The implementation of e-learning tools to enhance undergraduate bioinformatics teaching and learning: a case study in the National University of Singapore

BMC Bioinformatics10SUPPL. 15BBMI

Proteomics Databases and Websites

Information avalanche (overload or expansion) in various scientific fields is a novel issue turned out by a number of factors considered necessary to facilitate their record and registration. Though, the biological science and its diverse fields like proteomics are not immune of this event and even may be as the event’s herald. On the other hand, time as the most valued anxiety of human has encountered a huge mass of information. Therefore, in order to maintain access and ease the understanding of information in several fields some emprises have been prepared. Bioinformatics is an upshot of this anxiety and emprise. Interestingly, proteomics through studying proteins collection in alive things has covered a great portion of bioinformatics. Consequently, a noteworthy outlook on proteomics related databases (DBs) and websites not only can help investigators to face the upcoming archive of databases but also estimate the volume of the needed facilitates. Furthermore, enrichment of the DBs or related websites must be the priority of researchers. Herein, by covering the major proteomics related databases and websites, we have presented a comprehensive classification to simplify and clarify their understanding and applications

GCell A Sub-Cellular Localization Tool

Submitted to the faculty of the University Graduate School In partial fulfillment of the requirements For the degree Master of Sciences In the School of Informatics, Indiana University August, 2005The aim of this thesis is to develop a biological database mining tool that incorporates mining of various publicly available heterogeneous databases and provides researchers with a reporting and visualization tool for sub-cellular localization of genes and proteins. Although there is little conservation of the primary structure, the general physiochemical properties are conserved to some extent among proteins that share sub-cellular location. Hence, the function of a protein is closely correlated with its sub-cellular location. Data in the field of genomics and proteomics are detailed, complex, and voluminous and distributed in heterogeneous databases. Most of the earlier work in information extraction from biological databases focused on database integration using wrapper techniques. However, little work has been done to mine specific data leading to the identification of pathway information and evolutionary relationship from heterogeneous biological databases. The need to develop an interactive information visualization tool leading to biological pathway detection for genes by using controlled vocabulary and various publicly available biological databases has led to the concept and implementation of GCell. This system provides a researcher to move from raw text data at a broader level to a much more detailed view of pathways representing complex biological interactions

Phylogenomics of vertebrate serpins

Kumar A. Phylogenomics of vertebrate serpins. Bielefeld (Germany): Bielefeld University; 2010.The serpins constitute a superfamily of proteins that fold into a conserved tertiary structure and employ a sophisticated, irreversible suicide-mechanism of inhibition. More than 6000 serpins have been identified, occurring in all three forms of the life - the eukaryotes, the prokaryotes and the archea. Vertebrate serpins can be conveniently classified into six groups (V1 - V6), based on three independent biological features - gene organization, diagnostic amino acid sites and rare indels. In the present work, the phylogenetic relationships of serpins from Nematostella vectensis, Strongylocentrotus purpuratus, Ciona intestinalis, four fish species, frog, chicken and mammals were investigated, using gene architecture analyses and stringent criteria for identification of orthologs. With some deviations, all vertebrate serpin genes fit into one of the six exon/intron gene classes previously identified, dating the existence and maintenance of these gene organizations before or close to the divergence of fishes. Group V1 and V2 gene families underwent rapid adaptive radiation along the lineages leading to mammals as indicated by an up to nine-fold increased number of family members, accompanied by a rapid functional diversification. In contrast, gene groups V3 to V6 display a rather conservative evolution with little changes since the divergence of fishes and the other vertebrates. The orthology assessment indicates that all vertebrates are equipped with a subset of strongly conserved serpins with functions that can be clearly correlated with basic vertebrate-specific physiology. None of serpin genes from C. intestinalis shares a common exon-intron architecture organisation with any of the vertebrate serpin gene classes, nor was it possible to identify orthologs of vertebrates. The lack of gene architecture similarity and the complete absence of orthology between urochordate and vertebrate serpins indicate that major changes with bursts of character acquisition must have occurred during evolution of serpins in the time interval separating urochordates from chordates, indicating massive intron gains or losses and events providing C and N-terminal sequence extensions characteristic for today's vertebrate serpins. Lancelets and sea urchin genomes, in contrast, share one orthologous serpin with vertebrates. Rare genomic characters are used to show that orthologs of neuroserpin, a prominent representative of vertebrate group V3 serpin genes, exist in early diverging deuterostomes and probably also in cnidarians, indicating that the origin of a mammalian serpin can be traced back far in the history of eumetazoans. A C-terminal address code assigning association with secretory pathway organelles is present in all neuroserpin orthologs, suggesting that supervision of cellular export/import routes by antiproteolytic serpins is an ancient trait. Phylogenomic comparisons show that, after establishment of canonical exon-intron patterns in the serpin superfamily at the dawn of vertebrate evolution, multiple intron acquisition events have occurred during diversification of a lineage of actinopterygian fishes. The novel introns were acquired within a limited time interval (on an evolutionary timescale), and no such events were observed in other groups of vertebrates. Examination of the sequences flanking the intron insertion points revealed that the genetic requirements for acquisition of novel introns might be less stringent than previously suggested. Finally, we argue that genome compaction, a phenomenon associated with the fish lineage depicting preferential intron gain, might promote intron acquisition

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

Evolution of the Modern ODE Course

The rapid development of technology in the latter part of the twentieth century has revolutionized the teaching of differential equations. In this paper we will try to trace the evolution of this important change. We tried to include the most important efforts in this regard, but we apologize in advance if some efforts have slipped our attention

NFDI4Microbiota – national research data infrastructure for microbiota research

Microbes – bacteria, archaea, unicellular eukaryotes, and viruses – play an important role in human and environmental health. Growing awareness of this fact has led to a huge increase in microbiological research and applications in a variety of fields. Driven by technological advances that allow high-throughput molecular characterization of microbial species and communities, microbiological research now offers unparalleled opportunities to address current and emerging needs. As well as helping to address global health threats such as antimicrobial resistance and viral pandemics, it also has a key role to play in areas such as agriculture, waste management, water treatment, ecosystems remediation, and the diagnosis, treatment and prevention of various diseases. Reflecting this broad potential, billions of euros have been invested in microbiota research programs worldwide. Though run independently, many of these projects are closely related. However, Germany currently has no infrastructure to connect such projects or even compare their results. Thus, the potential synergy of data and expertise is being squandered. The goal of the NFDI4Microbiota consortium is to serve and connect this broad and heterogeneous research community by elevating the availability and quality of research results through dedicated training, and by facilitating the generation, management, interpretation, sharing, and reuse of microbial data. In doing so, we will also foster interdisciplinary interactions between researchers. NFDI4Microbiota will achieve this by creating a German microbial research network through training and community-building activities, and by creating a cloud-based system that will make the storage, integration and analysis of microbial data, especially omics data, consistent, reproducible, and accessible across all areas of life sciences. In addition to increasing the quality of microbial research in Germany, our training program will support widespread and proper usage of these services. Through this dual emphasis on education and services, NFDI4Microbiota will ensure that microbial research in Germany is synergistic and efficient, and thus excellent. By creating a central resource for German microbial research, NDFDI4Microbiota will establish a connecting hub for all NFDI consortia that work with microbiological data, including GHGA, NFDI4Biodiversity, NFDI4Agri and several others. NFDI4Microbiota will provide non-microbial specialists from these consortia with direct and easy access to the necessary expertise and infrastructure in microbial research in order to facilitate their daily work and enhance their research. The links forged through NFDI4Microbiota will not only increase the synergy between NFDI consortia, but also elevate the overall quality and relevance of microbial research in Germany