Pages that link to "Q39990279"
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The following pages link to Using the augmented Chou's pseudo amino acid composition for predicting protein submitochondria locations based on auto covariance approach (Q39990279):
Displaying 50 items.
- Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization (Q21095006) (← links)
- A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0 (Q21562645) (← links)
- iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins (Q28235305) (← links)
- Predicting drug-target interaction networks based on functional groups and biological features (Q28473160) (← links)
- Prediction of body fluids where proteins are secreted into based on protein interaction network (Q28476378) (← links)
- Classification and analysis of regulatory pathways using graph property, biochemical and physicochemical property, and functional property (Q28477267) (← links)
- Prediction of antimicrobial peptides based on sequence alignment and feature selection methods (Q28477742) (← links)
- iNR-PhysChem: a sequence-based predictor for identifying nuclear receptors and their subfamilies via physical-chemical property matrix (Q28480984) (← links)
- Predicting metabolic pathways of small molecules and enzymes based on interaction information of chemicals and proteins (Q28483951) (← links)
- Predicting chemical toxicity effects based on chemical-chemical interactions (Q28486192) (← links)
- A multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteins (Q28729737) (← links)
- iFC²: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content (Q30392851) (← links)
- In vitro transcriptomic prediction of hepatotoxicity for early drug discovery (Q30423433) (← 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)
- Prediction of regulatory interactions in Arabidopsis using gene-expression data and support vector machines (Q33808089) (← links)
- Gene ontology based transfer learning for protein subcellular localization (Q33810069) (← links)
- Predicting protein phenotypes based on protein-protein interaction network (Q33851525) (← links)
- iDNA-Prot: Identification of DNA Binding Proteins Using Random Forest with Grey Model (Q34026228) (← links)
- A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction (Q34151702) (← links)
- Predicting protein folding rates using the concept of Chou's pseudo amino acid composition (Q34165172) (← links)
- Prediction of GABAA receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine (Q34181833) (← links)
- Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites (Q34310191) (← links)
- An ensemble method for predicting subnuclear localizations from primary protein structures. (Q34608457) (← links)
- 3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors (Q35669549) (← links)
- Using support vector machine and evolutionary profiles to predict antifreeze protein sequences. (Q35795886) (← links)
- Prediction of bioluminescent proteins using auto covariance transformation of evolutional profiles. (Q35866073) (← links)
- Spatial and functional organization of mitochondrial protein network (Q36663268) (← links)
- SubMito-PSPCP: predicting protein submitochondrial locations by hybridizing positional specific physicochemical properties with pseudoamino acid compositions (Q37148566) (← links)
- iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid components (Q37645097) (← links)
- PseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets (Q37683961) (← links)
- iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking (Q37684124) (← links)
- Some remarks on protein attribute prediction and pseudo amino acid composition (Q37822128) (← links)
- Energy matters: mitochondrial proteomics for biomedicine (Q37829412) (← links)
- Recent progress in predicting protein sub-subcellular locations (Q37890426) (← links)
- Recent advances in protein-protein interaction prediction: experimental and computational methods (Q38014488) (← links)
- Protein submitochondrial localization from integrated sequence representation and SVM-based backward feature extraction (Q38471324) (← links)
- Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection (Q38495608) (← links)
- Predicting protein submitochondria locations by combining different descriptors into the general form of Chou’s pseudo amino acid composition (Q38499799) (← links)
- Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization (Q38500179) (← links)
- Virus-mPLoc: a fusion classifier for viral protein subcellular location prediction by incorporating multiple sites (Q38505682) (← links)
- Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences (Q38534551) (← links)
- MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins (Q38661276) (← links)
- Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou's General Pseudo Amino Acid Composition (Q38922819) (← links)
- Predicting the Functional Types of Singleplex and Multiplex Eukaryotic Membrane Proteins via Different Models of Chou's Pseudo Amino Acid Compositions (Q40440907) (← links)
- SySAP: a system-level predictor of deleterious single amino acid polymorphisms (Q42772243) (← links)
- Predicting the state of cysteines based on sequence information (Q42913448) (← links)
- An empirical study on the matrix-based protein representations and their combination with sequence-based approaches (Q44053250) (← links)
- SecretP: Identifying bacterial secreted proteins by fusing new features into Chou’s pseudo-amino acid composition (Q44759878) (← links)
- Two-intermediate model to characterize the structure of fast-folding proteins (Q45256926) (← links)