The following pages link to iNitro-Tyr (Q34242):
Displaying 22 items.
- 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)
- Identify five kinds of simple super-secondary structures with quadratic discriminant algorithm based on the chemical shifts (Q739232) (← links)
- mLASSO-Hum: a LASSO-based interpretable human-protein subcellular localization predictor (Q739351) (← 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)
- Precision assessment of some supervised and unsupervised algorithms for genotype discrimination in the genus \textit{pisum} using SSR molecular data (Q1664568) (← links)
- Prediction of S-sulfenylation sites using mRMR feature selection and fuzzy support vector machine algorithm (Q1712633) (← 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)
- 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)
- 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)
- iRNA-PseKNC(2methyl): identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components (Q1721769) (← 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)
- Dforml(KNN)-PseAAC: detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and pseudo components (Q1739305) (← links)
- Prediction of \(\beta\)-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine (Q2351316) (← links)
- A new technique for generating pathogenic barcodes in breast cancer susceptibility analysis (Q2415748) (← links)
- VR-BFDT: a variance reduction based binary fuzzy decision tree induction method for protein function prediction (Q2630322) (← links)
- An extension of fuzzy topological approach for comparison of genetic sequences (Q2987850) (← links)
