Evidence map›Paper›PMID 29508062›Full record

ArticleAmino acids2018

Analysis of fumarate-sensitive proteins and sites by exploiting residue interaction networks.

Gianluca Miglio

Abstract read
PubMed Publisher
In one paragraph

Article in Amino acids, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Gianluca MiglioDipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria, 9, Turin, Italy. gianluca.miglio@unito.it.ORCID http://orcid.org/0000-0002-6602-2099
University of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fumarate adduction to cysteines has been implicated in the pathogenesis of several disorders. Its role, however, still remains elusive, and the need of predictive methods has not yet been met. The reactivity of cysteines found in fumarate-sensitive proteins was predicted when the collected data for eight network-type features were analyzed using classification models. Therefore, methods for evaluating the likelihood of a cysteine site to be modified by fumarate could be developed by combining concepts of network theory and machine learning.

Indexed as

Databases, ProteinSequence Analysis, ProteinCysteineFumaratesProteinsCysteineFumaratesfumaric acidProteinsCysteine reactivityFumarateProtein succinationResidue interaction network

Identifiers

PMID29508062
OpenAlexW2790553025

What OpenQuestion holds

Textmetadata
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.