Evidence map›Paper›PMID 34236663›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Protein Subcellular Localization Prediction.

Elettra Barberis, Emilio Marengo, Marcello Manfredi

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Genome-Wide Analysis of theInternational journal of molecular sciences · 2025
    Article
  3. Article
  4. Article
  5. Protein subcellular localization prediction tools.Computational and structural biotechnology journal · 2024
    Review
  6. Article
  7. Article
  8. Article
  9. Review
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

3 authors.

Elettra BarberisDepartment of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Emilio MarengoDepartment of Sciences and Technological Innovation, University of Piemonte Orientale, Alessandria, Italy.
Marcello ManfrediDepartment of Translational Medicine, University of Piemonte Orientale, Novara, Italy. marcello.manfredi@uniupo.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elucidation of the subcellular localization of proteins is very important in order to deeply understand their functions. In fact, proteins activities are strictly correlated to the cellular compartment and microenvironment in which they are present.In recent years, several effective and reliable proteomics techniques and computational methods have been developed and implemented in order to identify the proteins subcellular localization. This process is often time-consuming and expensive, but the recent technological and bioinformatics progress allowed the development of more accurate and simple workflows to determine the localization, interactions, and functions of proteins.In the following chapter, a brief introduction on the importance of knowing subcellular localization of proteins will be presented. Then, sample preparation protocols, proteomic methods, data analysis strategies, and software for the prediction of proteins localization will be presented and discussed. Finally, the more recent and advanced spatial proteomics techniques will be shown.

Indexed as

ProteomicsProteinsProtein TransportSoftwareSubcellular FractionsProteinsProtein subcellular localization predictionSample preparation protocolsSoftware for predictionSpatial proteomics

Identifiers

PMID34236663

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.