<p>Predictive performance of the four types of zinc-binding residues (CHED) of our method, SitePredict and zincfinder on the 5-fold cross-validation benchmark dataset.</p
<p>ISMBLab-LIG residue-based prediction performances benchmarked with published datasets.</p
The zinc ion is the second richest metal ion in organisms. The proteins binding to zinc ions have im...
<p>Zinc is one the most abundant catalytic cofactor and also an important structural component of a ...
<p>(A) and (B): Recall-Precision and ROC curves for our method; (<b>C</b>) and (<b>D</b>): Recall-Pr...
<p>Znx, where “x” denotes the number of residues that bind to zinc ions. “x” = 1, 2, 3 and 4, respec...
<p>The performance was evaluated using REC, PRE, SPE, AUC and AURPC measures.</p>a<p>Prediction perf...
<p>The performance was evaluated using REC, PRE, SPE, AUC and AURPC measures.</p>a<p>Prediction perf...
<p>Recall-Precision and ROC curves displaying the performance of the three methods at both residue (...
<p>Performance assessment of structural and functional residue predictors using cross-validation on ...
<p>Green and red boxes denote zinc-binding and non-zinc binding residues, respectively. The horizont...
<p>Performance of various methods for DNA-binding protein prediction (leave-one-out cross validation...
<p>Recall-Precision and ROC curves displaying the performance of the three methods at both residue (...
<p>(A) Fraction of NSM sites satisfying various thresholds of recall. (B) Fraction of DPA prediction...
<p>There are four major stages: dataset construction, feature extraction, feature selection and zinc...
Background: Zinc binding proteins make up a significant proportion of the proteomes of most organism...
<p>ISMBLab-LIG residue-based prediction performances benchmarked with published datasets.</p
The zinc ion is the second richest metal ion in organisms. The proteins binding to zinc ions have im...
<p>Zinc is one the most abundant catalytic cofactor and also an important structural component of a ...
<p>(A) and (B): Recall-Precision and ROC curves for our method; (<b>C</b>) and (<b>D</b>): Recall-Pr...
<p>Znx, where “x” denotes the number of residues that bind to zinc ions. “x” = 1, 2, 3 and 4, respec...
<p>The performance was evaluated using REC, PRE, SPE, AUC and AURPC measures.</p>a<p>Prediction perf...
<p>The performance was evaluated using REC, PRE, SPE, AUC and AURPC measures.</p>a<p>Prediction perf...
<p>Recall-Precision and ROC curves displaying the performance of the three methods at both residue (...
<p>Performance assessment of structural and functional residue predictors using cross-validation on ...
<p>Green and red boxes denote zinc-binding and non-zinc binding residues, respectively. The horizont...
<p>Performance of various methods for DNA-binding protein prediction (leave-one-out cross validation...
<p>Recall-Precision and ROC curves displaying the performance of the three methods at both residue (...
<p>(A) Fraction of NSM sites satisfying various thresholds of recall. (B) Fraction of DPA prediction...
<p>There are four major stages: dataset construction, feature extraction, feature selection and zinc...
Background: Zinc binding proteins make up a significant proportion of the proteomes of most organism...
<p>ISMBLab-LIG residue-based prediction performances benchmarked with published datasets.</p
The zinc ion is the second richest metal ion in organisms. The proteins binding to zinc ions have im...
<p>Zinc is one the most abundant catalytic cofactor and also an important structural component of a ...