Topic
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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07 Nov 2003
TL;DR: The Family Video Archive is presented as a tool to give consumers the ability to annotate and browse large collections of informal family movies and the system explores the symbiosis between automated and manual techniques for annotation.
Abstract: We present the Family Video Archive as a tool to give consumers the ability to annotate and browse large collections of informal family movies. The informal nature of home movies makes it difficult to use fully-automated techniques for scene detection and annotation. Our system explores the symbiosis between automated and manual techniques for annotation. We also explore the use of a zooming interaction paradigm for browsing and filtering large collections of video scenes.
91 citations
TL;DR: Ten steps to facilitate researchers getting started in genome assembly and genome annotation are presented and the importance of data management is stressed, and advice on where to submit data and how to make results Findable, Accessible, Interoperable, and Reusable (FAIR).
Abstract: As a part of the ELIXIR-EXCELERATE efforts in capacity building, we present here 10 steps to facilitate researchers getting started in genome assembly and genome annotation The guidelines given are broadly applicable, intended to be stable over time, and cover all aspects from start to finish of a general assembly and annotation project Intrinsic properties of genomes are discussed, as is the importance of using high quality DNA Different sequencing technologies and generally applicable workflows for genome assembly are also detailed We cover structural and functional annotation and encourage readers to also annotate transposable elements, something that is often omitted from annotation workflows The importance of data management is stressed, and we give advice on where to submit data and how to make your results Findable, Accessible, Interoperable, and Reusable (FAIR)
91 citations
TL;DR: A multi-cue approach to automatic medical image annotation is proposed, which represents images using global and local features and combines three alternative approaches, all based on the support vector machine algorithm.
91 citations
TL;DR: MEGAnnotator platform will be useful for microbiologists interested in genome analyses of bacteria as well as those investigating the complexity of microbial communities that do not possess the necessary skills to prepare their own bioinformatics pipeline.
Abstract: Genome annotation is one of the key actions that must be undertaken in order to decipher the genetic blueprint of organisms. Thus, a correct and reliable annotation is essential in rendering genomic data valuable. Here, we describe a bioinformatics pipeline based on freely available software programs coordinated by a multithreaded script named MEGAnnotator (Multithreaded Enhanced prokaryotic Genome Annotator). This pipeline allows the generation of multiple annotated formats fulfilling the NCBI guidelines for assembled microbial genome submission, based on DNA shotgun sequencing reads, and minimizes manual intervention, while also reducing waiting times between software program executions and improving final quality of both assembly and annotation outputs. MEGAnnotator provides an efficient way to pre-arrange the assembly and annotation work required to process NGS genome sequence data. The script improves the final quality of microbial genome annotation by reducing ambiguous annotations. Moreover, the MEGAnnotator platform allows the user to perform a partial annotation of pre-assembled genomes and includes an option to accomplish metagenomic data set assemblies. MEGAnnotator platform will be useful for microbiologists interested in genome analyses of bacteria as well as those investigating the complexity of microbial communities that do not possess the necessary skills to prepare their own bioinformatics pipeline.
91 citations
TL;DR: An XML-based Java application is described that provides a function-oriented overview of the results of cluster analysis of gene-expression microarray data based on Gene Ontology terms and associations.
Abstract: Summary: An XML-based Java application is described that provides a function-oriented overview of the results of cluster analysis of gene-expression microarray data based on Gene Ontology terms and associations. The application generates one HTML page with listings of the frequencies of explicit and implicit Gene Ontology annotations for each cluster, and separate, linked pages with listings of explicit annotations for each gene in a cluster.
Availability: http://www.charite.de/ch/medgen/ontologizer
91 citations