Pages that link to "Q43571662"
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The following pages link to Using subsite coupling to predict signal peptides (Q43571662):
Displaying 50 items.
- Signal peptide prediction based on analysis of experimentally verified cleavage sites (Q24645296) (← links)
- iNuc-PhysChem: a sequence-based predictor for identifying nucleosomes via physicochemical properties (Q28484598) (← links)
- Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model (Q28485324) (← links)
- iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition (Q28486031) (← links)
- iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition (Q28541975) (← links)
- Identification of real microRNA precursors with a pseudo structure status composition approach (Q28651066) (← links)
- iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels (Q28658162) (← links)
- iEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networking (Q28661179) (← links)
- iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins (Q28675957) (← links)
- Preparing a human membrane and secreted protein-enriched cDNA library using PCR primers derived from a genomic database. (Q30715183) (← links)
- Benchmark data for identifying DNA methylation sites via pseudo trinucleotide composition (Q30983367) (← links)
- Prediction of Protein-Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures (Q31022492) (← links)
- A defective signal peptide in a 19-kD alpha-zein protein causes the unfolded protein response and an opaque endosperm phenotype in the maize De*-B30 mutant (Q33195639) (← links)
- Demonstration of two novel methods for predicting functional siRNA efficiency (Q33244915) (← links)
- 2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function (Q33633983) (← links)
- iMethyl-PseAAC: identification of protein methylation sites via a pseudo amino acid composition approach (Q33745509) (← links)
- iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition. (Q33747883) (← links)
- iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition (Q33755615) (← links)
- iDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid composition (Q34128762) (← links)
- Prediction of organellar targeting signals (Q34466798) (← links)
- iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition (Q34579675) (← links)
- A novel bacterial Water Hypersensitivity-like protein shows in vivo protection against cold and freeze damage (Q35695863) (← links)
- iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition (Q36740900) (← links)
- iACP: a sequence-based tool for identifying anticancer peptides (Q37086151) (← links)
- iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC. (Q37376337) (← links)
- iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC. (Q37536872) (← links)
- iPhos-PseEn: identifying phosphorylation sites in proteins by fusing different pseudo components into an ensemble classifier (Q37588275) (← links)
- iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid components (Q37645097) (← links)
- iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking (Q37684124) (← links)
- iSS-PC: Identifying Splicing Sites via Physical-Chemical Properties Using Deep Sparse Auto-Encoder. (Q38622969) (← links)
- Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou's General Pseudo Amino Acid Composition (Q38922819) (← links)
- Prediction of Signal Peptide Cleavage Sites with Subsite-Coupled and Template Matching Fusion Algorithm (Q39531157) (← links)
- pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC. (Q39646826) (← links)
- Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition (Q40534208) (← links)
- iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou's PseAAC to formulate DNA samples (Q40593974) (← links)
- iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition (Q41093262) (← links)
- iMiRNA-PseDPC: microRNA precursor identification with a pseudo distance-pair composition approach (Q41489664) (← links)
- Signal-BNF: a Bayesian network fusing approach to predict signal peptides (Q42042283) (← links)
- iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC. (Q42075633) (← links)
- Genetic complementation in yeast reveals functional similarities between the catalytic subunits of mammalian signal peptidase complex (Q44618304) (← links)
- Support vector machines for prediction of protein signal sequences and their cleavage sites (Q45858539) (← links)
- Prediction of signal peptides using scaled window (Q45882553) (← links)
- Prediction of protein secondary structure using feature selection and analysis approach. (Q45930709) (← links)
- TargetFreeze: Identifying Antifreeze Proteins via a Combination of Weights using Sequence Evolutionary Information and Pseudo Amino Acid Composition. (Q45954195) (← links)
- Influence of N-terminal truncations on the functional expression of Bacillus licheniformis gamma-glutamyltranspeptidase in recombinant Escherichia coli (Q46352118) (← links)
- Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach (Q46834389) (← links)
- iKcr-PseEns: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier (Q47437268) (← links)
- iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC. (Q47557569) (← links)
- A Novel Modeling in Mathematical Biology for Classification of Signal Peptides (Q47559177) (← links)
- iAFP-Ense: An Ensemble Classifier for Identifying Antifreeze Protein by Incorporating Grey Model and PSSM into PseAAC. (Q50553584) (← links)