Unlocking the secrets of the genome

By S. Celniker, Laura A. L. Dillon, Mark Gerstein, Kristin C. Gunsalus, Steven Henikoff, G. Karpen, Manolis Kellis, Eric C. Lai, J. Lieb, D. MacAlpine and 6 more. Nature, 2009

848 citations recorded by the source corpus.

Despite the successes of genomics, little is known about how genetic information produces complex organisms. A look at the crucial functional elements of fly and worm genomes could change that. The National Human Genome Research Institute's modENCODE project (the model organism ENCyclopedia Of DNA Elements) was set up in 2007 with the goal of identifying all the sequence-based functional elements in the genomes of two important experimental organisms, Caenorhabditis elegans and Drosophila melanogaster. Armed with modENCODE data, geneticists will be able to undertake the comprehensive molecular studies of regulatory networks that hold the key to how complex multicellular organisms arise from the list of instructions coded in the genome. In this issue, modENCODE team members outline their plan of campaign. Data from the project are to be made available on http://www.modencode.org and elsewhere as the work progresses.

Subfields: Aging, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/758236aa466c7cfd872bd3ab631c3e3da74a575d

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Citations in the corpus

DeepChrome: deep-learning for predicting gene expression from histone modifications (2016, neutral): “In contrast, to our knowledge, a deep learning framework has not yet been explored f r the task of understanding the combinatorial effect of histone modifications on gene regulation.”
The case for cloud computing in genome informatics (2010, background): “Projects like ENCODE [26] and modENCODE [27], which use next generation sequencing for high-resolution mapping of epigenetic marks, chromatin-binding proteins and other functional elements, are currently generating raw sequence at tremendous rates.”
Piercing the dark matter: bioinformatics of long-range sequencing and mapping (2018, background): “These second-generation technologies have enabled the sequencing of many new genomes and widespread resequencing efforts to analyse genomic diversity 2 and pathogenic variants 3 , as well as extensive studies of transcription, gene regulation and epigenetics in many species 4,5 .”
Data integration in the era of omics: current and future challenges (2014, background): “Scientists have acknowledged that biological systems cannot be understood by the analysis of single-type datasets as the regulation of the system certainly occurs at many levels (see [29,44] and in this supplement [45]).”