Transcription factors: from enhancer binding to developmental control
By F. Spitz, E. Furlong. Nature reviews genetics, 2012
2,153 citations recorded by the source corpus.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/915d392561047b606dfce4c293d44be3f1a8508a
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
- Richard A. Young
- Denes Hnisz
- James E. Bradner
- Tong Ihn Lee
- Aziz Khan
- Lei S. Qi
- Jonathan S. Weissman
- Luke A. Gilbert
Citations in the corpus
- Modification of enhancer chromatin: what, how and why? (2013, background): “Several excellent recent reviews covered role of TFs at enhancers, models of long-range communication, and potential impacts of eRNAs and enhancer transcription (Krivega and Dean, 2012; Lagha et al., 2012; Natoli and Andrau, 2012; Ong and Corces, 2012; Spitz and Furlong, 2012).”
- Selective Inhibition of Tumor Oncogenes by Disruption of Super-Enhancers (2013, background): “The y axis shows the average background subtracted ChIP-seq signal in units of rpm/bp. 322 Cell 153, 320–334, April 11, 2013 ª2013 Elsevier Inc. et al., 2012; Ong and Corces, 2011; Spitz and Furlong, 2012).”
- Transcriptional enhancers: from properties to genome-wide predictions (2014, background): “39 ) such that the binding of only one or a few transcription factors is possibly insufficient to activate transcription.”
- Understanding multicellular function and disease with human tissue-specific networks (2015, positive): “Based on previous work 22 that annotated samples from biological text, we extracted the title and description for each GDS dataset and annotated each using MetaMap 23 .”
- The impact of sex on gene expression across human tissues (2020, background): “However, this scenario cannot be discarded if such differences occur at an earlier developmental time point and translate into a more constitutive sex-biased TF binding profile (23).”
- Learning the human chromatin network from all ENCODE ChIP-seq data (2015, background): “Identifying the genomic co-localization in this network among regulatory factors, the chromatin network, is important for understanding genome regulation and the function of each regulatory factor [60, 4].”
- Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using random Forest (2018, background): “Background Transcription factors (TFs) are proteins which usually bind to genomic DNA at specific DNA sequences (motifs) [1].”
- Ever-changing landscapes: transcriptional enhancers in development and evolution (2016, background): “, less than one nucleosome length) is thought to play amajor role in overcoming the energetic barrier of nucleosome eviction, thus facilitating downstream effector binding and enhancer activation (Spitz and Furlong, 2012).”
- Intervene: a tool for intersection and visualization of multiple gene or genomic region sets (2017, background): “Transcription factors (TFs) are key proteins regulating transcription through their cooperative binding to the DNA [19, 20].”
- ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data (2016, background): “TFs) (39–41), and are critical for elucidating transcriptional regulation of genes (41).”
- Transcriptional Regulation and its Misregulation in Disease (2013, positive): “…leading to a present-day consensus model for selective gene control (Adelman and Lis, 2012; Bannister and Kouzarides, 2011; Bonasio et al., 2010; Conaway and Conaway, 2011; Fuda et al., 2009; Ho and Crabtree, 2010; Roeder, 2005; Spitz and Furlong, 2012; Taatjes, 2010; Zhou et al., 2012b).”
- AnimalTFDB 3.0: a comprehensive resource for annotation and prediction of animal transcription factors (2018, background): “As one of the major regulator types in biological processes or diseases, TFs have been well studied in many aspects, such as functions and regulatory mechanism (9), evolutionary analysis (10), drug targets analysis (11,12), disease or phenotype of TFs (13–15), TF regulatory networks (16), TF target ”
- Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation (2014, background): “These genes include p53-related protein TP73, cell cycle inhibitors CDKN1C (p57) and CDKN1A (p21), apoptotic factors BAK1 and BCL2L11 (BIM), and chromatin remodeling factor ARID1A (Figure 4D and Table S4).”
- Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes (2013, positive): “Enhancers are segments of DNA that are generally a few hundred base pairs in length and are typically occupied by multiple transcription factors (Carey, 1998; Levine and Tjian, 2003; Panne, 2008; Spitz and Furlong, 2012).”