↓ Skip to main content

PLOS

Statistical Analysis of Molecular Signal Recording

Overview of attention for article published in PLoS Computational Biology, July 2013
Altmetric Badge

Mentioned by

twitter
17 X users
facebook
1 Facebook page
googleplus
2 Google+ users

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
108 Mendeley
citeulike
1 CiteULike
Title
Statistical Analysis of Molecular Signal Recording
Published in
PLoS Computational Biology, July 2013
DOI 10.1371/journal.pcbi.1003145
Pubmed ID
Authors

Joshua I. Glaser, Bradley M. Zamft, Adam H. Marblestone, Jeffrey R. Moffitt, Keith Tyo, Edward S. Boyden, George Church, Konrad P. Kording

Abstract

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a "molecular ticker tape", in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
France 1 <1%
Austria 1 <1%
United Kingdom 1 <1%
Netherlands 1 <1%
Spain 1 <1%
Taiwan 1 <1%
Japan 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 97 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 23%
Researcher 22 20%
Student > Bachelor 15 14%
Professor > Associate Professor 11 10%
Professor 8 7%
Other 20 19%
Unknown 7 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 29%
Neuroscience 23 21%
Biochemistry, Genetics and Molecular Biology 9 8%
Engineering 9 8%
Computer Science 5 5%
Other 21 19%
Unknown 10 9%