Sciences and Engineering Research Council of Canad
The effects of threonine phosphorylation on the stability and dynamics of the central molecular switch region of 18.5-kDa myelin basic protein.
No full textThe classic isoforms of myelin basic protein (MBP) are essential for the formation and maintenance of myelin in the central nervous system of higher vertebrates. The protein is involved in all facets of the development, compaction, and stabilization of the multilamellar myelin sheath, and also interacts with cytoskeletal and signaling proteins. The predominant 18.5-kDa isoform of MBP is an intrinsically-disordered protein that is a candidate auto-antigen in the human demyelinating disease multiple sclerosis. A highly-conserved central segment within classic MBP consists of a proline-rich region (murine 18.5-kDa sequence -T92-P93-R94-T95-P96-P97-P98-S99-) containing a putative SH3-ligand, adjacent to a region that forms an amphipathic α-helix (P82-I90) upon interaction with membranes, or under membrane-mimetic conditions. The T92 and T95 residues within the proline-rich region can be post-translationally modified through phosphorylation by mitogen-activated protein (MAP) kinases. Here, we have investigated the structure of the α-helical and proline-rich regions in dilute aqueous buffer, and have evaluated the effects of phosphorylation at T92 and T95 on the stability and dynamics of the α-helical region, by utilizing four 36-residue peptides (S72-S107) with differing phosphorylation status. Nuclear magnetic resonance spectroscopy reveals that both the α-helical as well as the proline-rich regions are disordered in aqueous buffer, whereas they are both structured in a lipid environment (cf., Ahmed et al., Biochemistry 51, 7475-9487, 2012). Thermodynamic analysis of trifluoroethanol-titration curves monitored by circular dichroism spectroscopy reveals that phosphorylation, especially at residue T92, impedes formation of the amphipathic α-helix. This conclusion is supported by molecular dynamics simulations, which further illustrate that phosphorylation reduces the folding reversibility of the α-helix upon temperature perturbation and affect the global structure of the peptides through altered electrostatic interactions. The results support the hypothesis that the central conserved segment of MBP constitutes a molecular switch in which the conformation and/or intermolecular interactions are mediated by phosphorylation/dephosphorylation at T92 and T95
Gene Regulatory Network Inference via Conditional Inference Trees and Forests
No full textTrees are classical data structures allowing effectively classifying and predicting responses. Due to versatility and high performance in classification and prediction, there exist plenty of tree-based methods including popular Conditional Inference Tree (CIT) and Forests (CIF), Random Forests (RF), Randomized Trees (RT), randomized C4.5, etc. In this work we assessed the performance of CIT and CIF methods in correct gene regulatory network (GRN) prediction from expression data by using reference golden standard built from real transcriptional regulatory network of E. coli. The synthetic microarray expression data was obtained from DREAM4 challenge. The performance of each network inference method was assessed via Area Under Receiver Operating Characteristic (AUROC) and Area Under Precision Recall (AUPR) metrics.
Our preliminary results show that CIT and CIF successfully predict directed GRNs at acceptable performance rates although not optimal (the best AUROC at 0.68 and AUPR at 0.13 for CIF and the best AUROC at 0.58 and AUPR at 0.18 for CIT). Surprisingly by using the current aggregation scheme of feature importance that prefers features with the highest number of observations, a single CIT was a better performer compared to CIFs in all 5 networks. Nevertheless, the CIFs showed an overall 10% improvement in AUROC. A single CIT has 24% and CIFs have 27% lower overall performance compared to the best performer of DREAM4 Challenge based on cumulative areas of PR and ROC curves.
We plan to test other feature importance aggregation techniques in a single tree and in tree ensembles in order to outperform the top DREAM4 algorithms. In addition the effects of expression data standardization to unit variance will be presented. In future, the developed CIF framework will be used to perform data integration analysis of multi-omics datasets
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