Publications by authors named "Chihua Ma"
Article Synopsis
- The study introduces the community dynamic inference method (CommDy) as a novel analytical tool for neuroimaging data, specifically applied to understanding changes in brain networks due to aging in mice.
- Using CommDy, researchers found that auditory cortical networks in aged mice were significantly more fragmented than those in younger mice, indicating alterations in network connectivity associated with aging.
- Similar declines in network connectivity were also seen in the awake motor cortex, hinting that the changes observed in auditory cortex networks might reflect broader aging processes in the brain.
We introduce a web-based visual comparison approach for the systematic exploration of dynamic activation networks across biological datasets. Understanding the dynamics of such networks in the context of demographic factors like age is a fundamental problem in computational systems biology and neuroscience. We design visual encodings for the dynamic and community characteristics of these temporal networks.
View Article and Find Full Text PDFPrecision Risk Analysis of Cancer Therapy with Interactive Nomograms and Survival Plots.
IEEE Trans Vis Comput Graph
April 2019
We present the design and evaluation of an integrated problem solving environment for cancer therapy analysis. The environment intertwines a statistical martingale model and a K Nearest Neighbor approach with visual encodings, including novel interactive nomograms, in order to compute and explain a patient's probability of survival as a function of similar patient results. A coordinated views paradigm enables exploration of the multivariate, heterogeneous and few-valued data from a large head and neck cancer repository.
View Article and Find Full Text PDFBackground: Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists' understanding of phenotypic behavior associated with specific genes.
Results: We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks.