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Principal Investigator: Guanghua Xiao
Organization: UT SOUTHWESTERN MEDICAL CENTER
Fiscal Year: 2024
Award: $356,526
Funding agency: National Institute of General Medical Sciences
Project Summary
The location, timing and abundance of mRNA and proteins within a tissue underlie the basic molecular
mechanisms of cell functions and physiological and pathological developments. For example, the study of
expression of thousands of genes simultaneously at different locations could reveal great insights into embryo
development, the cooperation of molecular and cellular processes for high-order mental functions, and the
molecular basis and clinical impact of intra-tumor heterogeneity. Recent technology breakthroughs in spatial
molecular profiling (SMP), including both imaging-based technologies and sequencing-based technologies, have
enabled the comprehensive molecular characterization of single cells while preserving their spatial and
morphological contexts. Due to the huge potential to deepen our understanding of the molecular mechanisms of
cellular and physiological phenotypes, SMP technologies are rapidly gaining attention and a large amount of
such data will be generated. However, there are only few computational methods developed to analyze such
rich but complex data, and the limitations of computational methods lead to such valuable data being largely
under-used. The overarching goal of this study is to develop computational methods to analyze SMP data to
characterize detailed molecular spatial distributions and associate such information with cellular phenotypes and
physiological phenotypes. The specific aims are as follows: 1. develop novel spatio-statistical methods to
characterize spatial distributions of gene expression; 2. develop computational methods to characterize cellular
spatial organizations and investigate their relationship with molecular spatial distributions and disease status; 3.
develop user-friendly software to facilitate researchers in SMP data analysis and visualization. In order to achieve
this goal, we have assembled a strong team with complementary expertise in single-cell genomics, tissue image
analysis, spatial modelling, machine learning and software development. If implemented successfully, this
platform will greatly facilitate users in understanding molecular and cellular spatial organization in biological
tissues and provide comprehensive insights into the underlying biological processes.
Terms: <Algorithmic Software><Algorithmic Tools><Algorithms><Attention><Bayesian Modeling><Bayesian adaptive designs><Bayesian adaptive models><Bayesian belief network><Bayesian belief updating model><Bayesian framework><Bayesian hierarchical model><Bayesian network model><Bayesian nonparametric models><Bayesian spatial data model><Bayesian spatial image models><Bayesian spatial models><Bayesian statistical models><Bayesian tracking algorithms><Biological><Biological Function><Biological Process><Body Tissues><Cell Body><Cell Function><Cell Physiology><Cell Process><Cells><Cellular Function><Cellular Physiology><Cellular Process><Characteristics><Clinical><Communities><Complex><Computational algorithm><Computational toolkit><Computing Methodologies><Data><Data Analyses><Data Analysis><Data Set><Development><Disease><Disorder><Embryo Development><Embryogenesis><Embryonic Development><Feasibility Studies><Gene Expression><Genes><Goals><Graph><Heterogeneity><Image><Image Analyses><Image Analysis><Infrastructure><Intratumoral heterogeneity><Intuition><Investigators><Lead><Location><Machine Learning><Messenger RNA><Methodology><Methods><Modeling><Molecular><Molecular Fingerprinting><Molecular Profiling><Morphology><Network-based><Pathologic><Pathway interactions><Patient outcome><Patient-Centered Outcomes><Patient-Focused Outcomes><Pattern><Pb element><Phenotype><Physiologic><Physiological><Probabilistic Models><Probability Models><Proteins><Research><Research Personnel><Researchers><Software Algorithm><Spatial Distribution><Statistical Methods><Statistical Models><Structure><Subcellular Process><Technology><Tissue imaging><Tissues><Variant><Variation><Visualization><bio-informatics tool><bioinformatics tool><biologic><biological research><cell type><complex data><computational methodology><computational methods><computational toolbox><computational tools><computational toolset><computer algorithm><computer based method><computer methods><computerized tools><computing method><data interpretation><data structure><data visualization><deep learning><deep learning algorithm><deep learning method><deep learning strategy><develop software><developing computer software><developmental><disease classification><disease diagnosis><disorder classification><empowerment><experience><feature selection><flexibility><flexible><graph attention network><graph convolutional network><graph neural network><heavy metal Pb><heavy metal lead><heterogeneity in tumors><image evaluation><image interpretation><imaging><improved><informatics tool><insight><intra-tumoral heterogeneity><intratumor heterogeneity><intuitive><mRNA><machine based learning><mental function><molecular profile><molecular signature><nosology><novel><pathway><patient oriented outcomes><preservation><single cell genomics><software development><statistic methods><statistical linear mixed models><statistical linear models><tool><tumor heterogeneity><user friendly computer software><user friendly software>