Evidence map›Paper›PMID 34709562›Full record

ArticleNeuroinformatics2022

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience.

João P G Santos, Kadri Pajo, Daniel Trpevski, Andrey Stepaniuk, Olivia Eriksson, Anu G Nair, Daniel Keller, Jeanette Hellgren Kotaleski, Andrei Kramer

Abstract read
In one paragraph

Article in Neuroinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Pre- and Post-synaptic Mechanisms of Neuronal Inhibition Assessed Through Biochemically Detailed Modeling of GABAThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  2. Article
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

9 authors.

João P G Santos *Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-0395-039X
Kadri Pajo *Department of Neuroscience, Karolinska Institute, 17165, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-2110-7889
Daniel TrpevskiScience for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-9068-6744
Andrey StepaniukBlue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-2543-4820
Olivia ErikssonScience for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-0740-4318
Anu G NairDepartment of Neuroscience, Karolinska Institute, 17165, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-1952-9583
Daniel KellerBlue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID http://orcid.org/0000-0003-3280-6255
Jeanette Hellgren KotaleskiScience for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044, Stockholm, Sweden. jeanette@kth.se.ORCID http://orcid.org/0000-0002-0550-0739
Andrei KramerScience for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 10044, Stockholm, Sweden. andreikr@kth.se.ORCID http://orcid.org/0000-0002-3828-6978

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a variety of different software tools in the model building and analysis process. Here we focus on the scale of biochemical pathways, which is one of the main objects of study in systems biology. While systems biology is among the more standardized fields, conversion between different model formats and interoperability between various tools is still somewhat problematic. To offer our take on tackling these shortcomings and by keeping in mind the FAIR (findability, accessibility, interoperability, reusability) data principles, we have developed a workflow for building and analyzing biochemical pathway models, using pre-existing tools that could be utilized for the storage and refinement of models in all phases of development. We have chosen the SBtab format which allows the storage of biochemical models and associated data in a single file and provides a human readable set of syntax rules. Next, we implemented custom-made MATLAB® scripts to perform parameter estimation and global sensitivity analysis used in model refinement. Additionally, we have developed a web-based application for biochemical models that allows simulations with either a network free solver or stochastic solvers and incorporating geometry. Finally, we illustrate convertibility and use of a biochemical model in a biophysically detailed single neuron model by running multiscale simulations in NEURON. Using this workflow, we can simulate the same model in three different simulators, with a smooth conversion between the different model formats, enhancing the characterization of different aspects of the model.

Indexed as

NeurosciencesSystems BiologyHumansModels, BiologicalNeuronsSoftwareWorkflowGlobal sensitivity analysisInteroperabilityMultiscale modelingParameter estimationSBtabSystems biology

Identifiers

PMID34709562
PMCPMC9537196

What OpenQuestion holds

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LicenceCC BY
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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.