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Dive into the research topics where Eleanor Williams is active.

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Featured researches published by Eleanor Williams.


Nucleic Acids Research | 2009

ArrayExpress update—from an archive of functional genomics experiments to the atlas of gene expression

Helen E. Parkinson; Misha Kapushesky; Nikolay Kolesnikov; Gabriella Rustici; Mohammadreza Shojatalab; Niran Abeygunawardena; Hugo Bérubé; Miroslaw Dylag; Ibrahim Emam; Anna Farne; Ele Holloway; Margus Lukk; James P. Malone; Roby Mani; Ekaterina Pilicheva; Tim F. Rayner; Faisal Ibne Rezwan; Anjan Sharma; Eleanor Williams; Xiangqun Zheng Bradley; Tomasz Adamusiak; Marco Brandizi; Tony Burdett; Richard M. R. Coulson; Maria Krestyaninova; Pavel Kurnosov; Eamonn Maguire; Sudeshna Guha Neogi; Philippe Rocca-Serra; Susanna-Assunta Sansone

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository—a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse—a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas—a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200 000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently—ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.


Nucleic Acids Research | 2011

ArrayExpress update—an archive of microarray and high-throughput sequencing-based functional genomics experiments

Helen E. Parkinson; Ugis Sarkans; Nikolay Kolesnikov; Niran Abeygunawardena; Tony Burdett; Miroslaw Dylag; Ibrahim Emam; Anna Farne; Emma Hastings; Ele Holloway; Natalja Kurbatova; Margus Lukk; James Malone; Roby Mani; Ekaterina Pilicheva; Gabriella Rustici; Anjan Sharma; Eleanor Williams; Tomasz Adamusiak; Marco Brandizi; Nataliya Sklyar; Alvis Brazma

The ArrayExpress Archive (http://www.ebi.ac.uk/arrayexpress) is one of the three international public repositories of functional genomics data supporting publications. It includes data generated by sequencing or array-based technologies. Data are submitted by users and imported directly from the NCBI Gene Expression Omnibus. The ArrayExpress Archive is closely integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Advanced queries provided via ontology enabled interfaces include queries based on technology and sample attributes such as disease, cell types and anatomy.


Nucleic Acids Research | 2012

ArrayExpress update—trends in database growth and links to data analysis tools

Gabriella Rustici; Nikolay Kolesnikov; Marco Brandizi; Tony Burdett; Miroslaw Dylag; Ibrahim Emam; Anna Farne; Emma Hastings; Jon Ison; Maria Keays; Natalja Kurbatova; James Malone; Roby Mani; Annalisa Mupo; Rui Pedro Pereira; Ekaterina Pilicheva; Johan Rung; Anjan Sharma; Y. Amy Tang; Tobias Ternent; Andrew Tikhonov; Danielle Welter; Eleanor Williams; Alvis Brazma; Helen E. Parkinson; Ugis Sarkans

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is one of three international functional genomics public data repositories, alongside the Gene Expression Omnibus at NCBI and the DDBJ Omics Archive, supporting peer-reviewed publications. It accepts data generated by sequencing or array-based technologies and currently contains data from almost a million assays, from over 30 000 experiments. The proportion of sequencing-based submissions has grown significantly over the last 2 years and has reached, in 2012, 15% of all new data. All data are available from ArrayExpress in MAGE-TAB format, which allows robust linking to data analysis and visualization tools, including Bioconductor and GenomeSpace. Additionally, R objects, for microarray data, and binary alignment format files, for sequencing data, have been generated for a significant proportion of ArrayExpress data.


Nucleic Acids Research | 2015

ArrayExpress update—simplifying data submissions

Nikolay Kolesnikov; Emma Hastings; Maria Keays; Olga Melnichuk; Y. Amy Tang; Eleanor Williams; Miroslaw Dylag; Natalja Kurbatova; Marco Brandizi; Tony Burdett; Karyn Megy; Ekaterina Pilicheva; Gabriella Rustici; Andrew Tikhonov; Helen Parkinson; Robert Petryszak; Ugis Sarkans; Alvis Brazma

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is an international functional genomics database at the European Bioinformatics Institute (EMBL-EBI) recommended by most journals as a repository for data supporting peer-reviewed publications. It contains data from over 7000 public sequencing and 42 000 array-based studies comprising over 1.5 million assays in total. The proportion of sequencing-based submissions has grown significantly over the last few years and has doubled in the last 18 months, whilst the rate of microarray submissions is growing slightly. All data in ArrayExpress are available in the MAGE-TAB format, which allows robust linking to data analysis and visualization tools and standardized analysis. The main development over the last two years has been the release of a new data submission tool Annotare, which has reduced the average submission time almost 3-fold. In the near future, Annotare will become the only submission route into ArrayExpress, alongside MAGE-TAB format-based pipelines. ArrayExpress is a stable and highly accessed resource. Our future tasks include automation of data flows and further integration with other EMBL-EBI resources for the representation of multi-omics data.


Nucleic Acids Research | 2014

Expression Atlas update—a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

Robert Petryszak; Tony Burdett; Benedetto Fiorelli; Nuno A. Fonseca; Mar Gonzàlez-Porta; Emma Hastings; Wolfgang Huber; Simon Jupp; Maria Keays; Nataliya Kryvych; Julie McMurry; John C. Marioni; James P. Malone; Karine Megy; Gabriella Rustici; Amy Tang; Jan Taubert; Eleanor Williams; Oliver Mannion; Helen Parkinson; Alvis Brazma

Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of ‘baseline’ expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful ‘contrasts’, i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.


Nucleic Acids Research | 2016

Expression Atlas update—an integrated database of gene and protein expression in humans, animals and plants

Robert Petryszak; Maria Keays; Y. Amy Tang; Nuno A. Fonseca; Elisabet Barrera; Tony Burdett; Anja Füllgrabe; Alfonso Muñoz-Pomer Fuentes; Simon Jupp; Satu Koskinen; Oliver Mannion; Laura Huerta; Karine Megy; Catherine Snow; Eleanor Williams; Mitra Barzine; Emma Hastings; Hendrik Weisser; James C. Wright; Pankaj Jaiswal; Wolfgang Huber; Jyoti S. Choudhary; Helen Parkinson; Alvis Brazma

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons—estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: ‘enrichment’ in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.


Nucleic Acids Research | 2010

Gene Expression Atlas at the European Bioinformatics Institute

Misha Kapushesky; Ibrahim Emam; Ele Holloway; Pavel Kurnosov; Andrey Zorin; James Malone; Gabriella Rustici; Eleanor Williams; Helen Parkinson; Alvis Brazma

The Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive of Functional Genomics Data. A simple interface allows the user to query for differential gene expression either (i) by gene names or attributes such as Gene Ontology terms, or (ii) by biological conditions, e.g. diseases, organism parts or cell types. The gene queries return the conditions where expression has been reported, while condition queries return which genes are reported to be expressed in these conditions. A combination of both query types is possible. The query results are ranked using various statistical measures and by how many independent studies in the database show the particular gene-condition association. Currently, the database contains information about more than 200 000 genes from nine species and almost 4500 biological conditions studied in over 30 000 assays from over 1000 independent studies.


Nucleic Acids Research | 2012

Gene Expression Atlas update—a value-added database of microarray and sequencing-based functional genomics experiments

Misha Kapushesky; Tomasz Adamusiak; Tony Burdett; Aedín C. Culhane; Anna Farne; Alexey Filippov; Ele Holloway; Andrey Klebanov; Nataliya Kryvych; Natalja Kurbatova; Pavel Kurnosov; James P. Malone; Olga Melnichuk; Robert Petryszak; Nikolay Pultsin; Gabriella Rustici; Andrew Tikhonov; Ravensara S. Travillian; Eleanor Williams; Andrey Zorin; Helen E. Parkinson; Alvis Brazma

Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive and the European Nucleotide Archive. A simple interface allows the user to query for differential gene expression either by gene names or attributes or by biological conditions, e.g. diseases, organism parts or cell types. Since our previous report we made 20 monthly releases and, as of Release 11.08 (August 2011), the database supports 19 species, which contains expression data measured for 19 014 biological conditions in 136 551 assays from 5598 independent studies.


Nature Methods | 2017

Image Data Resource: a bioimage data integration and publication platform

Eleanor Williams; Josh Moore; Simon Li; Gabriella Rustici; Aleksandra Tarkowska; Anatole Chessel; Simone Leo; Bálint Antal; Richard K. Ferguson; Ugis Sarkans; Alvis Brazma; Jason R. Swedlow

Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR). IDR links data from several imaging modalities, including high-content screening, multi-dimensional microscopy and digital pathology, with public genetic or chemical databases and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable reanalysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open-source platform for publishing imaging data. Thus IDR provides an online resource and a software infrastructure that promotes and extends publication and reanalysis of scientific image data.


Journal of Biomedical Semantics | 2016

The cellular microscopy phenotype ontology

Simon Jupp; James Malone; Tony Burdett; Jean-Karim Hériché; Eleanor Williams; Jan Ellenberg; Helen Parkinson; Gabriella Rustici

BackgroundPhenotypic data derived from high content screening is currently annotated using free-text, thus preventing the integration of independent datasets, including those generated in different biological domains, such as cell lines, mouse and human tissues.DescriptionWe present the Cellular Microscopy Phenotype Ontology (CMPO), a species neutral ontology for describing phenotypic observations relating to the whole cell, cellular components, cellular processes and cell populations. CMPO is compatible with related ontology efforts, allowing for future cross-species integration of phenotypic data. CMPO was developed following a curator-driven approach where phenotype data were annotated by expert biologists following the Entity-Quality (EQ) pattern. These EQs were subsequently transformed into new CMPO terms following an established post composition process.ConclusionCMPO is currently being utilized to annotate phenotypes associated with high content screening datasets stored in several image repositories including the Image Data Repository (IDR), MitoSys project database and the Cellular Phenotype Database to facilitate data browsing and discoverability.

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Gabriella Rustici

Wellcome Trust Sanger Institute

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Alvis Brazma

European Bioinformatics Institute

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Tony Burdett

European Bioinformatics Institute

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Ugis Sarkans

European Bioinformatics Institute

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Emma Hastings

European Bioinformatics Institute

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Helen Parkinson

European Bioinformatics Institute

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