BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submissio...
Background: Annotation of eukaryotic genomes is a complex endeavor that requires the integration of...
With the sponsorship of "Fundacio La Caixa" we met in Barcelona, November 21st and 22nd, to analyze ...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...
BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art i...
BACKGROUND: The GENCODE consortium was formed to identify and map all protein-coding genes within th...
Background The ENCODE gene prediction workshop (EGASP) has been organized to evaluate how well state...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...
The Human and Vertebrate Analysis and Annotation (HAVANA) group at the Wellcome Trust Sanger Institu...
Background: Predicting complete protein-coding genes in human DNA remains a significant challenge. ...
The current GENCODE gene count of ~ 30,000, including 21,727 protein-coding and 8,483 RNA genes, is ...
Biomedical research has been undergoing a quasi-revolution with the dawn of the genomics era. The f...
The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded pro...
Computational methods for automated genome annotation are critical to our community's ability to mak...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...
This article is part of the supplement: Beyond the Genome: The true gene count, human evolution and ...
Background: Annotation of eukaryotic genomes is a complex endeavor that requires the integration of...
With the sponsorship of "Fundacio La Caixa" we met in Barcelona, November 21st and 22nd, to analyze ...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...
BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art i...
BACKGROUND: The GENCODE consortium was formed to identify and map all protein-coding genes within th...
Background The ENCODE gene prediction workshop (EGASP) has been organized to evaluate how well state...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...
The Human and Vertebrate Analysis and Annotation (HAVANA) group at the Wellcome Trust Sanger Institu...
Background: Predicting complete protein-coding genes in human DNA remains a significant challenge. ...
The current GENCODE gene count of ~ 30,000, including 21,727 protein-coding and 8,483 RNA genes, is ...
Biomedical research has been undergoing a quasi-revolution with the dawn of the genomics era. The f...
The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded pro...
Computational methods for automated genome annotation are critical to our community's ability to mak...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...
This article is part of the supplement: Beyond the Genome: The true gene count, human evolution and ...
Background: Annotation of eukaryotic genomes is a complex endeavor that requires the integration of...
With the sponsorship of "Fundacio La Caixa" we met in Barcelona, November 21st and 22nd, to analyze ...
The GENCODE Consortium aims to identify all gene features in the human genome using a combination of...