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Geoffrey J. Faulkner

Researcher at University of Queensland

Publications -  90
Citations -  16644

Geoffrey J. Faulkner is an academic researcher from University of Queensland. The author has contributed to research in topics: Retrotransposon & Genome. The author has an hindex of 43, co-authored 83 publications receiving 14957 citations. Previous affiliations of Geoffrey J. Faulkner include University of Edinburgh & Washington University in St. Louis.

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Journal ArticleDOI

The Transcriptional Landscape of the Mammalian Genome

Piero Carninci, +197 more
- 02 Sep 2005 - 
TL;DR: Detailed polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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A promoter-level mammalian expression atlas

Alistair R. R. Forrest, +280 more
- 27 Mar 2014 - 
TL;DR: For example, the authors mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body.
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Bellerophon: a program to detect chimeric sequences in multiple sequence alignments

TL;DR: Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments.
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Analyses of pig genomes provide insight into porcine demography and evolution

Martien A. M. Groenen, +141 more
- 15 Nov 2012 - 
TL;DR: The assembly and analysis of the genome sequence of a female domestic Duroc pig and a comparison with the genomes of wild and domestic pigs from Europe and Asia reveal a deep phylogenetic split between European and Asian wild boars ∼1 million years ago.
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Stem cell transcriptome profiling via massive-scale mRNA sequencing.

TL;DR: A massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, is developed, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that the understanding of transcriptional complexity is far from complete.