Tag Archives: encode

It is generally thought that most canonical or non-canonical splicing events involving U2- and U12 spliceosomes occur within nuclear pre-mRNAs. However, the question of whether at least some U12-type splicing occurs in the cytoplasm is still unclear. In recent years ...

The advent of high-throughput RNA sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their ...

June 8th – 10th, 2016 Li Ka Shing Center – Stanford University Hands-on training workshops to learn to navigate, analyze, and integrate ENCODE and mouse        ENCODE data into your research.  No programming experience required. Leading-edge research applications from distinguished invited ...

In addition to detecting novel transcripts and higher dynamic range, a principal claim for RNA-sequencing has been greater replicability, typically measured in sample-sample correlations of gene expression levels. Through a re-analysis of ENCODE data, researchers at Cold Spring Harbor Laboratory ...

July 11, 2016 The 2016 GTEx Project Community Meeting will be held at Stanford University. The meeting will highlight current data sets and types available, various tools being developed for these data types, and results from applying them to the ...

Advances in next-generation sequencing platforms have reshaped the landscape of functional genomic and epigenomic research as well as human genetics studies. Annotation of noncoding regions in the genome with genomic and epigenomic data has facilitated the generation of new, testable ...

Increasing evidence suggests that interactions between regulatory genomic elements play an important role in regulating gene expression. Researchers at Stanford University School of Medicine generated a genome-wide interaction map of regulatory elements in human cells (ENCODE tier 1 cells, K562, ...

Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. Researchers at the KU Leuven Center for Human Genetics developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying ...