scholarly article | Q13442814 |
P6179 | Dimensions Publication ID | 1042036148 |
P356 | DOI | 10.1007/S13238-012-2945-1 |
P932 | PMC publication ID | 4875394 |
P698 | PubMed publication ID | 22729399 |
P2093 | author name string | Luonan Chen | |
Zhi-Ping Liu | |||
P2860 | cites work | Unequal evolutionary conservation of human protein interactions in interologous networks | Q21092867 |
Finding and evaluating community structure in networks | Q21563748 | ||
Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence | Q22122411 | ||
Toward an understanding of the protein interaction network of the human liver | Q24292988 | ||
Global landscape of HIV-human protein complexes | Q24300336 | ||
Network organization of the human autophagy system | Q24324004 | ||
KEGG: kyoto encyclopedia of genes and genomes | Q24515297 | ||
BioGRID: a general repository for interaction datasets | Q24538650 | ||
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs | Q24545170 | ||
Multiple sequence alignment with the Clustal series of programs | Q24672842 | ||
STRING 7--recent developments in the integration and prediction of protein interactions | Q24675384 | ||
NCBI GEO: mining tens of millions of expression profiles--database and tools update | Q24675443 | ||
MINT: the Molecular INTeraction database | Q24675827 | ||
The human disease network | Q24678240 | ||
SCOPPI: a structural classification of protein-protein interfaces | Q25255780 | ||
Correlated mutations and residue contacts in proteins | Q25891592 | ||
Network biology: understanding the cell's functional organization | Q27861027 | ||
Protein interaction mapping in C. elegans using proteins involved in vulval development | Q28141447 | ||
Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae | Q28203878 | ||
The Database of Interacting Proteins: 2004 update | Q28234998 | ||
Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs | Q28264442 | ||
The IntAct molecular interaction database in 2010 | Q28749230 | ||
Reactome: a knowledge base of biologic pathways and processes | Q28757721 | ||
Assigning protein functions by comparative genome analysis: Protein phylogenetic profiles | Q29039336 | ||
Prediction of protein-protein interactions by combining structure and sequence conservation in protein interfaces | Q29302186 | ||
A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data | Q29395063 | ||
Network motifs: simple building blocks of complex networks | Q29547340 | ||
Human Protein Reference Database--2009 update | Q29547392 | ||
Evidence for dynamically organized modularity in the yeast protein-protein interaction network | Q29614449 | ||
Protein interaction maps for complete genomes based on gene fusion events | Q29616048 | ||
Conservation of gene order: a fingerprint of proteins that physically interact | Q29616049 | ||
BIND: the Biomolecular Interaction Network Database | Q29616859 | ||
IntAct--open source resource for molecular interaction data | Q29617575 | ||
Protein interaction networks from yeast to human | Q30002395 | ||
Prediction of protein-protein interactions by docking methods. | Q30329611 | ||
Relating whole-genome expression data with protein-protein interactions | Q30669147 | ||
Inferring strengths of protein-protein interactions from experimental data using linear programming | Q30881837 | ||
In silico two-hybrid system for the selection of physically interacting protein pairs. | Q54547905 | ||
Conserved clusters of functionally related genes in two bacterial genomes. | Q54574568 | ||
Similarity of phylogenetic trees as indicator of protein–protein interaction | Q55035526 | ||
Computational Prediction of Protein–Protein Interactions | Q57009010 | ||
Modeling Biomolecular Networks in Cells | Q57602323 | ||
Prediction of protein interactions: metabolic enzymes are frequently involved in gene fusion | Q73035327 | ||
DIPOS: database of interacting proteins in Oryza sativa | Q84465677 | ||
Inferring protein interactions from experimental data by association probabilistic method | Q31028667 | ||
Predicting protein-protein interaction by searching evolutionary tree automorphism space | Q33217293 | ||
Assessing the limits of genomic data integration for predicting protein networks | Q33218311 | ||
Analysis on multi-domain cooperation for predicting protein-protein interactions | Q33302713 | ||
Predicting gene ontology functions from protein's regional surface structures | Q33309502 | ||
Protein function in the post-genomic era. | Q33906809 | ||
Dissecting spatio-temporal protein networks driving human heart development and related disorders | Q34033622 | ||
Correlated sequence-signatures as markers of protein-protein interaction | Q34087861 | ||
Identification of dysfunctional modules and disease genes in congenital heart disease by a network-based approach | Q34089404 | ||
Computational methods for the prediction of protein interactions | Q34139922 | ||
Inferring high-confidence human protein-protein interactions | Q34257665 | ||
Inferring a protein interaction map of Mycobacterium tuberculosis based on sequences and interologs. | Q34272624 | ||
The MIPS mammalian protein-protein interaction database | Q34365947 | ||
Predicting protein-protein interactions based only on sequences information | Q35721356 | ||
Identifying disease genes and module biomarkers by differential interactions | Q35751276 | ||
Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers | Q35859609 | ||
Prediction of physical protein-protein interactions | Q36276666 | ||
Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences | Q36676452 | ||
Protein networks markedly improve prediction of subcellular localization in multiple eukaryotic species | Q36972115 | ||
Protein networks in disease | Q37125547 | ||
EcID. A database for the inference of functional interactions in E. coli | Q37202545 | ||
Network-based analysis of complex diseases | Q37987552 | ||
A relationship between gene expression and protein interactions on the proteome scale: analysis of the bacteriophage T7 and the yeast Saccharomyces cerevisiae | Q39097859 | ||
Predicting protein function by genomic context: quantitative evaluation and qualitative inferences | Q40414366 | ||
Co-evolution of proteins with their interaction partners | Q41742351 | ||
The Negatome database: a reference set of non-interacting protein pairs | Q41895237 | ||
Coexpression network analysis in chronic hepatitis B and C hepatic lesions reveals distinct patterns of disease progression to hepatocellular carcinoma | Q42978926 | ||
Tissue specificity and the human protein interaction network | Q43125316 | ||
FPPI: Fusarium graminearum protein-protein interaction database | Q43293252 | ||
Prediction of protein-RNA binding sites by a random forest method with combined features | Q44004039 | ||
Gaining confidence in high-throughput protein interaction networks | Q44011845 | ||
A discriminative approach for identifying domain-domain interactions from protein-protein interactions | Q45402219 | ||
Prediction of hot spots in protein interfaces using a random forest model with hybrid features. | Q45960983 | ||
HPID: the Human Protein Interaction Database | Q46533870 | ||
Correlation between gene expression profiles and protein-protein interactions within and across genomes. | Q48493508 | ||
Prediction of protein interaction sites from sequence profile and residue neighbor list | Q49265986 | ||
Identification of functional links between genes using phylogenetic profiles | Q50790966 | ||
Detecting and analyzing differentially activated pathways in brain regions of Alzheimer's disease patients | Q51601187 | ||
Use of contiguity on the chromosome to predict functional coupling. | Q51642809 | ||
P433 | issue | 7 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | protein-protein interaction | Q896177 |
P304 | page(s) | 508-520 | |
P577 | publication date | 2012-06-22 | |
P1433 | published in | Protein & Cell | Q26854012 |
P1476 | title | Proteome-wide prediction of protein-protein interactions from high-throughput data | |
P478 | volume | 3 |
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Q48687262 | Interactive protein network of FXIII-A1 in lipid rafts of activated and non-activated platelets |
Q41744338 | LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information. |
Q45959110 | PPIevo: protein-protein interaction prediction from PSSM based evolutionary information. |
Q35607697 | Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs |
Q41717369 | Protein-Protein Interactions as New Targets for Ion Channel Drug Discovery. |
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Q30943430 | Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data |
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Q46101705 | SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome |
Q30363264 | Structural bioinformatics of the interactome. |
Q39412615 | TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation. |
Q26770343 | The biochemical and mass spectrometric profiling of the dystrophin complexome from skeletal muscle |
Q38125039 | Towards a detailed atlas of protein–protein interactions |
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