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The set of clinical and basic biology data is important for the descriptions and modeling of disease progression, response to therapies, and in general for the diseased states.
My interests include infectious diseases, outbreak and anomaly detection, using surveillance data as epidemic intelligence, and mathematical modeling of disease transmission.
A reverse paradigm is now emerging through microphysiological platforms for preclinical testing of drugs and modeling of disease that contain large numbers of very small human tissues.
Mathematical modeling of disease transmission has provided quantitative predictions for health policy, facilitating the evaluation of epidemiological outcomes and the cost-effectiveness of interventions.
iCRISPR enabled rapid and highly efficient generation of biallelic knockout hPSCs for loss-of-function studies, as well as homozygous knockin hPSCs with specific nucleotide alterations for precise modeling of disease conditions.
This theme encompasses thrusts in bio-inspired electronics and neural prostheses; nano- and micro-technologies for understanding and manipulating biological processes at the cellular and molecular level; imaging and computational modeling of disease and neuro-anatomical processes; and communication biophysics, including language, speech, hearing and haptics.
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And he has done some modeling of diseases, including ALS, schizophrenia, and obsessive-compulsive disorder.
They are also developing microscale bioreactors for studies of stem cell differentiation, modeling of diseases, and drug development.
Raj, A., Kuceyeski, A. & Weiner, M. A network diffusion model of disease progression in dementia.
Those cells could be used to create laboratory models of disease.
Horvath, P. et al. Screening out irrelevant cell-based models of disease.
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