Publications by authors named "Jennifer Hillman-Jackson"

Article Synopsis
  • Traditional hands-on training in bioinformatics often struggles with resource-intensive requirements and management issues for instructors, especially in virtual settings where tracking student progress is challenging.
  • The Training Infrastructure-as-a-Service (TIaaS) was developed to provide user-friendly, efficient training resources specifically for Galaxy-based courses, allowing event organizers to allocate dedicated resources for smoother operations and quick job completion.
  • TIaaS enhances the training experience for both instructors and students by offering a dashboard for monitoring progress and ensuring students can seamlessly continue using Galaxy tools even after the training, with significant usage reported over the past 60 months.
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Summary: Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform.

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Article Synopsis
  • - Modern biology is increasingly reliant on computational methods to handle the large and complex datasets that are emerging, posing a challenge for experimental biologists who may lack computational skills.
  • - Galaxy is a web-based platform that provides access to a variety of computational biology tools and public biological data repositories, allowing users to blend private and public datasets.
  • - The article offers detailed protocols for using Galaxy to conduct specific biological analyses, including finding human coding exons, analyzing ChIP-seq data, comparing datasets, and working with RNA-seq.
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Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging.

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High-throughput data production technologies, particularly 'next-generation' DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses.

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Article Synopsis
  • Next-generation sequencing (NGS) technology generates massive amounts of data faster than we can analyze it, creating a need for better informatics methods.
  • The chapter focuses on using the Galaxy platform for transforming NGS data into usable information through step-by-step example analyses.
  • Instructions for setting up a personal Galaxy server, either on local hardware or in the cloud, and for installing new tools are included.
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Innovations in biomedical research technologies continue to provide experimental biologists with novel and increasingly large genomic and high-throughput data resources to be analyzed. As creating and obtaining data has become easier, the key decision faced by many researchers is a practical one: where and how should an analysis be performed? Datasets are large and analysis tool set-up and use is riddled with complexities outside of the scope of core research activities. The authors believe that Galaxy provides a powerful solution that simplifies data acquisition and analysis in an intuitive Web application, granting all researchers access to key informatics tools previously only available to computational specialists working in Unix-based environments.

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Article Synopsis
  • The University of California, Santa Cruz Genome Browser provides access to a comprehensive database of genomic data for various organisms, along with tools for analysis and visualization of both public and user-generated datasets.
  • This year, new features include a gene search tool, improved annotation track management, and support for advanced file formats like BAM and BigWig/BigBed, enhancing user experience.
  • Recent updates include the addition of seven new genome assemblies, a Neandertal genome portal, new phenotype and disease data, and updates to existing tracks for more effective data representation.
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The University of California, Santa Cruz (UCSC) Genome Browser website (http://genome.ucsc.edu/) provides a large database of publicly available sequence and annotation data along with an integrated tool set for examining and comparing the genomes of organisms, aligning sequence to genomes, and displaying and sharing users' own annotation data.

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Article Synopsis
  • - The study reports on experiments analyzing a targeted 1% of the human genome during the ENCODE Project's pilot phase, providing crucial insights into human genome function.
  • - Findings reveal that the human genome is largely transcribed, with evidence showing that most genomic bases contribute to various types of transcripts, including those that do not code for proteins.
  • - Enhanced understanding of transcription regulation, chromatin structure, and evolutionary insights from comparisons between species help define the functional landscape of the human genome, guiding future research in genome characterization.
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The goal of the Encyclopedia Of DNA Elements (ENCODE) Project is to identify all functional elements in the human genome. The pilot phase is for comparison of existing methods and for the development of new methods to rigorously analyze a defined 1% of the human genome sequence. Experimental datasets are focused on the origin of replication, DNase I hypersensitivity, chromatin immunoprecipitation, promoter function, gene structure, pseudogenes, non-protein-coding RNAs, transcribed RNAs, multiple sequence alignment and evolutionarily constrained elements.

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