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Related Experiment Video

Updated: Jul 19, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing
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Protein Sequencing with Artificial Intelligence: Machine Learning Integrated Phosphorene Nanoslit.

Sneha Mittal1, Milan Kumar Jena1, Biswarup Pathak1

  • 1Department of Chemistry, Indian Institute of Technology (IIT) Indore, Indore, Madhya Pradesh, 453552, India.

Chemistry (Weinheim an Der Bergstrasse, Germany)
|August 7, 2023
PubMed
Summary

Researchers developed a novel phosphorene nanoslit biosensor for rapid, high-throughput protein sequencing. This advanced sensor accurately identifies all twenty amino acids, paving the way for faster biomolecule analysis and disease diagnosis.

Keywords:
artificial intelligencemachine learningphosphorene nanoslitprotein sequencingtransmission

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Area of Science:

  • Materials Science
  • Biotechnology
  • Computational Chemistry

Background:

  • High-throughput protein sequencing at single-molecule resolution is a significant challenge in molecular biology and diagnostics.
  • Current methods often lack the speed and sensitivity required for comprehensive analysis of all amino acids.

Purpose of the Study:

  • To develop a novel biosensor for rapid identification of all twenty amino acids at single-molecule resolution.
  • To leverage machine learning and advanced materials for enhanced protein sequencing capabilities.

Main Methods:

  • Utilized a solid-state 2D phosphorene nanoslit device as a biosensor.
  • Employed an interpretable machine learning (ML) model, specifically the XGBoost regression algorithm, for data analysis.
  • Conducted density functional theory (DFT) studies to understand molecular interactions and signal generation.

Main Results:

  • Achieved accurate determination of transmission functions for all twenty amino acids using the XGBoost model.
  • Demonstrated high sensitivity and selectivity in identifying individual amino acids through transmission and current signal readouts.
  • Showcased a 20-fold increase in transmission sensitivity compared to graphene nanoslit devices.

Conclusions:

  • The phosphorene nanoslit biosensor offers a promising platform for high-throughput screening of amino acids.
  • This technology has the potential to significantly advance protein sequencing and biomolecule analysis for disease diagnosis and therapeutic decision-making.