Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities
By M. Berger, A. Philippakis, A. M. Qureshi, F. He, Preston W. Estep, Martha L. Bulyk. Nature Biotechnology, 2006
729 citations recorded by the source corpus.
Subfields: Molecular Biology, Plant Science
View Paper: https://www.semanticscholar.org/paper/682ca569f9cf3f72b090e648991d1ce407da4cae
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Christina S. Leslie
- Ron Shamir
- Martha L. Bulyk
- Roded Sharan
- Trey Ideker
- Yaron Orenstein
- William Stafford Noble
- Michael A. Beer
In Plant Science
- Martha L. Bulyk
- Stijn van Dongen
- Anders Krogh
- Trey Ideker
- William Stafford Noble
- Ron Shamir
- Brendan J. Frey
- Anton J. Enright
Citations in the corpus
- PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants (2015, background): “The development of in vitro protein-binding microarray (PBM) technology has allowed for DNA-binding specificities (10).”
- Diverse RNA-Binding Proteins Interact with Functionally Related Sets of RNAs, Suggesting an Extensive Regulatory System (2008, neutral): “[97,98].”
- Detecting microRNA binding and siRNA off-target effects from expression data (2008, background): “Existing motif discovery methods9-13 are not explicitly designed for this purpose (see Supplementary Discussion online).”
- STAT3 activation of miR-21 and miR-181b-1, via PTEN and CYLD, are part of the epigenetic switch linking inflammation to cancer (2010, methodology): “Position weight matrix (PWM) representations of the PBM data derived using the ‘‘Seed-and-Wobble’’ algorithm (Berger et al., 2006) were used in the Lever analysis.”
- Evaluation of methods for modeling transcription-factor sequence specificity (2013, methodology): “There are arguments for and against both 7, 19, 24 and our comparisons to independent data did not support either as being superior overall (Supplementary Note 2).”
- A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data (2014, methodology): “We used five algorithms to generate PWMs from PBM experiments: Amadeus-PBM (10), Seed-and-Wobble (4), RankMotif++ (15), BEEMLPBM (17) and RAP (18).”
- High Resolution Genome Wide Binding Event Finding and Motif Discovery Reveals Transcription Factor Spatial Binding Constraints (2012, methodology): “We collected known binding preference motifs from the TRANSFAC [50], JASPAR [51], and Uniprobe [52] databases.”
- Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences. (2008, methodology): “PBM assays were performed essentially as described previously (Berger et al., 2006), except that four proteins were simultaneously assayed in separate sectors of a single microarray and scanned with at least three different laser power settings to best capture a broad range of signal intensities…”
- Genome-wide analysis of ETS-family DNA-binding in vitro and in vivo (2010, positive): “Binding reactions were performed with 39–100 nM (see Supplementary Table S1) of protein using PBM array design #015681 essentially as described in Berger et al (2006).”
- Protein networks in disease. (2008, background): “However, despite the availability of human protein–protein interaction networks, large-scale measurements of human transcriptional interactions are still underway, mainly using systematic chromatin immunoprecipitation experiments in human cell lines and in-vitro technologies such as the proteinbindi”