The following pages link to iNuc-PseKNC (Q28476):
Displaying 31 items.
- Predicting Golgi-resident protein types using pseudo amino acid compositions: approaches with positional specific physicochemical properties (Q304850) (← links)
- An estimator for local analysis of genome based on the minimal absent word (Q306587) (← links)
- Comparison of genomic data via statistical distribution (Q309233) (← links)
- Prediction of Golgi-resident protein types using general form of Chou's pseudo-amino acid compositions: approaches with minimal redundancy maximal relevance feature selection (Q738670) (← 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)
- 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)
- NucPosPred: predicting species-specific genomic nucleosome positioning via four different modes of general PseKNC (Q1642583) (← links)
- Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC (Q1642634) (← 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)
- Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC (Q1714173) (← 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)
- iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC (Q1716822) (← links)
- Prediction of aptamer-protein interacting pairs based on sparse autoencoder feature extraction and an ensemble classifier (Q2328398) (← links)
- A two-layer classification framework for protein fold recognition (Q2351306) (← links)
- Prediction of \(\beta\)-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine (Q2351316) (← links)
- Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model (Q2351334) (← links)
- Distribution bias of the sequence matching between exons and introns in exon joint and EJC binding region in \textit{C. elegans} (Q2413932) (← links)
- fabp4 is central to eight obesity associated genes: a functional gene network-based polymorphic study (Q2413941) (← links)
- A Hooke's law-based approach to protein folding rate (Q2413957) (← links)
- Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction (Q2415547) (← links)
- Constructing a linear QSAR for some metabolizable drugs by human or pig flavin-containing monooxygenases using some molecular features selected by a genetic algorithm trained SVM (Q2415560) (← links)
- Human proteins characterization with subcellular localizations (Q2415647) (← links)
- An effective haplotype assembly algorithm based on hypergraph partitioning (Q2415650) (← links)
- A set of descriptors for identifying the protein-drug interaction in cellular networking (Q2415703) (← links)
- Communities in the iron superoxide dismutase amino acid network (Q2415794) (← links)
- Predicting protein sub-Golgi locations by combining functional domain enrichment scores with pseudo-amino acid compositions (Q2419825) (← links)
- Novel 3D bio-macromolecular bilinear descriptors for protein science: predicting protein structural classes (Q2630314) (← links)
