Pages that link to "Item:Q2261622"
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The following pages link to Predicting ion channels and their types by the dipeptide mode of pseudo amino acid composition (Q2261622):
Displaying 14 items.
- Using weighted features to predict recombination hotspots in \textit{Saccharomyces cerevisiae} (Q739312) (← links)
- Predict potential drug targets from the ion channel proteins based on SVM (Q1629111) (← links)
- Analysis and prediction of ion channel inhibitors by using feature selection and Chou's general pseudo amino acid composition (Q1714359) (← links)
- Two-intermediate model to characterize the structure of fast-folding proteins (Q1783656) (← links)
- Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition (Q1784371) (← links)
- \textbf{iLoc-Virus}: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites (Q1786031) (← links)
- A novel canonical dual computational approach for prion AGAAAAGA amyloid fibril molecular modeling (Q1786044) (← links)
- Studies on the rules of \(\beta\)-strand alignment in a protein \(\beta\)-sheet structure (Q1786068) (← links)
- A new hybrid fractal algorithm for predicting thermophilic nucleotide sequences (Q2263499) (← links)
- Transmission of intra-cellular genetic information: a system proposal (Q2415671) (← links)
- iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints (Q2632182) (← links)
- Analysis and identification of toxin targets by topological properties in protein-protein interaction network (Q2632760) (← links)
- Using long-range contact number information for protein secondary structure prediction (Q2933550) (← links)
- A data-driven explainable case-based reasoning approach for financial risk detection (Q6158390) (← links)
