| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/jcc/FanZLNW15 |
| P356 | DOI | 10.1002/JCC.24210 |
| P698 | PubMed publication ID | 26484844 |
| P5875 | ResearchGate publication ID | 283049149 |
| P2093 | author name string | Hui Wang | |
| Xiao-Yan Zhang | |||
| Yan-Ling Liu | |||
| Yi Nang | |||
| Guo-Liang Fan | |||
| P2860 | cites work | Some remarks on predicting multi-label attributes in molecular biosystems | Q38093788 |
| Impacts of bioinformatics to medicinal chemistry | Q38303748 | ||
| Gene function prediction using semantic similarity clustering and enrichment analysis in the malaria parasite Plasmodium falciparum | Q38371376 | ||
| Predicting protein submitochondria locations by combining different descriptors into the general form of Chou’s pseudo amino acid composition | Q38499799 | ||
| MITOP, the mitochondrial proteome database: 2000 update | Q39541857 | ||
| Structural similarity enhances interaction propensity of proteins | Q41836879 | ||
| Molecular science for drug development and biomedicine | Q42583554 | ||
| PreDNA: accurate prediction of DNA-binding sites in proteins by integrating sequence and geometric structure information. | Q44035464 | ||
| Predict mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou’s pseudo amino acid composition | Q44499984 | ||
| Identify catalytic triads of serine hydrolases by support vector machines | Q44921864 | ||
| iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites | Q45999913 | ||
| Using K-minimum increment of diversity to predict secretory proteins of malaria parasite based on groupings of amino acids | Q47900800 | ||
| Identification of RNA-binding sites in proteins by integrating various sequence information | Q50550153 | ||
| iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins | Q50761949 | ||
| Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition | Q50904851 | ||
| iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types | Q51261419 | ||
| Support Vector Machines for predicting HIV protease cleavage sites in protein | Q52043614 | ||
| A Simple Definition of Structural Regions in Proteins and Its Use in Analyzing Interface Evolution | Q54378760 | ||
| The use of the area under the ROC curve in the evaluation of machine learning algorithms | Q56594447 | ||
| Identification of Plasmodium malariae, a human malaria parasite, in imported chimpanzees | Q20904870 | ||
| Protein stickiness, rather than number of functional protein-protein interactions, predicts expression noise and plasticity in yeast | Q21093159 | ||
| A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0 | Q21562645 | ||
| Recent progress in protein subcellular location prediction | Q28240670 | ||
| Targeting Protein Kinases in the Malaria Parasite: Update of an Antimalarial Drug Target | Q28257406 | ||
| Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms | Q28268738 | ||
| Predicting Secretory Proteins of Malaria Parasite by Incorporating Sequence Evolution Information into Pseudo Amino Acid Composition via Grey System Model | Q28485324 | ||
| iSNO-PseAAC: Predict Cysteine S-Nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition | Q28486031 | ||
| A Novel View of pH Titration in Biomolecules† | Q29029861 | ||
| Comparison of the predicted and observed secondary structure of T4 phage lysozyme | Q29398301 | ||
| Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements | Q29614394 | ||
| Measuring the accuracy of diagnostic systems | Q29614441 | ||
| pH-Dependent pKaValues in Proteins—A Theoretical Analysis of Protonation Energies with Practical Consequences for Enzymatic Reactions | Q30050459 | ||
| Prediction of protein structure classes with pseudo amino acid composition and fuzzy support vector machine network. | Q30365585 | ||
| Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles | Q33328691 | ||
| A generic method for assignment of reliability scores applied to solvent accessibility predictions | Q33489065 | ||
| Prediction of protein cellular attributes using pseudo-amino acid composition | Q33941503 | ||
| Prediction of GABAA receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine | Q34181833 | ||
| Prediction of metalloproteinase family based on the concept of Chou’s pseudo amino acid composition using a machine learning approach | Q34238445 | ||
| PseAAC-Builder: A cross-platform stand-alone program for generating various special Chou’s pseudo-amino acid compositions | Q34264398 | ||
| Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning | Q34285299 | ||
| Predicting antibacterial peptides by the concept of Chou's pseudo-amino acid composition and machine learning methods | Q34294078 | ||
| Prediction of Allergenic Proteins by Means of the Concept of Chou's Pseudo Amino Acid Composition and a Machine Learning Approach | Q34296591 | ||
| Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou’s pseudo amino acid composition | Q34310638 | ||
| propy: a tool to generate various modes of Chou's PseAAC. | Q34328788 | ||
| iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition | Q34579675 | ||
| Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization | Q34733089 | ||
| Progress in the prediction of pKa values in proteins | Q35627466 | ||
| Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences | Q35810290 | ||
| Cellular crowding imposes global constraints on the chemistry and evolution of proteomes | Q36483608 | ||
| iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition | Q36740900 | ||
| Community knowledge, attitudes and practices (KAP) on malaria in Swaziland: a country earmarked for malaria elimination | Q37112344 | ||
| PseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets | Q37683961 | ||
| Some remarks on protein attribute prediction and pseudo amino acid composition | Q37822128 | ||
| P433 | issue | 31 | |
| P921 | main subject | malaria | Q12156 |
| P304 | page(s) | 2317-2327 | |
| P577 | publication date | 2015-10-20 | |
| P1433 | published in | Journal of Computational Chemistry | Q3186908 |
| P1476 | title | DSPMP: Discriminating secretory proteins of malaria parasite by hybridizing different descriptors of Chou's pseudo amino acid patterns | |
| P478 | volume | 36 |
Search more.