In-silico-Systemanalyse von Biopathways

Chen M. In silico systems analysis of biopathways. Bielefeld (Germany): Bielefeld University; 2004.In the past decade with the advent of high-throughput technologies, biology has migrated from a descriptive science to a predictive one. A vast amount of information on the metabolism have been produced; a number of specific genetic/metabolic databases and computational systems have been developed, which makes it possible for biologists to perform in silico analysis of metabolism. With experimental data from laboratory, biologists wish to systematically conduct their analysis with an easy-to-use computational system. One major task is to implement molecular information systems that will allow to integrate different molecular database systems, and to design analysis tools (e.g. simulators of complex metabolic reactions). Three key problems are involved: 1) Modeling and simulation of biological processes; 2) Reconstruction of metabolic pathways, leading to predictions about the integrated function of the network; and 3) Comparison of metabolism, providing an important way to reveal the functional relationship between a set of metabolic pathways. This dissertation addresses these problems of in silico systems analysis of biopathways. We developed a software system to integrate the access to different databases, and exploited the Petri net methodology to model and simulate metabolic networks in cells. It develops a computer modeling and simulation technique based on Petri net methodology; investigates metabolic networks at a system level; proposes a markup language for biological data interchange among diverse biological simulators and Petri net tools; establishes a web-based information retrieval system for metabolic pathway prediction; presents an algorithm for metabolic pathway alignment; recommends a nomenclature of cellular signal transduction; and attempts to standardize the representation of biological pathways. Hybrid Petri net methodology is exploited to model metabolic networks. Kinetic modeling strategy and Petri net modeling algorithm are applied to perform the processes of elements functioning and model analysis. The proposed methodology can be used for all other metabolic networks or the virtual cell metabolism. Moreover, perspectives of Petri net modeling and simulation of metabolic networks are outlined. A proposal for the Biology Petri Net Markup Language (BioPNML) is presented. The concepts and terminology of the interchange format, as well as its syntax (which is based on XML) are introduced. BioPNML is designed to provide a starting point for the development of a standard interchange format for Bioinformatics and Petri nets. The language makes it possible to exchange biology Petri net diagrams between all supported hardware platforms and versions. It is also designed to associate Petri net models and other known metabolic simulators. A web-based metabolic information retrieval system, PathAligner, is developed in order to predict metabolic pathways from rudimentary elements of pathways. It extracts metabolic information from biological databases via the Internet, and builds metabolic pathways with data sources of genes, sequences, enzymes, metabolites, etc. The system also provides a navigation platform to investigate metabolic related information, and transforms the output data into XML files for further modeling and simulation of the reconstructed pathway. An alignment algorithm to compare the similarity between metabolic pathways is presented. A new definition of the metabolic pathway is proposed. The pathway defined as a linear event sequence is practical for our alignment algorithm. The algorithm is based on strip scoring the similarity of 4-hierarchical EC numbers involved in the pathways. The algorithm described has been implemented and is in current use in the context of the PathAligner system. Furthermore, new methods for the classification and nomenclature of cellular signal transductions are recommended. For each type of characterized signal transduction, a unique ST number is provided. The Signal Transduction Classification Database (STCDB), based on the proposed classification and nomenclature, has been established. By merging the ST numbers with EC numbers, alignments of biopathways are possible. Finally, a detailed model of urea cycle that includes gene regulatory networks, metabolic pathways and signal transduction is demonstrated by using our approaches. A system biological interpretation of the observed behavior of the urea cycle and its related transcriptomics information is proposed to provide new insights for metabolic engineering and medical care

Application of heuristic methods in finding patterns common to groups of biological sequences.

Master'sMASTER OF ENGINEERIN

Basic Research in Endocrinology

The first all-Russia conference with international participation “Basic Research in Endocrinology: A Modern Strategy for the Development and Technologies of Personalized Medicine” was held in Novosibirsk on 26–27 November 2020. The purpose of this conference was to disseminate the latest basic and clinical findings in the fields of etiology, clinical characteristics, and modern diagnostics and treatments of endocrine disorders among various relevant specialists. The conference was intended for practicing endocrinologists, primary care physicians, medical geneticists, pediatric endocrinologists, pediatricians, and physician–scientists. The main topics included epidemiology and pathogenesis of endocrine disorders; genomic research in endocrinology; biochemical characteristics of endocrine aberrations; immunology and immunogenetics in endocrinology; cellular technologies in endocrinology; metabolomic research in endocrinology; pharmacogenetics; basic pathomorphology; high-tech care of patients with endocrine disorders; iodine-deficiency-related, autoimmune, and oncological diseases of the thyroid; modern diagnostic and therapeutic strategies for diabetes mellitus; osteoporosis and osteopenias; polyendocrinopathies; an interdisciplinary approach to the diagnosis and treatment of obesity and metabolic syndrome; hypo- and hyperparathyroidism, vitamin D; neuroendocrine disorders; reproductive health; rehabilitation of patients with endocrine disorders; health resort and spa treatments of endocrine disorders and comorbid conditions

Prevention strategy of tuberculosis among HIV positive adolescents in Hawassa town, Southern Ethiopia

The study aimed at identifying the determinants of tuberculosis infection among human immunodeficiency virus (HIV) positive adolescents and subsequently develop a prevention strategy for tuberculosis (TB) among HIV positive adolescents in Hawassa town, Ethiopia. The study was conducted from 10 September 2021 to 28 February 2022 in Hawassa town, which is located in the southern part of Ethiopia. The study adopted a sequential exploratory mixed methods study design. A qualitative study was conducted in the first phase, followed by a quantitative study in the second phase. Data for the qualitative phase was collected through face-to-face interviews as well as focus group discussions using an interview guide. Data was collected from adolescents who were diagnosed with TB/HIV or only HIV and treated in chronic care centres, and their guardians. Qualitative data was further collected from key informants who were public officials and focal persons for the TB/HIV prevention/control programme in their institutions. The quantitative data was collected through a structured questionnaire from 321 TB/HIV patients of whom 107 were cases and 214 were controls from four conveniently selected health facilities in Hawassa. Qualitative data was analysed thematically and manually, while quantitative data was analysed using SPSS version 26 and Epi Info version 7.2.5. The study revealed a consistent increase of tuberculosis infection among the adolescents living with HIV owing to failure of good governance and leadership; deterioration of school health services; critical budget shortages; and poor motivation of health professionals. Factors that were found to be independently associated with tuberculosis infection were taking isoniazid preventive therapy (IPT) AOR=0.09, 95% CI (0.01, 0.69) which shows that IPT has a preventive effect against tuberculosis; WHO clinical stages III and IV AOR= 3.64, 95% CI (2.95, 4.49); previous history of tuberculosis AOR=222.18, 95% CI (127.06, 389.59) and history of smoking AOR=112.4, 95%CI (146.83, 940.15). The study concluded that all stakeholders must work together to improve the execution of services for TB/HIV prevention. The contribution of this study is the development of an alternative integrated TB/HIV preventive strategy, which would promote TB/HIV prevention for better health outcomes.Health StudiesPh. D. (Public Health