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Related Experiment Video

Updated: May 28, 2026

Quantification of Immunostained Caspase-9 in Retinal Tissue

Quantification of Immunostained Caspase-9 in Retinal Tissue

Published on: July 25, 2022

CASP9 target classification.

Lisa N Kinch¹, Shuoyong Shi, Hua Cheng

¹Howard Hughes Medical Institute, University of Texas, Southwestern Medical Center, Dallas, TX 75390-9050, USA. lkinch@chop.swmed.edu

|October 15, 2011

Summary

This summary is machine-generated.

The Critical Assessment of Protein Structure Prediction (CASP9) evaluated 129 protein structures. It refined classification of template-based and free modeling categories, improving protein structure prediction accuracy.

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Area of Science:

Structural Biology
Computational Biology
Bioinformatics

Background:

Protein structure prediction is crucial for understanding biological function.
Accurate tertiary structure prediction remains a significant challenge in bioinformatics.
The Critical Assessment of Protein Structure Prediction (CASP) initiative provides a benchmark for evaluating prediction methods.

Purpose of the Study:

To evaluate protein structure prediction methods in the Critical Assessment of Protein Structure Prediction round 9 (CASP9).
To refine the classification of protein targets into template-based modeling (TBM) and template-free modeling (FM) categories.
To analyze prediction performance and identify challenges in protein structure prediction.

Main Methods:

Evaluation of 129 experimentally determined protein structures from CASP9.
Division of target structures into domain-based evaluation units.
Classification of domains into TBM and FM categories based on template availability and server performance.
Analysis of prediction accuracy and identification of challenging cases.

Main Results:

CASP9 provided a comprehensive assessment of protein structure prediction accuracy.
A refined classification system for TBM and FM categories was developed.
The study identified challenging targets, including those with unusual structural differences or undetectable templates.
Performance analysis revealed areas for improvement in prediction methodologies.

Conclusions:

CASP9 demonstrated progress in protein structure prediction, particularly for template-based modeling.
The refined classification highlights the complexities in distinguishing between TBM and FM categories.
Further development is needed for accurate prediction of novel protein folds and difficult targets.
The CASP assessments continue to drive innovation in computational structural biology.