Evidence map›Paper›PMID 35696083›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Systematic Characterization of Lysine Post-translational Modification Sites Using MUscADEL.

Zhen Chen, Xuhan Liu, Fuyi Li, Chen Li, Tatiana Marquez-Lago, André Leier, Geoffrey I Webb, Dakang Xu, Tatsuya Akutsu, Jiangning Song

Abstract read
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Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

10 authors.

Zhen ChenKey Laboratory of Rice Biology in Henan Province, Henan Agricultural University, Zhengzhou, China.
Xuhan LiuDrug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.
Fuyi LiDepartment of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, VIC, Australia.
Chen LiBiomedicine Discovery Institute, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia.
Tatiana Marquez-LagoDepartment of Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
André LeierDepartment of Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
Geoffrey I WebbMonash Centre for Data Science, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia.
Dakang XuFaculty of Medical Laboratory Science, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Tatsuya AkutsuBioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan. takutsu@kuicr.kyoto-u.ac.jp.
Jiangning SongBiomedicine Discovery Institute, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia. jiangning.song@monash.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among various types of protein post-translational modifications (PTMs), lysine PTMs play an important role in regulating a wide range of functions and biological processes. Due to the generation and accumulation of enormous amount of protein sequence data by ongoing whole-genome sequencing projects, systematic identification of different types of lysine PTM substrates and their specific PTM sites in the entire proteome is increasingly important and has therefore received much attention. Accordingly, a variety of computational methods for lysine PTM identification have been developed based on the combination of various handcrafted sequence features and machine-learning techniques. In this chapter, we first briefly review existing computational methods for lysine PTM identification and then introduce a recently developed deep learning-based method, termed MUscADEL (Multiple Scalable Accurate Deep Learner for lysine PTMs). Specifically, MUscADEL employs bidirectional long short-term memory (BiLSTM) recurrent neural networks and is capable of predicting eight major types of lysine PTMs in both the human and mouse proteomes. The web server of MUscADEL is publicly available at http://muscadel.erc.monash.edu/ for the research community to use.

Indexed as

LysineProtein Processing, Post-TranslationalAmino Acid SequenceAnimalsMachine LearningMiceProteomeLysineProteomeBioinformaticsDeep learningLong short-term memoryLysineMachine learningPost-translational modification

Identifiers

PMID35696083

What OpenQuestion holds

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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.