Defining functional DNA elements in the human genome
By Manolis Kellis, Barbara J. Wold, Michael Snyder, Bradley E. Bernstein, Anshul B Kundaje, G. Marinov, Lucas D. Ward, Ewan Birney, Gregory E. Crawford, Job Dekker and 20 more. 2014
696 citations recorded by the source corpus.
Subfields: Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Roded Sharan
- Trey Ideker
- Lenore J. Cowen
- Benjamin J. Raphael
- Nathan Johnson
- Steven P. Wilder
- John Hardy
- Thomas Juettemann
Citations in the corpus
- Network propagation: a universal amplifier of genetic associations (2017, background): “In addition, regulatory networks are increasing in scope and resolution, through efforts such as ENCODE 97 and the Roadmap Epigenomics project 98 .”
- The Human Transcription Factors. (2018, neutral): “Most of the functional DNA in the genome is likely regulatory (Kellis et al., 2014), with TFs playing a central role in its recognition and utilization.”
- Regulation of disease-associated gene expression in the 3D genome (2016, neutral): “GWAS classically do not sequence entire genomes; thus, the identified riskassociated variants may be drivers of disease or passengers that are in linkage disequilibrium with nearby but undetected driver variants 29,112 .”
- High-Throughput Sequencing Technologies (2015, background): “Nonetheless, a variety of lines of evidence (GWAS and ENCODE) suggest that the total amount of regulatory regions is likely greater than that of protein coding regions (Kellis et al., 2014).”
- The Ensembl Regulatory Build (2015, background): “Its regulatory features are phenomenological, that is, defined by biochemical signal alone [34].”
- Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses (2019, neutral): “[49] Even for traits that are genetically independent, knowing that a SNP is causal for one trait implies it is functional, and thus more likely to be causal for another trait then a random SNP that may or may not be functional.”
- Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences (2016, background): “Since signature patterns differ between cells and tissues, data are generated and collected based on cell type [116].”