… The clinical course of Alzheimer’s disease (AD) is generally … , we use a neural network model
to investigate how the interplay … Within the model we show that the deterioration of memory …

… To identify the molecular mechanisms and novel therapeutic targets of late-onset Alzheimer's
Disease (LOAD), we performed an integrative network analysis of multi-omics profiling of …

… network-based analyses are an attractive complement to classical approaches. In Alzheimer
disease (… /proteins involved in this biological network and classified them according to their …

… network modeling approach to neurological diseases or even broader clinical research
fields, which would facilitate the faster and more efficient development of disease interventions. …

… Based on this, a network model of neurons is developed, that explains the consequent loss
… from this model. We also show how the global efficiency of signal transmission in the network …

… Alzheimer’s disease has become a public health crisis globally due to its increasing … The
purpose of this study was to establish an early warning model using artificial neural network (…

… Dementia-related diseases like Alzheimer's Disease (AD) have a tremendous social and
economic cost. A deeper understanding of its underlying pathophysiologies may provide an …

… gene networks constructed from … networks using gene expression datasets generated from
mice with ablation of major gene expression nodes identified in our AD-dysregulated networks…

… Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker …
In this Review, we discuss several time-dependent models of AD that take into consideration …

… diseases like Alzheimer's disease. We constructed a “Core” Alzheimer's disease protein
interaction network by … The Core network consisted of 775 nodes and 2,204 interactions. To our …