Evidence map›Paper›PMID 33529200›Full record

ArticlePLoS computational biology2021

Finding branched pathways in metabolic network via atom group tracking.

Yiran Huang, Yusi Xie, Cheng Zhong, Fengfeng Zhou

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Yiran HuangSchool of Computer and Electronics and Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning, China.ORCID 0000-0001-6289-8766
Yusi XieSchool of Computer and Electronics and Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning, China.ORCID 0000-0002-7777-8596
Cheng ZhongSchool of Computer and Electronics and Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning, China.ORCID 0000-0002-5560-2151
Fengfeng ZhouCollege of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Finding non-standard or new metabolic pathways has important applications in metabolic engineering, synthetic biology and the analysis and reconstruction of metabolic networks. Branched metabolic pathways dominate in metabolic networks and depict a more comprehensive picture of metabolism compared to linear pathways. Although progress has been developed to find branched metabolic pathways, few efforts have been made in identifying branched metabolic pathways via atom group tracking. In this paper, we present a pathfinding method called BPFinder for finding branched metabolic pathways by atom group tracking, which aims to guide the synthetic design of metabolic pathways. BPFinder enumerates linear metabolic pathways by tracking the movements of atom groups in metabolic network and merges the linear atom group conserving pathways into branched pathways. Two merging rules based on the structure of conserved atom groups are proposed to accurately merge the branched compounds of linear pathways to identify branched pathways. Furthermore, the integrated information of compound similarity, thermodynamic feasibility and conserved atom groups is also used to rank the pathfinding results for feasible branched pathways. Experimental results show that BPFinder is more capable of recovering known branched metabolic pathways as compared to other existing methods, and is able to return biologically relevant branched pathways and discover alternative branched pathways of biochemical interest. The online server of BPFinder is available at http://114.215.129.245:8080/atomic/. The program, source code and data can be downloaded from https://github.com/hyr0771/BPFinder.

Indexed as

AlgorithmsCell Line, TumorComputational BiologyGlutamic AcidHumansLinear ModelsMetabolic EngineeringMetabolic Networks and PathwaysModels, BiologicalOrnithinePredictive Value of TestsReproducibility of ResultsSoftwareSynthetic BiologyGlutamic AcidOrnithine

Identifiers

PMID33529200
PMCPMC7880430

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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.