Evidence map›Paper›PMID 33582139›Full record

ArticleBiophysical journal2021

EGGTART: A tool to visualize the dynamics of biophysical transport under the inhomogeneous l-TASEP.

Dan D Erdmann-Pham, Wonjun Son, Khanh Dao Duc, Yun S Song

Abstract read
In one paragraph

Article in Biophysical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dan D Erdmann-PhamDepartment of Mathematics, University of California, Berkeley, California.
Wonjun SonDepartment of Computer Science, Columbia University, New York, New York.
Khanh Dao DucDepartment of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada. Electronic address: kdd@math.ubc.ca.
Yun S SongComputer Science Division, University of California, Berkeley, California; Department of Statistics, University of California, Berkeley, California; Chan Zuckerberg Biohub, San Francisco, California. Electronic address: yss@berkeley.edu.

Funding

Robust and efficient statistical inference methods for genomicsR35GM134922 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI SONG, YUN S · 2020 to 2024
$2.0M
NIGMS NIH HHS R35 GM134922
6 · The paper itself

Abstract

The totally asymmetric simple exclusion process (TASEP), which describes the stochastic dynamics of interacting particles on a lattice, has been actively studied over the past several decades and applied to model important biological transport processes. Here, we present a software package, called EGGTART (Extensive GUI gives TASEP-realization in Real Time), which quantifies and visualizes the dynamics associated with a generalized version of the TASEP with an extended particle size and heterogeneous jump rates. This computational tool is based on analytic formulas obtained from deriving and solving the hydrodynamic limit of the process. It allows an immediate quantification of the particle density, flux, and phase diagram, as a function of a few key parameters associated with the system, which would be difficult to achieve via conventional stochastic simulations. Our software should therefore be of interest to biophysicists studying general transport processes and can in particular be used in the context of gene expression to model and quantify mRNA translation of different coding sequences.

Indexed as

Protein BiosynthesisBiological TransportBiophysics

Identifiers

PMID33582139
PMCPMC8105713

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.