Evidence map›Paper›PMID 34071282›Full record

ReviewMicroorganisms2021

Molecular Microbial Community Analysis as an Analysis Tool for Optimal Biogas Production.

Seyedbehnam Hashemi, Sayed Ebrahim Hashemi, Kristian M Lien, Jacob J Lamb

Abstract readReview
In one paragraph

Review in Microorganisms, 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

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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

4 authors.

Seyedbehnam HashemiDepartment of Energy and Process Engineering & Enersense, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.
Sayed Ebrahim HashemiDepartment of Energy and Process Engineering & Enersense, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.
Kristian M LienDepartment of Energy and Process Engineering & Enersense, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.
Jacob J LambDepartment of Energy and Process Engineering & Enersense, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.ORCID 0000-0002-1019-6655

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The microbial diversity in anaerobic digestion (AD) is important because it affects process robustness. High-throughput sequencing offers high-resolution data regarding the microbial diversity and robustness of biological systems including AD; however, to understand the dynamics of microbial processes, knowing the microbial diversity is not adequate alone. Advanced meta-omic techniques have been established to determine the activity and interactions among organisms in biological processes like AD. Results of these methods can be used to identify biomarkers for AD states. This can aid a better understanding of system dynamics and be applied to producing comprehensive models for AD. The paper provides valuable knowledge regarding the possibility of integration of molecular methods in AD. Although meta-genomic methods are not suitable for on-line use due to long operating time and high costs, they provide extensive insight into the microbial phylogeny in AD. Meta-proteomics can also be explored in the demonstration projects for failure prediction. However, for these methods to be fully realised in AD, a biomarker database needs to be developed.

Indexed as

anaerobic digetionbiogascommunity diversitymetabolomicsmicrobial diversitynext generation sequencingproteomics

Identifiers

PMID34071282
PMCPMC8226781

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.