Phyloinformatics in the age of Wikipedia

This talk describes a mapping between the NCBI taxonomy database and Wikipedia. These two databases were chosen because the NCBI taxonomy contains all the taxa for which sequences are publicly available, and for many taxa Wikipedia is the first site returned in a Google search on that taxon's scientific name. The NCBI web pages for nearly 53,000 NCBI taxa now have a link to the corresponding page in Wikipedia

A fast Peptide Match service for UniProt Knowledgebase

Summary: We have developed a new web application for peptide matching using Apache Lucene-based search engine. The Peptide Match service is designed to quickly retrieve all occurrences of a given query peptide from UniProt Knowledgebase (UniProtKB) with isoforms. The matched proteins are shown in summary tables with rich annotations, including matched sequence region(s) and links to corresponding proteins in a number of proteomic/peptide spectral databases. The results are grouped by taxonomy and can be browsed by organism, taxonomic group or taxonomy tree. The service supports queries where isobaric leucine and isoleucine are treated equivalent, and an option for searching UniRef100 representative sequences, as well as dynamic queries to major proteomic databases. In addition to the web interface, we also provide RESTful web services. The underlying data are updated every 4 weeks in accordance with the UniProt releases. Availability: http://proteininformationresource.org/peptide.shtml Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Surfacing the deep data of taxonomy

Taxonomic databases are perpetuating approaches to citing literature that may have been appropriate before the Internet, often being little more than digitised 5 × 3 index cards. Typically the original taxonomic literature is either not cited, or is represented in the form of a (typically abbreviated) text string. Hence much of the “deep data” of taxonomy, such as the original descriptions, revisions, and nomenclatural actions are largely hidden from all but the most resourceful users. At the same time there are burgeoning efforts to digitise the scientific literature, and much of this newly available content has been assigned globally unique identifiers such as Digital Object Identifiers (DOIs), which are also the identifier of choice for most modern publications. This represents an opportunity for taxonomic databases to engage with digitisation efforts. Mapping the taxonomic literature on to globally unique identifiers can be time consuming, but need be done only once. Furthermore, if we reuse existing identifiers, rather than mint our own, we can start to build the links between the diverse data that are needed to support the kinds of inference which biodiversity informatics aspires to support. Until this practice becomes widespread, the taxonomic literature will remain balkanized, and much of the knowledge that it contains will linger in obscurity

Building the European Alien Species Information Network (EASIN): a novel approach for the exploration of distributed alien species data

The European Alien Species Information Network (EASIN; http://easin.jrc.ec.europa.eu) aims to facilitate the exploration of existing alien species information from distributed sources through a network of interoperable web services, and to assist the implementation of European policies on biological invasions. The network allows extraction of alien species information from online information systems for all species included in the EASIN catalogue. This catalogue was based on an inventory of reported alien species in Europe that was produced by reviewing and standardizing information from 43 online databases. It includes information on taxonomy, synonyms, common names, pathways of introduction, native range in Europe, and impact. EASIN catalogue entails the basic information needed to efficiently link to existing online databases and retrieve spatial information for alien species distribution in Europe. Using search functionality powered by a widget framework, it is possible to make a tailored selection of a subgroup of species based on various criteria (e.g., environment, taxonomy, pathways). Distribution maps of the selected species can be produced dynamically and downloaded by the user. The EASIN web tools and services follow internationally recognized standards and protocols, and can be utilized freely and independently by any website, while ownership of the data remains with its source, which is properly cited and linked.JRC.H.1-Water Resource

Biodiversity informatics: the challenge of linking data and the role of shared identifiers

A major challenge facing biodiversity informatics is integrating data stored in widely distributed databases. Initial efforts have relied on taxonomic names as the shared identifier linking records in different databases. However, taxonomic names have limitations as identifiers, being neither stable nor globally unique, and the pace of molecular taxonomic and phylogenetic research means that a lot of information in public sequence databases is not linked to formal taxonomic names. This review explores the use of other identifiers, such as specimen codes and GenBank accession numbers, to link otherwise disconnected facts in different databases. The structure of these links can also be exploited using the PageRank algorithm to rank the results of searches on biodiversity databases. The key to rich integration is a commitment to deploy and reuse globally unique, shared identifiers (such as DOIs and LSIDs), and the implementation of services that link those identifiers

EcomRISK.org : A site to classify and organize the risks of performing business on the Internet

As the use of the Internet and other computer networks to transact business grows, there is an ever increasing need for those taking part in those transactions to understand the risks of doing so. While there are many web sites that have created valuable databases of specific vulnerabilities for certain types of hardware and software, there is a lack of focus on attempting to analyze the interaction of businesses, their systems, computer networks, and their customers and the risks that are created by either intended or unattended interactions. EcomRISK.org is a web site that presents a clear taxonomy to classify these risks and provides other features to aid in the general discussion of e-commerce risk. The site, and the taxonomy at the center of it, creates a database of these incidents so they can be clearly searched. This paper discusses the creation of EcomRISK.org, from vision to birth

Wikipedia as an encyclopaedia of life

In his 2003 essay E O Wilson outlined his vision for an “encyclopaedia of life” comprising “an electronic page for each species of organism on Earth”, each page containing “the scientific name of the species, a pictorial or genomic presentation of the primary type specimen on which its name is based, and a summary of its diagnostic traits.” Although the “quiet revolution” in biodiversity informatics has generated numerous online resources, including some directly inspired by Wilson's essay (e.g., "http://ispecies.org":http://ispecies.org, "http://www.eol.org":http://www.eol.org), we are still some way from the goal of having available online all relevant information about a species, such as its taxonomy, evolutionary history, genomics, morphology, ecology, and behaviour. While the biodiversity community has been developing a plethora of databases, some with overlapping goals and duplicated content, Wikipedia has been slowly growing to the point where it now has over 100,000 pages on biological taxa. My goal in this essay is to explore the idea that, largely independent of the efforts of biodiversity informatics and well-funded international efforts, Wikipedia ("http://en.wikipedia.org/wiki/Main_Page":http://en.wikipedia.org/wiki/Main_Page) has emerged as potentially the best platform for fulfilling E O Wilson’s vision

The Human Oral Microbiome Database: a web accessible resource for investigating oral microbe taxonomic and genomic information

The human oral microbiome is the most studied human microflora, but 53% of the species have not yet been validly named and 35% remain uncultivated. The uncultivated taxa are known primarily from 16S rRNA sequence information. Sequence information tied solely to obscure isolate or clone numbers, and usually lacking accurate phylogenetic placement, is a major impediment to working with human oral microbiome data. The goal of creating the Human Oral Microbiome Database (HOMD) is to provide the scientific community with a body site-specific comprehensive database for the more than 600 prokaryote species that are present in the human oral cavity based on a curated 16S rRNA gene-based provisional naming scheme. Currently, two primary types of information are provided in HOMD—taxonomic and genomic. Named oral species and taxa identified from 16S rRNA gene sequence analysis of oral isolates and cloning studies were placed into defined 16S rRNA phylotypes and each given unique Human Oral Taxon (HOT) number. The HOT interlinks phenotypic, phylogenetic, genomic, clinical and bibliographic information for each taxon. A BLAST search tool is provided to match user 16S rRNA gene sequences to a curated, full length, 16S rRNA gene reference data set. For genomic analysis, HOMD provides comprehensive set of analysis tools and maintains frequently updated annotations for all the human oral microbial genomes that have been sequenced and publicly released. Oral bacterial genome sequences, determined as part of the Human Microbiome Project, are being added to the HOMD as they become available. We provide HOMD as a conceptual model for the presentation of microbiome data for other human body sites