Probability weighted ensemble transfer learning for predicting interactions between HIV-1 and human proteins.
about
Multi-label multi-instance transfer learning for simultaneous reconstruction and cross-talk modeling of multiple human signaling pathwaysComputational discovery of Epstein-Barr virus targeted human genes and signalling pathways.Computational approaches for prediction of pathogen-host protein-protein interactions.A novel one-class SVM based negative data sampling method for reconstructing proteome-wide HTLV-human protein interaction networks.Computational prediction of virus-human protein-protein interactions using embedding kernelized heterogeneous data.Computational reconstruction of proteome-wide protein interaction networks between HTLV retroviruses and Homo sapiens.AdaBoost based multi-instance transfer learning for predicting proteome-wide interactions between Salmonella and human proteinsMulti-label ℓ2-regularized logistic regression for predicting activation/inhibition relationships in human protein-protein interaction networksA review of in silico approaches for analysis and prediction of HIV-1-human protein-protein interactions.A simple feature construction method for predicting upstream/downstream signal flow in human protein-protein interaction networks.DeNovo: virus-host sequence-based protein-protein interaction prediction.Improving the Understanding of Pathogenesis of Human Papillomavirus 16 via Mapping Protein-Protein Interaction Network.Review of computational methods for virus-host protein interaction prediction: a case study on novel Ebola-human interactions.Analysis of protein targets in pathogen-host interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network.Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.Transferring knowledge of bacterial protein interaction networks to predict pathogen targeted human genes and immune signaling pathways: a case study on M. tuberculosis.
P2860
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P2860
Probability weighted ensemble transfer learning for predicting interactions between HIV-1 and human proteins.
description
2013 nî lūn-bûn
@nan
2013 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
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
name
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@ast
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@en
type
label
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@ast
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@en
prefLabel
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@ast
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@en
P2860
P1433
P1476
Probability weighted ensemble ...... ween HIV-1 and human proteins.
@en
P2093
P2860
P304
P356
10.1371/JOURNAL.PONE.0079606
P407
P577
2013-11-18T00:00:00Z