Posts Tagged ‘encode’

ncdriver and ENCODE

Saturday, March 17th, 2018

Received: 13 November 2017 Revised: 22 November 2017 Accepted: 29 November 2017

George Church Medical Info

Saturday, January 6th, 2018
George Church discloses a lot of his medical records

Software Tools – ENCODE

Sunday, October 1st, 2017

The Genomics Landscape: A monthly update from the NHGRI Director – July 2017

Monday, July 10th, 2017

.@Genome_Gov Extramural Grant Portfolio
https://www.Genome.Gov/27569006/july-6-2017-the-nhgri-extramural-grant-portfolio-using-different-approaches-to-fund-genomics-research Nice grid divides programs into PI-initiated/consortia & RFA-solicited v not

promoter/enhancer categorization and Encyclopedia

Saturday, July 1st, 2017

Genome-wide characterization of..promoters w…enhancer functions Blurs distinction betw these, suggests flexibility

Genome-wide characterization of mammalian promoters with distal enhancer functions

Lan T M Dao,
Ariel O Galindo-Albarrán,
Jaime A Castro-Mondragon,
Charlotte Andrieu-Soler,
Alejandra Medina-Rivera,
Charbel Souaid,
Guillaume Charbonnier,
Aurélien Griffon,
Laurent Vanhille,
Tharshana Stephen,
Jaafar Alomairi,
David Martin,
Magali Torres,
Nicolas Fernandez,
Eric Soler,
Jacques van Helden,
Denis Puthier
& Salvatore Spicuglia

Promoting transcription over long distances

Rui R Catarino,
Christoph Neumayr
& Alexander Stark

Nature Genetics 49, 972–973 (2017) doi:10.1038/ng.3904
28 June 2017

“Should we be surprised that promoters can function as enhancers—or better—that enhancers and promoter regions can overlap? Probably not: the habit of annotating different genomic regions with distinct labels ignores the fact that DNA sequences typically encode different genetic functions in a rather flexible manner. Enhancers and promoters are determined by the presence of short degenerate motifs, and even protein-coding regions display flexibility due to the degeneracy of the genetic code. Therefore, a single DNA sequence can encode different types of functions, including enhancer function of protein-coding regions or—as shown now—enhancer function of

Journal Club Paper

Sunday, June 18th, 2017

Zhou, J. and Troyanskaya, O.G. (2015). Predicting effects of noncoding variants with deep learning–based sequence model. Nature Methods, 12, 931–934.

Predicting (& prioritizing) effects of noncoding variants w. [DeepSEA] #DeepLearning…model Trained w #ENCODE data

The dark side of the human genome : Nature : Nature Research

Sunday, November 27th, 2016

Dark side of the..genome QT: NextGen..has been..the tech engine of #ENCODE..but..hi-res livecell imaging [is coming]

Has figure from Khurana et al. Nat. Rev. Genet. (’16)

“Next-generation sequencing has been — and still is — the
technological engine of ENCODE. But looking ahead, researchers might be able to roll out high-resolution live-cell imaging on a large scale to watch the state of the genome change in real time using specific markers. This technology could be disruptive. “If we had a better microscope, we wouldn’t be sequencing anymore,” says

Species-Specific | The Scientist Magazine(R)

Sunday, September 6th, 2015

Scientists uncover striking differences between mouse and human gene expression across a variety of tissues.
By Jyoti Madhusoodanan | November 17, 2014

The results “go a little against the grain,” said bioinformatician Mark Gerstein of Yale University who was not involved in the study. “We might think that humans and mice are very similar [genetically], but when we compare their transcriptomes, they’re more different than we thought.”

Single-cell chromatin accessibility reveals principles of regulatory variation : Nature : Nature Publishing Group

Friday, August 28th, 2015

#SingleCell chromatin accessibility >1.6k ATAC-seq expts; many on @ENCODE_NIH cell lines H1, GM12878 & K562

PLOS Genetics: 8.2% of the Human Genome Is Constrained: Variation in Rates of Turnover across Functional Element Classes in the Human Lineage

Sunday, August 2nd, 2015

While enriched with ENCODE biochemical annotations, much of the short-lived constrained sequences we identify are not detected by models optimized for wider pan-mammalian conservation. Constrained DNase 1 hypersensitivity sites, promoters and untranslated regions have been more evolutionarily stable than long noncoding RNA loci which have turned over especially rapidly. By contrast, protein coding sequence has been highly stable, with an estimated half-life of over a billion years (d1/2 = 2.1–5.0). From extrapolations we estimate that 8.2% (7.1–9.2%) of the human genome is presently subject to negative selection and thus is likely to be functional, while only 2.2% has maintained constraint in both human and mouse since these species diverged.