The following pages link to iPro54-PseKNC (Q34203):
Displaying 33 items.
- Predicting Golgi-resident protein types using pseudo amino acid compositions: approaches with positional specific physicochemical properties (Q304850) (← links)
- pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach (Q305612) (← links)
- Discriminate protein decoys from native by using a scoring function based on ubiquitous phi and psi angles computed for all atom (Q738564) (← links)
- Machine learning approaches for discrimination of extracellular matrix proteins using hybrid feature space (Q738768) (← links)
- Identify five kinds of simple super-secondary structures with quadratic discriminant algorithm based on the chemical shifts (Q739232) (← links)
- Using weighted features to predict recombination hotspots in \textit{Saccharomyces cerevisiae} (Q739312) (← links)
- Classification of membrane protein types using voting feature interval in combination with Chou's pseudo amino acid composition (Q739723) (← links)
- iLM-2L: a two-level predictor for identifying protein lysine methylation sites and their methylation degrees by incorporating K-gap amino acid pairs into Chou's general PseAAC (Q739749) (← links)
- RBSURFpred: modeling protein accessible surface area in real and binary space using regularized and optimized regression (Q1635544) (← links)
- IMem-2LSAAC: a two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into Chou's pseudo amino acid composition (Q1649407) (← links)
- Classify vertebrate hemoglobin proteins by incorporating the evolutionary information into the general PseAAC with the hybrid approach (Q1664426) (← links)
- Prediction of metastasis in advanced colorectal carcinomas using CGH data (Q1704333) (← links)
- BlaPred: predicting and classifying \(\beta\)-lactamase using a 3-tier prediction system via Chou's general PseAAC (Q1712641) (← links)
- Predicting apoptosis protein subcellular localization by integrating auto-cross correlation and PSSM into Chou's PseAAC (Q1712667) (← links)
- pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC (Q1712835) (← links)
- Large-scale frequent stem pattern mining in RNA families (Q1714283) (← links)
- iMethyl-STTNC: identification of N\(^6\)-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences (Q1714298) (← links)
- Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC (Q1714327) (← links)
- Convex hull analysis of evolutionary and phylogenetic relationships between biological groups (Q1714357) (← links)
- Analysis and prediction of ion channel inhibitors by using feature selection and Chou's general pseudo amino acid composition (Q1714359) (← links)
- iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC (Q1716822) (← links)
- Fu-SulfPred: identification of protein S-sulfenylation sites by fusing forests via Chou's general PseAAC (Q1716873) (← links)
- Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC (Q1716885) (← links)
- pSSbond-PseAAC: prediction of disulfide bonding sites by integration of PseAAC and statistical moments (Q1717058) (← links)
- Analysis and prediction of animal toxins by various Chou's pseudo components and reduced amino acid compositions (Q1717294) (← links)
- SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins (Q1734238) (← links)
- Prediction of interface residue based on the features of residue interaction network (Q1747711) (← links)
- Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC (Q1747718) (← links)
- Bi-PSSM: position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins (Q1749056) (← links)
- Prediction of aptamer-protein interacting pairs based on sparse autoencoder feature extraction and an ensemble classifier (Q2328398) (← links)
- Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach (Q2400938) (← links)
- VR-BFDT: a variance reduction based binary fuzzy decision tree induction method for protein function prediction (Q2630322) (← links)
- Publication:739232 (← links)
