Computational and Mathematical Methods in Medicine

Developing and Applying Machine Learning-Based Methods in Special Function Protein Identification


Publishing date
01 Apr 2021
Status
Closed
Submission deadline
27 Nov 2020

Lead Editor

1University of Electronic Science and Technology of China, Chengdu, China

2Ajou University School of Medicine, Suwon, Republic of Korea

3Mahidol University, Nakhon Pathom, Thailand

This issue is now closed for submissions.
More articles will be published in the near future.

Developing and Applying Machine Learning-Based Methods in Special Function Protein Identification

This issue is now closed for submissions.
More articles will be published in the near future.

Description

With the development of high-throughput sequencing techniques, increasing amounts of protein data have become available. In these proteins, some display special functions. The knowledge about these proteins could provide an opportunity to explore new targets for disease treatment.

Thus, it is urgent for us to develop computational methods to study and analyze these special functional proteins. As such, more and more scholars have focused on this topic. Some computational methods have been developed for the prediction of protein subcellular localization and the identification of post-translational modification sites. However, the function of many proteins has still not been annotated. As of July 17th 2020, the Uniprot database contains 184,998,855 proteins. However, the database provides the annotation information of only 562,755 proteins. Although some sequence similar algorithms could provide some useful information for these non-annotated proteins, the homologue for many proteins cannot be found in the database. Thus, these similarity-based computational tools cannot give suitable predicted annotation on these proteins. Therefore, machine learning-based methods have increasingly attracted attention.

Due to the rapid development of this field, this Special Issue will mainly focus on the development of machine learning methods to recognize proteins with special functions. We invite authors to contribute original research or review articles in this field.

Potential topics include but are not limited to the following:

  • Development of sequence feature extraction methods in special functional proteins
  • Applying new mathematical methods to formulate special functional protein samples
  • Novel non-sequence feature extraction in special functional protein description
  • Feature fusion in ion channel protein identification
  • Computational methods in cyclin protein prediction
  • Toxin protein prediction and analysis using machine learning methods
  • Receptor protein identification using computational methods
  • Developing new tools for hormone-related protein identification
  • Special enzyme identification using machine learning methods
  • Immunoglobulins recognition

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 6683407
  • - Research Article

Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach

Hasan Zulfiqar | Muhammad Shareef Masoud | ... | Hao Lin
  • Special Issue
  • - Volume 2021
  • - Article ID 6652288
  • - Research Article

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence

Wang-Ren Qiu | Gang Chen | ... | Shou-Hua Zhang
  • Special Issue
  • - Volume 2021
  • - Article ID 6664362
  • - Research Article

iBLP: An XGBoost-Based Predictor for Identifying Bioluminescent Proteins

Dan Zhang | Hua-Dong Chen | ... | Ke-Jun Deng
  • Special Issue
  • - Volume 2021
  • - Article ID 6690299
  • - Research Article

iT3SE-PX: Identification of Bacterial Type III Secreted Effectors Using PSSM Profiles and XGBoost Feature Selection

Chenchen Ding | Haitao Han | ... | Taigang Liu
  • Special Issue
  • - Volume 2021
  • - Article ID 6683051
  • - Research Article

iMPTCE-Hnetwork: A Multilabel Classifier for Identifying Metabolic Pathway Types of Chemicals and Enzymes with a Heterogeneous Network

Yuanyuan Zhu | Bin Hu | ... | Qi Dai
  • Special Issue
  • - Volume 2021
  • - Article ID 6636350
  • - Research Article

iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network

Ang Sun | Xuan Xiao | Zhaochun Xu
  • Special Issue
  • - Volume 2020
  • - Article ID 8845133
  • - Research Article

PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron

Yanjuan Li | Zitong Zhang | ... | Xiaoyan Liu
  • Special Issue
  • - Volume 2020
  • - Article ID 8858489
  • - Research Article

Succinylation Site Prediction Based on Protein Sequences Using the IFS-LightGBM (BO) Model

Lu Zhang | Min Liu | ... | Guangzhong Liu
  • Special Issue
  • - Volume 2020
  • - Article ID 8872329
  • - Research Article

An Integrating Immune-Related Signature to Improve Prognosis of Hepatocellular Carcinoma

Rui Zhu | Wenna Guo | ... | Liucun Zhu
  • Special Issue
  • - Volume 2020
  • - Article ID 8852258
  • - Research Article

Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network

Qingwen Li | Lei Xu | ... | Lichao Zhang
Computational and Mathematical Methods in Medicine
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