Types Of Annotations Research Articles

The what, where, how and why of gene ontology--a primer for bioinformaticians

With high-throughput technologies providing vast amounts of data, it has become more important to provide systematic, quality annotations. The Gene Ontology (GO) project is the largest resource for cataloguing gene function. Nonetheless, its use is not yet ubiquitous and is still fraught with pitfalls. In this review, we provide a short primer to the GO for bioinformaticians. We summarize important aspects of the structure of the ontology, describe sources and types of functional annotations, survey measures of GO annotation similarity, review typical uses of GO and discuss other important considerations pertaining to the use of GO in bioinformatics applications.

OrthoNets: simultaneous visual analysis of orthologs and their interaction neighborhoods across different organisms

Motivation: Protein interaction networks contain a wealth of biological information, but their large size often hinders cross-organism comparisons. We present OrthoNets, a Cytoscape plugin that displays protein–protein interaction (PPI) networks from two organisms simultaneously, highlighting orthology relationships and aggregating several types of biomedical annotations. OrthoNets also allows PPI networks derived from experiments to be overlaid on networks extracted from public databases, supporting the identification and verification of new interactors. Any newly identified PPIs can be validated by checking whether their orthologs interact in another organism.Availability: OrthoNets is freely available at http://wodaklab.org/orthonets/.Contact: jim.vlasblom@utoronto.ca

A set of semantic norms for German and Italian

The psychological community frequently investigates semantic norms of properties produced by native speakers after being presented concept words, and these norms are of great value for a wide variety of psychological experiments. This paper presents a new set of norms that includes a collection of properties from a production experiment for the German and the Italian languages. Stimuli consisted of 50 concrete objects taken from 10 different concept classes. The data comprise annotations of semantic relation types and several statistical measures, which facilitate the comparison of the two target languages.

UniRule - Automatic Annotation In UniProtKB

AbstractThe UniProt KnowledgeBase (UniProtKB) provides a stable, comprehensive, freely accessible, centralized resource on protein sequences and functional annotation. UniProtKB consists of two sections: UniProtKB/SwissProt, a section containing records that are manually annotated with information extracted from the literature and curator-evaluated computational analysis, and UniProtKB/TrEMBL, a section containing computationally analysed records enriched with automatic annotation and classification.Automatic annotation is an essential complement to manual annotation, which cannot keep pace with either current or projected rates of growth of UniProtKB. To this end UniProt is developing an integrated annotation system termed UniRule, which is based on both manually curated and automatically generated annotation rules and signatures. UniRule provides a variety of annotation types including protein names, general functional annotation in the form of free text and controlled vocabularies, sequence annotation including domains and residues of functional importance, and inferred family relationships.At the time of writing (UniProtKB release 2010_08), UniRule provides annotations for around 30% of more than 11 million UniProtKB/TrEMBL entries. The UniRule system and plans for its future development will be presented.

Workflows to open provenance graphs, round-trip

The Open Provenance Model is designed to capture relationships amongst data values, and amongst processors that produce or consume those values. While OPM graphs are able to describe aspects of a workflow execution, capturing the structure of the workflows themselves is understandably beyond the scope of the OPM specification, since the graphs may be generated by a broad variety of processes, which may not be formal workflows at all. In particular, the OPM does not address two questions: firstly, whether for any OPM graph there exists a plausible workflow, in some model, which could have generated the graph, and secondly, which information should be captured as part of an OPM graph that is derived from the execution of some known type of workflow, so that the workflow structure and the execution trace can both be inferred back from the graph. Motivated by the need to address the Third Provenance Challenge using Taverna workflows and provenance, in this paper we explore the notion of losslessness of OPM graphs relative to Taverna workflows. For the first question, we show that Taverna is a suitable model for representing plausible OPM-generating processes. For the second question, we show how augmenting OPM with two types of annotation makes it lossless with respect to Taverna. We support this claim by presenting a two-way mapping between OPM graphs and Taverna workflows.

Tag based feedback for programming courses

This paper reports the findings of a preliminary investigation into whether feedback generated by annotating source code with tags is considered useful by undergraduate students. These types of annotations facilitate a new approach to presenting assessment feedback to students in the form of a Web 2.0 tagging environment. This paper highlights the benefits and limitations of this approach as well as details of student reaction and behavior. This investigation focuses on assessment and feedback for an undergraduate Software Engineering Group Project. The preliminary results collected encourage further investigation of this approach.

The Medicago truncatula gene expression atlas web server

BackgroundLegumes (Leguminosae or Fabaceae) play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA) web server for this purpose.DescriptionThe Medicago truncatula Gene Expression Atlas (MtGEA) web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible at: http://bioinfo.noble.org/gene-atlas/.ConclusionsThe MtGEA web server has a well managed rich data set, and offers data retrieval and analysis tools provided in the web platform. It's proven to be a powerful resource for plant biologists to effectively and efficiently identify Medicago transcripts of interest from a multitude of aspects, formulate hypothesis about gene function, and overall interpret the Medicago genome from a systematic point of view.

Structural and functional-annotation of an equine whole genome oligoarray

BackgroundThe horse genome is sequenced, allowing equine researchers to use high-throughput functional genomics platforms such as microarrays; next-generation sequencing for gene expression and proteomics. However, for researchers to derive value from these functional genomics datasets, they must be able to model this data in biologically relevant ways; to do so requires that the equine genome be more fully annotated. There are two interrelated types of genomic annotation: structural and functional. Structural annotation is delineating and demarcating the genomic elements (such as genes, promoters, and regulatory elements). Functional annotation is assigning function to structural elements. The Gene Ontology (GO) is the de facto standard for functional annotation, and is routinely used as a basis for modelling and hypothesis testing, large functional genomics datasets.ResultsAn Equine Whole Genome Oligonucleotide (EWGO) array with 21,351 elements was developed at Texas A&M University. This 70-mer oligoarray was designed using the approximately 7× assembled and annotated sequence of the equine genome to be one of the most comprehensive arrays available for expressed equine sequences. To assist researchers in determining the biological meaning of data derived from this array, we have structurally annotated it by mapping the elements to multiple database accessions, including UniProtKB, Entrez Gene, NRPD (Non-Redundant Protein Database) and UniGene. We next provided GO functional annotations for the gene transcripts represented on this array. Overall, we GO annotated 14,531 gene products (68.1% of the gene products represented on the EWGO array) with 57,912 annotations. GAQ (GO Annotation Quality) scores were calculated for this array both before and after we added GO annotation. The additional annotations improved the meanGAQ score 16-fold. This data is publicly available at AgBase http://www.agbase.msstate.edu/.ConclusionProviding additional information about the public databases which link to the gene products represented on the array allows users more flexibility when using gene expression modelling and hypothesis-testing computational tools. Moreover, since different databases provide different types of information, users have access to multiple data sources. In addition, our GO annotation underpins functional modelling for most gene expression analysis tools and enables equine researchers to model large lists of differentially expressed transcripts in biologically relevant ways.

Annotation of protein residues based on a literature analysis: cross-validation against UniProtKb

BackgroundA protein annotation database, such as the Universal Protein Resource knowledge base (UniProtKb), is a valuable resource for the validation and interpretation of predicted 3D structure patterns in proteins. Existing studies have focussed on point mutation extraction methods from biomedical literature which can be used to support the time consuming work of manual database curation. However, these methods were limited to point mutation extraction and do not extract features for the annotation of proteins at the residue level.ResultsThis work introduces a system that identifies protein residues in MEDLINE abstracts and annotates them with features extracted from the context written in the surrounding text. MEDLINE abstract texts have been processed to identify protein mentions in combination with taxonomic species and protein residues (F1-measure 0.52). The identified protein-species-residue triplets have been validated and benchmarked against reference data resources (UniProtKb, average F1-measure of 0.54). Then, contextual features were extracted through shallow and deep parsing and the features have been classified into predefined categories (F1-measure ranges from 0.15 to 0.67). Furthermore, the feature sets have been aligned with annotation types in UniProtKb to assess the relevance of the annotations for ongoing curation projects. Altogether, the annotations have been assessed automatically and manually against reference data resources.ConclusionThis work proposes a solution for the automatic extraction of functional annotation for protein residues from biomedical articles. The presented approach is an extension to other existing systems in that a wider range of residue entities are considered and that features of residues are extracted as annotations.

The LEMO annotation framework: weaving multimedia annotations with the web

Cultural institutions and museums have realized that annotations contribute valuable metadata for search and retrieval, which in turn can increase the visibility of the digital items they expose via their digital library systems. By exploiting annotations created by others, visitors can discover content they would not have found otherwise, which implies that annotations must be accessible and processable for humans and machines. Currently, however, there exists no widely adopted annotation standard that goes beyond specific media types. Most institutions build their own in-house annotation solution and employ proprietary annotation models, which are not interoperable with those of other systems. As a result, annotation data are usually stored in closed data silos and visible and processable only within the scope of a certain annotation system. As the main contribution of this paper, we present the LEMO Annotation Framework. It (1) provides a uniform annotation model for multimedia contents and various types of annotations, (2) can address fragments of various content-types in a uniform, interoperable manner and (3) pulls annotations out of closed data silos and makes them available as interoperable, dereferencable Web resources. With the LEMO Annotation Framework annotations become part of the Web and can be processed, linked, and referenced by other services. This in turn leads to even higher visibility and increases the potential value of annotations.

OVerFA: a collaborative framework for the semantic annotation of documents and websites

Ontology-based annotation is one of the leading trends in the creation of metadata. It uses ontologies as vocabularies. Several languages and tools exist which support annotations of different types of media. Usually, such languages are tightly coupled with specific tools and they are able to describe only those features the tools are designed to manage. Furthermore, very few tools and languages (or none at all) support annotations of multiple media types or documents, or ontologies and annotations versioning, so they are not so useful in a collaborative infrastructure which aims to produce annotations of multimedia resources. In this work the main architecture and the language to create annotations of the Ontology-based VERsioned Framework for Annotation (OVerFA) are presented. How the framework allows for collaborative annotation of documents of different media types and how it is possible to exploit useful features in order to produce clear and complete ontology-based annotations are shown.

No Miniatures, not even Decoration, yet Extraordinarily Fascinating New Hypotheses Concerning the Lancelot Compilation and Related Manuscripts

AbstractThis essay sheds new light on the controversial fourteenth-century poet and compiler Lodewijk van Velthem. Specifically, the article considers the possible relationships between The Hague, Koninklijke Bibliotheek, MS 129 A 10, the manuscript containing the famous Lancelot Compilation, and Leiden, University Library, MS BPL 14 E, the only extant manuscript with Velthem's entire Fifth Part of the Spiegel historiael. A note written at the end of the manuscript in The Hague naming Velthem has been interpreted in different ways, either as a note of the manuscript's ownership, or as the attribution of the compilation to Velthem. Other scholars have considered Velthem the 'corrector' of the manuscript. The relatively low quality of these two manuscripts, as well as the types of annotations made in the margins of MS 129 A 10, however, can be explained when we consider both books as the poet's working copies, as manuscripts which formed part of Velthem's own literary archive.

GPAT: Retrieval of genomic annotation from large genomic position datasets

BackgroundRecent genome wide transcription factor binding site or chromatin modification mapping analysis techniques, such as chromatin immunoprecipitation (ChIP) linked to DNA microarray analysis (ChIP on chip) or ChIP coupled to high throughput sequencing (ChIP-seq), generate tremendous amounts of genomic location data in the form of one-dimensional series of signals. After pre-analysis of these data (signal pre-clearing, relevant binding site detection), biologists need to search for the biological relevance of the detected genomic positions representing transcription regulation or chromatin modification events.ResultsTo address this problem, we have developed a Genomic Position Annotation Tool (GPAT) with a simple web interface that allows the rapid and systematic labelling of thousands of genomic positions with several types of annotations. GPAT automatically extracts gene annotation information around the submitted positions from different public databases (Refseq or ENSEMBL). In addition, GPAT provides access to the expression status of the corresponding genes from either existing transcriptomic databases or from user generated expression data sets. Furthermore, GPAT allows the localisation of the genomic coordinates relative to the chromosome bands and the well characterised ENCODE regions. We successfully used GPAT to analyse ChIP on chip data and to identify genes functionally regulated by the TATA binding protein (TBP).ConclusionGPAT provides a quick, convenient and flexible way to annotate large sets of genomic positions obtained after pre-analysis of ChIP-chip, ChIP-seq or other high throughput sequencing-based techniques. Through the different annotation data displayed, GPAT facilitates the interpretation of genome wide datasets for molecular biologists.

Introducing meta-services for biomedical information extraction

We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; ). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations for PubMed/Medline abstracts. Annotation types cover gene names, gene IDs, species, and protein-protein interactions. The annotations are distributed by the meta-server in both human and machine readable formats (HTML/XML). This service is intended to be used by biomedical researchers and database annotators, and in biomedical language processing. The platform allows direct comparison, unified access, and result aggregation of the annotations.

Automatic Annotation of Semantic Fields for Political Science Research

ABSTRACT This article discusses methods for automatic annotation of political texts for semantic fields—groups of words with related meanings. This type of annotation is useful when studying political communication, such as legislative debate or political speeches. We present three types of automatic annotation: unsupervised clustering, dictionary-based approaches, and a method based on relevant experimental data. All methods are applied to analyzing Margaret Thatcher's political rhetoric. For this data, we find that unsupervised clustering is most useful for tracing topics; dictionary-based methods are most effective in a comparative setting; whereas the last method is the most promising for detecting off-topic, singular uses of semantic domains, which are often rhetorical tools used to achieve a political end. Applicability, strengths, and weaknesses of each method and of their combinations are addressed in detail.

Maps: An integrated system for protein sequence annotation using support vector machine

An Integrated environment for biological data is valuable to the function annotation of protein sequences. In this paper, we present a protein sequence annotation system, named MAPS (Multiple Annotation for Protein Sequences), which provides a mechanism to extract multiple annotations from various types of biological data including SwissProt keywords, InterPro signatures and GO terms. Furthermore, MAPS can automatically eliminate the annotation errors generated by a pre‐trained SVM classifier. It assigns an annotation to the protein sequence at question by considering not only a single similar protein but also all similar proteins with the annotation. In other words, we take account of the evolutionary information of the protein of interest to reduce the error annotations inferred from weak sequence similarities and from sequence identities in non‐functional segments. The experimental results show that the error annotations can be eliminated effectively while keeping high accuracy for different types of annotations.

Predictors of Foreign Language Reading Comprehension in a Hypermedia Reading Environment

This study investigated factors affecting second/foreign language (L2) reading comprehension in a hypermedia environment within the theoretical framework of dual coding and cognitive load theories, and interactive models of L2 reading. The independent variables were reading ability, topic interest, prior topical knowledge, and the number of times participants accessed annotations. The dependent variable of interest was reading comprehension measured through a recall test. The participants were 54 senior foreign language teaching students at a state university in Turkey. The participants were given a hypertext to read for general comprehension and were told that they would be required to write down everything they remembered at the end of reading. The text was annotated with multiple forms of media: text, graphics, audio, and video. Annotations provided information both at the word level (i.e., definitions of words) and topic level (i.e., extra information about the topic). A multiple regression analysis with reading comprehension as the criterion and the independent variables mentioned above as the predictors served to reveal whether a relationship existed between the potential predictor and outcome variables. Findings indicated that topic interest and annotation look up were important variables contributing to reading comprehension in a hypermedia environment. It was also found that videos and textual information were the most useful types of annotations. It was suggested that hypermedia environments accommodated for most types of learning styles. It was also suggested that providing extra topical information through annotations compensated for the lack of prior knowledge.

The use of annotations in examination marking: opening a window into markers' minds

This study investigated the functions of annotations, the role of annotations in markers' decision‐making processes, whether annotations conform to conventions, and whether these vary according to subject area. Across subjects a number of scripts were analysed to survey which annotations are subject specific and which are more general. Twelve examiners at different levels of responsibility marked the same General Certificate of Secondary Education Mathematics and Business Studies scripts as one another. The marking was analysed to identify whether there were any patterns in the use of annotations. Retrospective individual interviews were used to inform the analysis of the annotations. Findings showed that the frequency and type of annotations used differed between subjects and that within a subject team examiners drew from a common pool of annotations. Purposes for annotation use included supporting markers' judgements and explaining decisions.

Text processing through Web services: calling Whatizit

Text-mining (TM) solutions are developing into efficient services to researchers in the biomedical research community. Such solutions have to scale with the growing number and size of resources (e.g. available controlled vocabularies), with the amount of literature to be processed (e.g. about 17 million documents in PubMed) and with the demands of the user community (e.g. different methods for fact extraction). These demands motivated the development of a server-based solution for literature analysis. Whatizit is a suite of modules that analyse text for contained information, e.g. any scientific publication or Medline abstracts. Special modules identify terms and then link them to the corresponding entries in bioinformatics databases such as UniProtKb/Swiss-Prot data entries and gene ontology concepts. Other modules identify a set of selected annotation types like the set produced by the EBIMed analysis pipeline for proteins. In the case of Medline abstracts, Whatizit offers access to EBI's in-house installation via PMID or term query. For large quantities of the user's own text, the server can be operated in a streaming mode (http://www.ebi.ac.uk/webservices/whatizit).

Automatic Annotation of Semantic Fields for Political Science Research

This article discusses methods for automatic annotation of political texts for semantic fields - groups of words with related meanings. This type of annotation is useful when studying the structure of political ideology, from agendas to rhetoric. We argue that it is important to exclude the researcher from the construction of analytic categories, due to her own susceptibility to the very phenomenon under analysis. In this vein, three types of automatic annotation are presented - unsupervised clustering, dictionary-based approaches, and a method based on relevant experimental data. All methods are applied to analyzing Margaret Thatcher's political rhetoric. We find that unsupervised clustering is most useful for tracing agendas/topics; dictionary-based methods are most effective in a comparative setting, whereas the last method is the most promising for detecting off-topic, singular uses of semantic domains, which are often rhetorical tools used to achieve a political end. Validity, applicability, strengths and weaknesses of each method and of their combinations are addressed in detail.