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HumDLoc: Human Protein Subcellular Localization Prediction Using Deep Neural Network.

Rahul Semwal1, Pritish Kumar Varadwaj1

  • 11Department of Information Technology (Bioinformatics), Indian Institute of Information Technology-Allahabad, Jhalwa, Prayagraj, India; 2Department of Bioinformatics and Applied Science, Indian Institute of Information Technology-Allahabad, Jhalwa, Prayagraj, India.

Current Genomics
|November 20, 2020
PubMed
Summary

A new tool, HumDLoc, accurately predicts human protein subcellular localization using sequence-based features. This machine learning model surpasses existing methods in precision and recall for proteomic research.

Keywords:
Bioinformaticsdeep learningdeep neural networkhuman proteinmachine learningsubcellular localization

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput human proteomics projects generate vast amounts of protein sequence data.
  • Accurate annotation of protein function and biological roles is crucial.
  • Subcellular localization is a key determinant of protein function.

Purpose of the Study:

  • To develop an automated and reliable tool for predicting human protein subcellular localization.
  • To create a machine learning-based model for high-accuracy protein localization annotation.

Main Methods:

  • Utilized sequence-based features and the PSI-CD-HIT homology criterion.
  • Developed the HumDLoc model using a dataset from the Uniprot knowledge base.
  • Trained the model to generalize effectively on unseen protein sequences.

Main Results:

  • HumDLoc demonstrated high predictive performance, achieving ≥97.00% accuracy.
  • The model showed strong precision (≥0.86) and recall (≥0.89).
  • Evaluated using MCC score (≥0.86), ROC curve (0.98), and precision-recall curve (0.93).

Conclusions:

  • HumDLoc outperformed alternative tools in predicting human protein subcellular localization.
  • The developed model offers a reliable solution for current proteomic research needs.
  • HumDLoc is available as a web-based tool for public use.