Large-scale prediction of human protein-protein interactions from amino acid sequence based on latent topic features.
about
An overview of topic modeling and its current applications in bioinformaticsSequence-based prediction of protein protein interaction using a deep-learning algorithm.IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational predictionPredicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forestLarge-scale protein-protein interactions detection by integrating big biosensing data with computational model.Aggregation prone regions in human proteome: Insights from large-scale data analyses.HomPPI: a class of sequence homology based protein-protein interface prediction methods.Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set.Identification of 14-3-3 Proteins Phosphopeptide-Binding Specificity Using an Affinity-Based Computational Approach.Prediction of protein-protein interaction with pairwise kernel support vector machine.The current Salmonella-host interactome.Recent advances in protein-protein interaction prediction: experimental and computational methods.Protein sequence classification using feature hashing.Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.Computational Approaches for Predicting Binding Partners, Interface Residues, and Binding Affinity of Protein-Protein Complexes.Detecting protein-protein interactions with a novel matrix-based protein sequence representation and support vector machines.PredcircRNA: computational classification of circular RNA from other long non-coding RNA using hybrid features.Flaws in evaluation schemes for pair-input computational predictions.An empirical study on the matrix-based protein representations and their combination with sequence-based approaches.Feature selection and classification of protein-protein complexes based on their binding affinities using machine learning approaches.Comparative Analysis and Classification of Cassette Exons and Constitutive Exons.Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.An empirical study of different approaches for protein classificationDeep Neural Network Based Predictions of Protein Interactions Using Primary Sequences
P2860
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P2860
Large-scale prediction of human protein-protein interactions from amino acid sequence based on latent topic features.
description
2010 nî lūn-bûn
@nan
2010年の論文
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2010年学术文章
@wuu
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
2010年學術文章
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2010年學術文章
@zh-hant
name
Large-scale prediction of huma ...... ased on latent topic features.
@en
type
label
Large-scale prediction of huma ...... ased on latent topic features.
@en
prefLabel
Large-scale prediction of huma ...... ased on latent topic features.
@en
P2093
P356
P1476
Large-scale prediction of huma ...... ased on latent topic features.
@en
P2093
Hong-Bin Shen
Xiao-Yong Pan
Ya-Nan Zhang
P304
P356
10.1021/PR100618T
P577
2010-10-01T00:00:00Z