Evidence map›Paper›PMID 30260564›Full record

ArticleProteomics2018

Identification of Moonlighting Proteins in Genomes Using Text Mining Techniques.

Aashish Jain, Hareesh Gali, Daisuke Kihara

Abstract read
In one paragraph

Article in Proteomics, 2018. 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

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

3 citing papers in PubMed.

  1. Article
  2. Multiple Forms of Multifunctional Proteins in Health and Disease.Frontiers in cell and developmental biology · 2020
    Review
  3. 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

3 authors.

Aashish JainDepartment of Biological Science, Purdue University, West Lafayette, IN, 47907, USA.
Hareesh GaliDepartment of Computer Science, Purdue University, West Lafayette, IN, 47907, USA.
Daisuke KiharaDepartment of Biological Science, Purdue University, West Lafayette, IN, 47907, USA.ORCID 0000-0003-4091-6614

Funding

Structural Modeling of Multifarious Protein ComplexesR01GM123055 · NIGMS · PURDUE UNIVERSITY · PI KIHARA, DAISUKE · 2017 to 2020
$1.2M
NIGMS NIH HHS R01 GM123055NIGMS NIH HHS R01GM123055
6 · The paper itself

Abstract

Moonlighting proteins is an emerging concept for considering protein functions, which indicate proteins with two or more independent and distinct functions. An increasing number of moonlighting proteins have been reported in the past years; however, a systematic study of the topic has been hindered because the secondary functions of proteins are usually found serendipitously by experiments. Toward systematic identification and study of moonlighting proteins, computational methods for identifying moonlighting proteins from several different information sources, database entries, literature, and large-scale omics data have been developed. In this study, an overview for finding moonlighting proteins is discussed. Then, the literature-mining method, DextMP, is applied to find new moonlighting proteins in three genomes, Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. Potential moonlighting proteins identified by DextMP are further examined by a two-step manual literature checking procedure, which finally yielded 13 new moonlighting proteins. Identified moonlighting proteins are categorized into two classes based on the clarity of the distinctness of two functions of the proteins. A few cases of the identified moonlighting proteins are described in detail. Further direction for improving the DextMP algorithm is also discussed.

Indexed as

AnimalsArabidopsisCaenorhabditis elegansData MiningDrosophila melanogasterGenomicsbifunctional proteinsfunctional genomicsmoonlighting proteinsprotein function annotationtext mining

Identifiers

PMID30260564
PMCPMC6404977

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.