Ensembl 2018

By Daniel R. Zerbino, P. Achuthan, Wasiu A. Akanni, M. Amode, Daniel Barrell, Jyothish Bhai, Konstantinos Billis, Carla A. Cummins, A. Gall, C. G. Girón and 47 more. 2017

2,474 citations recorded by the source corpus.

Abstract The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.

Subfields: Molecular Biology

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Citations in the corpus

UniProt: a worldwide hub of protein knowledge (2018, methodology): “To ensure comprehensiveness, complementary pipelines have been developed to supplement these with genomes sequenced and / or annotated by groups such as Ensembl (3), Vectorbase (4) and WormBase ParaSite (5).”
Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes (2019, methodology): “pyHam can also be used to infer enhanced phylogenies for other datasets available in OrthoXML format such as ENSEMBL [13] or with data generated from phylogenetic trees such as those found in PANTHER [64] through the use of the function etree2orthoxml () in the tree analysis package ETE3 [65].”
The PRIDE database and related tools and resources in 2019: improving support for quantification data (2018, background): “At present, identified proteins in PRIDE ‘Complete’ datasets are cross-referenced in the corresponding UniProt entries (e.g. https://www.uniprot.org/uniprot/Q12181) and ‘TrackHubs’ are published for some ‘Complete’ datasets in Ensembl.”