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Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding

Overview of attention for article published in BMC Genomics, January 2017
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Title
Modular combinatorial binding among human trans-acting factors reveals direct and indirect factor binding
Published in
BMC Genomics, January 2017
DOI 10.1186/s12864-016-3434-3
Pubmed ID
Authors

Yuchun Guo, David K. Gifford

Abstract

The combinatorial binding of trans-acting factors (TFs) to the DNA is critical to the spatial and temporal specificity of gene regulation. For certain regulatory regions, more than one regulatory module (set of TFs that bind together) are combined to achieve context-specific gene regulation. However, previous approaches are limited to either pairwise TF co-association analysis or assuming that only one module is used in each regulatory region. We present a new computational approach that models the modular organization of TF combinatorial binding. Our method learns compact and coherent regulatory modules from in vivo binding data using a topic model. We found that the binding of 115 TFs in K562 cells can be organized into 49 interpretable modules. Furthermore, we found that tens of thousands of regulatory regions use multiple modules, a structure that cannot be observed with previous hard clustering based methods. The modules discovered recapitulate many published protein-protein physical interactions, have consistent functional annotations of chromatin states, and uncover context specific co-binding such as gene proximal binding of NFY + FOS + SP and distal binding of NFY + FOS + USF. For certain TFs, the co-binding partners of direct binding (motif present) differs from those of indirect binding (motif absent); the distinct set of co-binding partners can predict whether the TF binds directly or indirectly with up to 95% accuracy. Joint analysis across two cell types reveals both cell-type-specific and shared regulatory modules. Our results provide comprehensive cell-type-specific combinatorial binding maps and suggest a modular organization of combinatorial binding.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
France 1 1%
Unknown 75 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 34%
Researcher 14 18%
Student > Master 13 17%
Student > Bachelor 8 10%
Student > Doctoral Student 6 8%
Other 6 8%
Unknown 4 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 44%
Biochemistry, Genetics and Molecular Biology 20 26%
Computer Science 8 10%
Medicine and Dentistry 5 6%
Physics and Astronomy 1 1%
Other 3 4%
Unknown 6 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 November 2018.
All research outputs
#7,741,906
of 23,543,207 outputs
Outputs from BMC Genomics
#3,706
of 10,789 outputs
Outputs of similar age
#142,831
of 423,376 outputs
Outputs of similar age from BMC Genomics
#92
of 227 outputs
Altmetric has tracked 23,543,207 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,789 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 423,376 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 227 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.