about
Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and futureLearning from Co-expression Networks: Possibilities and ChallengesInformatic system for a global tissue-fluid biorepository with a graph theory-oriented graphical user interfaceSTON: exploring biological pathways using the SBGN standard and graph databasesTopological analysis and interactive visualization of biological networks and protein structures.CLASH: Complementary Linkage with Anchoring and Scoring for Heterogeneous biomolecular and clinical dataNetwork Tools for the Analysis of Proteomic Data.Use of Graph Database for the Integration of Heterogeneous Biological Data.Genome scale modeling in systems biology: algorithms and resources.Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.The human plasma membrane peripherome: visualization and analysis of interactions.NAP: The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networksIntegrative analysis reveals disease-associated genes and biomarkers for prostate cancer progression.Medusa: A tool for exploring and clustering biological networksMarkov Chain Ontology Analysis (MCOA).Data-driven insights into deletions of Mycobacterium tuberculosis complex chromosomal DR region using spoligoforests.Nonparametric simulation of signal transduction networks with semi-synchronized updateTopological and functional properties of the small GTPases protein interaction network.Topology of molecular interaction networks.Adverse outcome pathway (AOP) development I: strategies and principlesRelevance Epistasis Network of Gastritis for Intra-chromosomes in the Korea Associated Resource (KARE) Cohort Study.Affinity purification-mass spectrometry and network analysis to understand protein-protein interactions.Identification of important interacting proteins (IIPs) in Plasmodium falciparum using large-scale interaction network analysis and in-silico knock-out studies.A system based network approach to ethanol tolerance in Saccharomyces cerevisiae.Hierarchical feedback modules and reaction hubs in cell signaling networks.CompNet: a GUI based tool for comparison of multiple biological interaction networks.Mango: combining and analyzing heterogeneous biological networks.Efficient randomization of biological networks while preserving functional characterization of individual nodesIntegrative Variation Analysis Reveals that a Complex Genotype May Specify Phenotype in Siblings with Syndromic Autism Spectrum Disorder.Integrative analysis of cancer genes in a functional interactome.Tracking Cancer Genetic Evolution using OncoTrack.Formal modeling and analysis of the hexosamine biosynthetic pathway: role of O-linked N-acetylglucosamine transferase in oncogenesis and cancer progression.Visualization of the interactome: what are we looking at?mRNA-miRNA bipartite network reconstruction to predict prognostic module biomarkers in colorectal cancer stage differentiation.Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly.Computational methods to identify metabolic sub-networks based on metabolomic profiles.Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.PlaNet: Comparative Co-Expression Network Analyses for Plants.Small world properties changes in mild traumatic brain injuryFinding the shortest path with PesCa: a tool for network reconstruction.
P2860
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P2860
description
2011 nî lūn-bûn
@nan
2011 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Using graph theory to analyze biological networks
@ast
Using graph theory to analyze biological networks
@en
type
label
Using graph theory to analyze biological networks
@ast
Using graph theory to analyze biological networks
@en
prefLabel
Using graph theory to analyze biological networks
@ast
Using graph theory to analyze biological networks
@en
P2093
P2860
P50
P356
P1433
P1476
Using graph theory to analyze biological networks
@en
P2093
Charalampos N Moschopoulos
Maria Secrier
Reinhard Schneider
Sophia Kossida
P2860
P2888
P356
10.1186/1756-0381-4-10
P577
2011-04-28T00:00:00Z
P5875
P6179
1002056061