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Annotation

About: Annotation is a research topic. Over the lifetime, 6719 publications have been published within this topic receiving 203463 citations. The topic is also known as: note & markup.


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Proceedings ArticleDOI
28 Jul 2003
TL;DR: The approach shows the usefulness of using formal information retrieval models for the task of image annotation and retrieval by assuming that regions in an image can be described using a small vocabulary of blobs.
Abstract: Libraries have traditionally used manual image annotation for indexing and then later retrieving their image collections. However, manual image annotation is an expensive and labor intensive procedure and hence there has been great interest in coming up with automatic ways to retrieve images based on content. Here, we propose an automatic approach to annotating and retrieving images based on a training set of images. We assume that regions in an image can be described using a small vocabulary of blobs. Blobs are generated from image features using clustering. Given a training set of images with annotations, we show that probabilistic models allow us to predict the probability of generating a word given the blobs in an image. This may be used to automatically annotate and retrieve images given a word as a query. We show that relevance models allow us to derive these probabilities in a natural way. Experiments show that the annotation performance of this cross-media relevance model is almost six times as good (in terms of mean precision) than a model based on word-blob co-occurrence model and twice as good as a state of the art model derived from machine translation. Our approach shows the usefulness of using formal information retrieval models for the task of image annotation and retrieval.

1,275 citations

Proceedings Article
23 Apr 2012
TL;DR: The brat rapid annotation tool (BRAT) is introduced, an intuitive web-based tool for text annotation supported by Natural Language Processing (NLP) technology and an evaluation of annotation assisted by semantic class disambiguation on a multicategory entity mention annotation task, showing a 15% decrease in total annotation time.
Abstract: We introduce the brat rapid annotation tool (BRAT), an intuitive web-based tool for text annotation supported by Natural Language Processing (NLP) technology. BRAT has been developed for rich structured annotation for a variety of NLP tasks and aims to support manual curation efforts and increase annotator productivity using NLP techniques. We discuss several case studies of real-world annotation projects using pre-release versions of BRAT and present an evaluation of annotation assisted by semantic class disambiguation on a multicategory entity mention annotation task, showing a 15% decrease in total annotation time. BRAT is available under an open-source license from: http://brat.nlplab.org

1,121 citations

Journal ArticleDOI
TL;DR: Through incorporation of multiple transcript and proteomic expression data sets, the Institute for Genomic Research has been able to annotate 24 799 genes (31 739 gene models), representing ∼50% of the total gene models, as expressed in the rice genome.
Abstract: In The Institute for Genomic Research Rice Genome Annotation project (http://rice.tigr.org), we have continued to update the rice genome sequence with new data and improve the quality of the annotation. In our current release of annotation (Release 4.0; January 12, 2006), we have identified 42,653 non-transposable element-related genes encoding 49,472 gene models as a result of the detection of alternative splicing. We have refined our identification methods for transposable element-related genes resulting in 13,237 genes that are related to transposable elements. Through incorporation of multiple transcript and proteomic expression data sets, we have been able to annotate 24 799 genes (31,739 gene models), representing approximately 50% of the total gene models, as expressed in the rice genome. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 59 tracks. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads.

1,117 citations

Journal ArticleDOI
TL;DR: The Genome Browser displays a wide variety of annotations at all scales from the single nucleotide level up to a full chromosome and includes assembly data, genes and gene predictions, mRNA and EST alignments, and comparative genomics, regulation, expression and variation data.
Abstract: The University of California, Santa Cruz Genome Browser Database contains, as of September 2006, sequence and annotation data for the genomes of 13 vertebrate and 19 invertebrate species. The Genome Browser displays a wide variety of annotations at all scales from the single nucleotide level up to a full chromosome and includes assembly data, genes and gene predictions, mRNA and EST alignments, and comparative genomics, regulation, expression and variation data. The database is optimized for fast interactive performance with web tools that provide powerful visualization and querying capabilities for mining the data. In the past year, 22 new assemblies and several new sets of human variation annotation have been released. New features include VisiGene, a fully integrated in situ hybridization image browser; phyloGif, for drawing evolutionary tree diagrams; a redesigned Custom Track feature; an expanded SNP annotation track; and many new display options. The Genome Browser, other tools, downloadable data files and links to documentation and other information can be found at http://genome.ucsc.edu/.

1,061 citations

Journal ArticleDOI
TL;DR: An algorithm for reference annotation-based transcript assembly is presented and it is shown how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation.
Abstract: Summary: We describe a new ‘reference annotation based transcript assembly’ problem for RNA-Seq data that involves assembling novel transcripts in the context of an existing annotation. This problem arises in the analysis of expression in model organisms, where it is desirable to leverage existing annotations for discovering novel transcripts. We present an algorithm for reference annotation-based transcript assembly and show how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation. Availability: The methods described in this article are implemented in the Cufflinks suite of software for RNA-Seq, freely available from http://bio.math.berkeley.edu/cufflinks. The software is released under the BOOST license. Contact:cole@broadinstitute.org; lpachter@math.berkeley.edu Supplementary Information:Supplementary data are available at Bioinformatics online.

953 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,564
20223,226
2021343
2020421
2019401
2018394