L
Leah O. Barrera
Researcher at University of California, San Diego
Publications - 6
Citations - 3620
Leah O. Barrera is an academic researcher from University of California, San Diego. The author has contributed to research in topics: ChIA-PET & Promoter. The author has an hindex of 6, co-authored 6 publications receiving 3352 citations. Previous affiliations of Leah O. Barrera include Ludwig Institute for Cancer Research.
Papers
More filters
Journal ArticleDOI
Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome.
Nathaniel D. Heintzman,Rhona K. Stuart,Gary C. Hon,Yutao Fu,Christina W. Ching,R. David Hawkins,Leah O. Barrera,Sara Van Calcar,Chunxu Qu,Keith A. Ching,Wei Wang,Zhiping Weng,Roland Green,Gregory E. Crawford,Bing Ren +14 more
TL;DR: Insight is given into the connections between chromatin modifications and transcriptional regulatory activity and a novel functional enhancer for the carnitine transporter SLC22A5 (OCTN2) is uncovered, providing a new tool for the functional annotation of the human genome.
Journal ArticleDOI
The transcriptional regulatory code of eukaryotic cells – insights from genome-wide analysis of chromatin organization and transcription factor binding
Leah O. Barrera,Bing Ren +1 more
TL;DR: The rapidly growing number of maps has revealed the dynamic nature of nucleosome composition and chromatin remodeling at regulatory regions and highlighted some unexpected properties of transcriptional regulatory networks in eukaryotic cells.
Journal ArticleDOI
Direct isolation and identification of promoters in the human genome
Tae Hoon Kim,Leah O. Barrera,Chunxu Qu,Sara Van Calcar,Nathan D. Trinklein,Sara J. Cooper,Rosa Luna,Christopher K. Glass,Michael G. Rosenfeld,Richard M. Myers,Bing Ren +10 more
TL;DR: The results demonstrate the specificity of a genome-wide analysis method for mapping transcriptional regulatory elements and also indicate that a small, yet significant number of human genes remains to be discovered.
Journal ArticleDOI
ChIP-chip: Data, Model, and Analysis
TL;DR: The ChIP‐chip process is described and a model‐based method for recognizing the peak shapes for the purpose of detecting protein‐binding sites is proposed, and the issue of bandwidth in nonparametric kernel smoothing method is investigated.
ChIP-chip: Data, Model, and Analysis
TL;DR: In this paper, the authors present a probability theory for modeling ChIP-chip data and propose a model-based computational method for locating and testing peaks for the purpose of identifying potential protein binding sites.