Molecular networks as sensors and drivers of common human diseases

By Eric E. Schadt. Nature, 2009

799 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e1f6890da6fb8992328c14d3f0e8eddea2636f78

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In Molecular Biology

Citations in the corpus

TYROBP in Alzheimer’s Disease (2015, background): “In addition, previous study has revealed that LOAD arise from the downstream interplay of DNA sequence variants that act through molecular networks to confer disease risk [58].”
Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases (2018, background): “These densely interconnected networks sense and propagate perturbations from genetic variants and environmental factors, giving rise to disease states that may be difficult to understand at the level of individual genes (Schadt, 2009).”
From big data analysis to personalized medicine for all: challenges and opportunities (2015, background): “Systems approaches are driving the leading-edge of biology and medicine [5, 6].”
A survey of current trends in computational drug repositioning (2016, background): “Previous studies have suggested that drug–target network, drug–drug network, drug–disease network, protein interaction network, transcriptional networks and signaling networks are useful in the identification of therapeutic targets or characteristics of drug targets [63–65], thus providing new oppor”
Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease (2013, background): “Complex diseases such as late-onset Alzheimer’s disease (LOAD) arise from the downstream interplay of DNA-sequence variants and nongenetic factors that act through molecular networks to confer disease risk (Schadt, 2009).”
Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework (2013, background): “In a corollary development, we note that disease data are also particularly well suited to a network representation; the structure emerges naturally since biological phenotypes are products of molecular interaction.(8) Thus, genetic and molecular data can be integrated with phenotypic data to improv”
Trait-Associated SNPs Are More Likely to Be eQTLs: Annotation to Enhance Discovery from GWAS (2010, result): “Our results build on those of previous studies, particularly those of Schadt and colleagues [12–15] that focused on using transcriptome information to improve understanding of genetic signals, but the rapid accumulation of trait-associated SNPs through GWAS, coupled with the systematic efforts to ca”
Network target for screening synergistic drug combinations with application to traditional Chinese medicine (2011, background): “Now, we are standing at the portal of a new era to bridge molecular states to physiological states as well as various disease states through the biological networks that sense genetic and environmental perturbations [18].”
A DIseAse MOdule Detection (DIAMOnD) Algorithm Derived from a Systematic Analysis of Connectivity Patterns of Disease Proteins in the Human Interactome (2015, background): “In the recent years, there is increasing evidence that proteins associated with a particular disease have distinct interactions within theHuman Interactome, representing the cellular network of all physical molecular interactions [1–7].”
Computational tools for prioritizing candidate genes: boosting disease gene discovery (2012, methodology): “Ranking methods can roughly be classified into three categories: text mining 59,60 , similarity profiling and network analysis 43,61–63 (FIG.”
Analysing biological pathways in genome-wide association studies (2010, background): “It is well known that genes do not work in isolation; instead, complex molecular networks and cellular pathways are often involved in disease susceptibility and disease progressio”
Network Medicine: A Network-based Approach to Human Disease (2011, background): “Therefore, an understanding of a gene's network context is essential in determining the phenotypic impact of defects that affect i”