Number Of Biological Databases Research Articles

IMPLICATION OF NANOPORE SEQUENCING TECHNOLOGY FOR PATHOGENIC DIAGNOSTICS: A MINI-REVIEW

DNA sequencing is the most critical technique to explore and study genomic data of human beings and surrounding environments. The history of DNA sequencing has rapidly grown since the first-generation DNA sequencing in 1977. Until now, emerging high-throughput sequencing technology has recently revolutionized omics areas, including genomics, transcriptomics, metagenomics, and metabolomics for the development of modern molecular biology. Besides the short-read sequencing method (Illumina platforms), the long-read sequencing technologies (including Pacific Biosciences and Oxford Nanopore Technologies) have been developed with the advantages of larger read sizes, portable devices, and diverse preparation kits. Consequently, the number of biological databases and study-related nanopore sequencing technologies has grown fast. This review paper summarized the principle and fundament of nanopore sequencing regarding their advanced applications in pathogenic diagnostics of different hosts. The most recent application of nanopore sequencing in the diagnostics of infectious diseases is highlighted and discussed to provide insights into the novelty of nanopore sequencing technology and its future perspectives.

DBHR: a collection of databases relevant to human research.

Background:The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive growth of biological data, a growing number of biological databases are being established to support human-related research.Objective:The main objective of our study is to store, organize and share data in a structured and searchable manner. In short, we have planned the future development of new features in the database research area.Materials & methods:In total, we collected and integrated 680 human databases from scientific published work. Multiple options are presented for accessing the data, while original links and short descriptions are also presented for each database.Results & discussion:We have provided the latest collection of human research databases on a single platform with six categories: DNA database, RNA database, protein database, expression database, pathway database and disease database.Conclusion:Taken together, our database will be useful for further human research study and will be modified over time. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://habdsk.org/database.php.

BioCarian: search engine for exploratory searches in heterogeneous biological databases

BackgroundThere are a large number of biological databases publicly available for scientists in the web. Also, there are many private databases generated in the course of research projects. These databases are in a wide variety of formats. Web standards have evolved in the recent times and semantic web technologies are now available to interconnect diverse and heterogeneous sources of data. Therefore, integration and querying of biological databases can be facilitated by techniques used in semantic web. Heterogeneous databases can be converted into Resource Description Format (RDF) and queried using SPARQL language. Searching for exact queries in these databases is trivial. However, exploratory searches need customized solutions, especially when multiple databases are involved. This process is cumbersome and time consuming for those without a sufficient background in computer science. In this context, a search engine facilitating exploratory searches of databases would be of great help to the scientific community.ResultsWe present BioCarian, an efficient and user-friendly search engine for performing exploratory searches on biological databases. The search engine is an interface for SPARQL queries over RDF databases. We note that many of the databases can be converted to tabular form. We first convert the tabular databases to RDF. The search engine provides a graphical interface based on facets to explore the converted databases. The facet interface is more advanced than conventional facets. It allows complex queries to be constructed, and have additional features like ranking of facet values based on several criteria, visually indicating the relevance of a facet value and presenting the most important facet values when a large number of choices are available. For the advanced users, SPARQL queries can be run directly on the databases. Using this feature, users will be able to incorporate federated searches of SPARQL endpoints. We used the search engine to do an exploratory search on previously published viral integration data and were able to deduce the main conclusions of the original publication. BioCarian is accessible via http://www.biocarian.com.ConclusionsWe have developed a search engine to explore RDF databases that can be used by both novice and advanced users.

Array2GO: a simple web-based tool to search gene ontology for analysis of multi genes expression

As a result of population and universality in high-throughput omics technologies in the last decade, such as microarray methods, many researchers who study their genes of interest that are similarly or differently expressed in cellular states, diseases, functional, or environmental element conditions have been possessed of the ability to identify biological validation on the genomic scale. In parallel with the advancement of omics experiments, the number of biological databases, which contain the biological annotations, genetic functionalities, metabolic pathways, and mutational information or functional interactions between genes or proteins, has increased. Fortunately, these datasets have been mainly opened to computational network protocols, such as FTP or SSH, and have freely served as web search tools to enable users to retrieve a biological annotation with queries. Of these databases, GO (Gene Ontology) provides controlled vocabulary terms for describing biological annotation of a gene or gene product in tree aspects that are classified as biological process, cellular component, and molecular function across various species. Also, GO gives researchers a publicly accessible tool for identification of a gene or gene product with GO terms. The result of this tool displays the hierarchical tree-type html format or DAGs (Directed Acyclic Graphs) graphtype format to users according to the three aspects of GO. However, as this permits users to ask only one keyword at a time, it is difficult to search many interesting gene sets in gene expression profiles obtained from microarray experiments at once. A few GO search tools have been developed to help in analysis of GO annotation for multi genes. However they have not satisfied user demands in terms of the simplicity of the user interface and visualization of analysis results. For these reasons, Array2GO, which has been based on a web environment, has been developed and is freely accessible at http://www.koreagene.co.kr/cgi-bin/service/service1.pl.

A Distributed-Processing System for Accelerating Biological Research Using Data-Staging

The number of biological databases has been increasing rapidly as a result of progress in biotechnology. As the amount and heterogeneity of biological data increase, it becomes more difficult to manage the data in a few centralized databases. Moreover, the number of sites storing these databases is getting larger, and the geographic distribution of these databases has become wider. In addition, biological research tends to require a large amount of computational resources, i.e., a large number of computing nodes. As such, the computational demand has been increasing with the rapid progress of biological research. Thus, the development of methods that enable computing nodes to use such widely-distributed database sites effectively is desired. In this paper, we propose a method for providing data from the database sites to computing nodes. Since it is difficult to decide which program runs on a node and which data are requested as their inputs in advance, we have introduced the notion of “data-staging” in the proposed method. Data-staging dynamically searches for the input data from the database sites and transfers the input data to the node where the program runs. We have developed a prototype system with data-staging using grid middleware. The effectiveness of the prototype system is demonstrated by measurement of the execution time of similarity search of several-hundred gene sequences against 527 prokaryotic genome data.

Access to DNA and protein databases on the internet

During the past year, the number of biological databases that can be queried via Internet has dramatically increased. This increase has resulted from the introduction of networking tools, such as Gopher and WAIS, that make it easy for research workers to index databases and make them available for on-line browsing. Biocomputing in the nineties will see the advent of more client/server options for the solution of problems in bioinformatics.