Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence.
about
Sequence-based prediction of protein protein interaction using a deep-learning algorithm.PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein SequencesPredicting protein-protein interactions via multivariate mutual information of protein sequences.Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical CharacteristicsIdentification of Protein-Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information.Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree.Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM.Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.Identification of DNA-protein Binding Sites through Multi-Scale Local Average Blocks on Sequence Information.PCLPred: A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine Model with Low-Rank Matrix Approximation.Single-Trial Evoked Potential Estimating Based on Sparse Coding under Impulsive Noise Environment.Accurate Prediction of ncRNA-Protein Interactions From the Integration of Sequence and Evolutionary InformationDeep Neural Network Based Predictions of Protein Interactions Using Primary Sequences
P2860
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P2860
Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence.
description
2015 nî lūn-bûn
@nan
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
2015年论文
@zh
2015年论文
@zh-cn
name
Using Weighted Sparse Represen ...... actions from Protein Sequence.
@en
type
label
Using Weighted Sparse Represen ...... actions from Protein Sequence.
@en
prefLabel
Using Weighted Sparse Represen ...... actions from Protein Sequence.
@en
P2093
P2860
P356
P1476
Using Weighted Sparse Represen ...... actions from Protein Sequence.
@en
P2093
Lirong Wang
Yu-An Huang
Zhu-Hong You
P2860
P304
P356
10.1155/2015/902198
P407
P577
2015-10-28T00:00:00Z