The histone modifying complexes PRC2 and TrxG/MLL play pivotal roles in determining the activation state of genes controlling pluripotency, lineage commitment, and cell differentiation. Long non-coding RNAs (lncRNAs) can bind to either complex, and some have been shown to act as modulators of PRC2 or TrxG/MLL activity. Here we show...
Polycomb Repressive Complex 2 (PRC2) function and DNA methylation (DNAme) are typically correlated with gene repression. Here, we show that PRC2 is required to maintain expression of maternal microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) from the Gtl2-Rian-Mirg locus, which is essential for full pluripotency of iPSCs. In the absence...
Polycomb Repressive Complex 2 (PRC2) function and DNA methylation (DNAme) are typically correlated with gene repression. Here, we show that PRC2 is required to maintain expression of maternal microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) from the Gtl2-Rian-Mirg locus, which is essential for full pluripotency of iPSCs. In the absence...
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Shen, Richard I. Gregory, George Q. Daley, Alexander
Meissner, ManolisKellis, Konrad Hochedlinger
Polycomb Repressive Complex 2 (PRC2) function and DNA methylation (DNAme) are typically correlated with gene repression. Here, we show that PRC2 is required to maintain expression of maternal microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) from the Gtl2-Rian-Mirg locus, which is essential for full pluripotency of iPSCs. In the absence...
Full Text:
Meissner,4,7 ManolisKellis,3 Konrad Hochedlinger,2,4,5 Jonghwan Kim,1,16
and Stuart H. Orkin1,2
We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
Gene regulation is a complex mechanism that controls the spatial and temporal expression of genes in a living cell. My dissertation studies focus on two problems. First, tissue-specific gene expression prediction from DNA sequence and chromatin state, and second, the accurate discovery of small over-represented regulatory circuits in gene regulatory...
Systems biology is a powerful approach which considers and sheds light on all of the puzzle pieces which make up complex biological processes, and is an effective alternative to unraveling these processes using traditional molecular approaches alone. It is a natural companion approach for computational biology, which leverages the power...
Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...