Evidence map›Paper›PMID 40119888›Full record

ArticleBioprocess and biosystems engineering2025

Genetic algorithm-optimized artificial neural network for multi-objective optimization of biomass and exopolysaccharide production by Haloferax mediterranei.

Alaa M Al Rawahi, Mohd Zafar, Taqi Ahmed Khan, Sara Al Araimi, Biswanath Mahanty, Shishir Kumar Behera

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Article in Bioprocess and biosystems engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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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

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Alaa M Al RawahiDepartment of Applied Biotechnology, College of Applied Sciences and Pharmacy, University of Technology and Applied Sciences - Sur, Sur, Oman.
Mohd ZafarDepartment of Applied Biotechnology, College of Applied Sciences and Pharmacy, University of Technology and Applied Sciences - Sur, Sur, Oman. Mohammed.Zafar@utas.edu.om.
Taqi Ahmed KhanDepartment of Applied Biotechnology, College of Applied Sciences and Pharmacy, University of Technology and Applied Sciences - Sur, Sur, Oman.
Sara Al AraimiDepartment of Applied Biotechnology, College of Applied Sciences and Pharmacy, University of Technology and Applied Sciences - Sur, Sur, Oman.
Biswanath MahantyDivision of Biotechnology, Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore, Tamil Nadu, 641 114, India. bmahanty@karunya.edu.
Shishir Kumar BeheraIndustrial Ecology Research Group, School of Chemical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, 632 014, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial production of industrially important exopolysaccharide (EPS) from extremophiles has several advantages. In this study, key media components (i.e., sucrose, yeast extract, and urea) were optimized for biomass growth and extracellular EPS production in Haloferax mediterranei DSM 1411 using Box-Behnken design. In a multi-objective optimization framework, response surface methodology (RSM) and genetic algorithm (GA)-optimized artificial neural network (ANN) were used to minimize biomass growth while increasing EPS production. The performance of the selected ANN model for the prediction of biomass and EPS (R

Indexed as

AlgorithmsBiomassHaloferax mediterraneiNeural Networks, ComputerPolysaccharides, BacterialGenetic AlgorithmsPolysaccharides, BacterialBox–Behnken designComposite desirabilityGellan gumGenetic algorithmMulti-objective optimization

Identifiers

PMID40119888

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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.