12 Questions
What is the main requirement for homology based predictions to be done?
Known structure of homologous protein is required
What is the main principle behind Ab initio predictions?
Predicts structure based on principles of thermodynamics and physicochemical theory
Which experimental method is the most accurate for predicting protein structures?
X-ray crystallography
What is Sensitivity in assessing prediction quality?
Sensitivity measures what share of the actual positives are predicted
What is Specificity in assessing prediction quality?
Specificity measures what share of the predicted values are true
What does Q3 Assessment measure?
Q3 Assessment measures the accuracy of individual amino acids
What does Sov measure in terms of structure prediction?
Sov measures the percentage of correctly predicted secondary structures.
When does Sov perform poorly?
Sov performs poorly when overlapping segments between predicted and observed structures are very fragmented.
What does a high RMSD value indicate in structure prediction?
A high RMSD value indicates more discrepancies between observed and predicted structures.
Why should the test dataset in machine learning not be homologous to the training set?
To avoid performance bias, the test dataset should not be homologous to the training set.
What does adding noise in machine learning aim to prevent?
Adding noise aims to prevent overfitting by introducing variation in predictions.
What concept in machine learning tries to avoid overfitting?
Adding noise helps in avoiding overfitting in machine learning.
Test your knowledge on homology-based predictions and ab initio methods for protein structure prediction. Learn about the requirements for homology-based predictions and the principles behind ab initio modeling. Explore potential issues and differences between the two approaches.
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