Predicting protein lysine phosphoglycerylation sites by hybridizing many sequence based features-Reference-Cited by-同舟云学术

Predicting protein lysine phosphoglycerylation sites by hybridizing many sequence based features

Published:2017 Issue:5 Volume:13 Page:874-882
ISSN:1742-206X
Container-title:Molecular BioSystems
language:en
Short-container-title:Mol. BioSyst.

Author:

Chen Qing-Yun¹²³⁴,Tang Jijun¹²³⁴⁵,Du Pu-Feng¹²³⁴^ORCID

Affiliation:

1. School of Computer Science and Technology

2. Tianjin University

3. Tianjin 300350

4. China

5. School of Computational Science and Engineering

Abstract

PhoglyPred is an algorithm that can computationally predict protein phosphoglycerylation sites using three different kinds of descriptors.

Publisher

Royal Society of Chemistry (RSC)

Subject

Molecular Biology,Biotechnology

Link

http://pubs.rsc.org/en/content/articlepdf/2017/MB/C6MB00875E

Reference46 articles.

1. D. Voet , J. G.Voet and C. W.Pratt, Fundamentals of Biochemistry: Life at the Molecular Level, Wiley, 2013

2. SUMO wrestling with type 1 diabetes

3. J.-S. Seeler , O.Bischof, K.Nacerddine and A.Dejean, in Acute Promyelocytic Leukemia: Molecular Genetics, Mouse Models and Targeted Therapy, ed. P. P. Pandolfi and P. K. Vogt, Springer Berlin Heidelberg, 2007, pp. 49–71

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting Phosphoglycerylation with Transformer Features and Deep Learning;2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE);2023-12-04

2. KPhogly-RAM:Prediction of Phosphoglycerylation Sites Using Residue Adjacency Matrix;2022 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE);2022-12-30

3. PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection;Briefings in Bioinformatics;2022-08-04

4. Maximizing Depth of PTM Coverage: Generating Robust MS Datasets for Computational Prediction Modeling;Methods in Molecular Biology;2022

5. ECM-LSE: Prediction of Extracellular Matrix Proteins Using Deep Latent Space Encoding of k-Spaced Amino Acid Pairs;Frontiers in Bioengineering and Biotechnology;2021-10-14