iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition.
about
Survey of Programs Used to Detect Alternative Splicing Isoforms from Deep Sequencing Data In SilicoiNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid compositioniCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channelsIdentification of Multi-Functional Enzyme with Multi-Label ClassifierReverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function.iMethyl-PseAAC: identification of protein methylation sites via a pseudo amino acid composition approachiSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition.iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid compositioniDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid compositioniPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformationExon skipping event prediction based on histone modifications.Prediction of protein-protein interactions with clustered amino acids and weighted sparse representation.Accurate prediction of nuclear receptors with conjoint triad featurePredHSP: Sequence Based Proteome-Wide Heat Shock Protein Prediction and Classification Tool to Unlock the Stress Biology.Identification and analysis of the N(6)-methyladenosine in the Saccharomyces cerevisiae transcriptomeAn Ensemble Method to Distinguish Bacteriophage Virion from Non-Virion Proteins Based on Protein Sequence CharacteristicsPredicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier.iROS-gPseKNC: Predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide composition.iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid componentsiNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking.Predicting the types of J-proteins using clustered amino acids.Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou's General Pseudo Amino Acid Composition.PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition.The effect of three novel feature extraction methods on the prediction of the subcellular localization of multi-site virus proteins.iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou's PseAAC to formulate DNA samples.Identify Secretory Protein of Malaria Parasite with Modified Quadratic Discriminant Algorithm and Amino Acid Composition.Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression.Analysis of Conformational B-Cell Epitopes in the Antibody-Antigen Complex Using the Depth Function and the Convex HulliRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.Sequence-based predictive modeling to identify cancerlectins.iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences.Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition.Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach.UltraPse: A Universal and Extensible Software Platform for Representing Biological Sequences.BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches.Prediction of Metal Ion Binding Sites in Proteins from Amino Acid Sequences by Using Simplified Amino Acid Alphabets and Random Forest Model.iPromoter-2L: a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC.Predicting the Organelle Location of Noncoding RNAs Using Pseudo Nucleotide Compositions.
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P2860
iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition.
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
iHSP-PseRAAAC: Identifying the ...... ino acid alphabet composition.
@en
type
label
iHSP-PseRAAAC: Identifying the ...... ino acid alphabet composition.
@en
prefLabel
iHSP-PseRAAAC: Identifying the ...... ino acid alphabet composition.
@en
P356
P1476
iHSP-PseRAAAC: Identifying the ...... ino acid alphabet composition.
@en
P2093
Peng-Mian Feng
P304
P356
10.1016/J.AB.2013.05.024
P407
P577
2013-06-10T00:00:00Z