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Related Concept Videos

Prediction Intervals01:03

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Conservation of Protein Domains02:26

Conservation of Protein Domains

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End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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Related Experiment Video

Updated: Jun 16, 2026

Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench

Published on: August 23, 2017

DomSVR: domain boundary prediction with support vector regression from sequence information alone.

Peng Chen1, Chunmei Liu, Legand Burge

  • 1Department of Systems and Computer Science, Howard University, 2400 Sixth Street, NW, Washington, DC 20059, USA. pchen1978@gmail.com

Amino Acids
|February 19, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for identifying protein domain boundaries using sequence information. The approach offers a simpler and faster way to understand protein structures and functions.

Related Experiment Videos

Last Updated: Jun 16, 2026

Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench

Published on: August 23, 2017

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Protein domains are key structural and functional units.
  • Identifying protein domain boundaries aids in understanding protein evolution, structure, function, and classification.

Purpose of the Study:

  • To develop a novel method for protein domain boundary identification.
  • To improve upon existing methods for predicting domain boundaries.

Main Methods:

  • A support vector regression-based method was employed.
  • Novel input profiles were extracted from the AAindex database.
  • The method relies solely on protein sequence information.

Main Results:

  • The proposed method achieved an average sensitivity of approximately 36.5% and an average specificity of approximately 81% for multi-domain protein chains.
  • Performance was superior to previously published approaches for domain boundary identification.

Conclusions:

  • The developed method provides a simpler and faster approach to protein domain boundary identification.
  • Sequence-based prediction of domain boundaries is effective and efficient.