Understanding and manipulating the machineries of cells and tissues requires a multi-scale approach that examines details of genes/proteins and their interactions to elucidate complex behavior of cellular and tissue states, as well as their spatio-temporal pattern formation.
This talk will explore the complex interdisciplinary software systems developed to support the 32-site international PREDICTHD project that aims to better characterize disease progression in Huntington’s disease. Key aspects of how software engineering best practices are applied by an interdisciplinary team of computer scientists, software engineers, biostatisticians, and clinical investigators to accelerate the analysis and understanding of distributed and heterogeneous data sources will be presented. This presentation will describe the infrastructure and environmen
Hypertrophic scarring is a major clinical problem characterized by excessive fibrosis that can result in disfigurement, distress, discomfort/pain, and permanent loss of function. In several treatment strategies reduced fibrosis and scarring appears connected to a reduction in force at the wound site. However, the underlying mechanisms that link mechanical environment to fibrosis remain unclear.
The second-order implicit integration factor method (IIF2) is effective at solving stiff reaction–diffusion equations owing to its nice stability condition. IIF has previously been applied primarily to systems in which the reaction contained no explicitly time-dependent terms and the boundary conditions were homogeneous. If applied to a system with explicitly time-dependent reaction terms, we find that IIF2 requires prohibitively small time-steps, that are relative to the square of spatial grid sizes, to attain its theoretical second-order temporal accuracy.
Following injury, skin activates a complex wound healing programme. While cellular and signalling mechanisms of wound repair have been extensively studied, the principles of epidermal‐dermal interactions and their effects on wound healing outcomes are only partially understood. To gain new insight into the effects of epidermal‐dermal interactions, we developed a multiscale, hybrid mathematical model of skin wound healing. The model takes into consideration interactions between epidermis and dermis across the basement membrane via diffusible signals, defined as activator and inhibitor.
The use of single-cell transcriptomics has become a major approach to delineate cell subpopulations and the transitions between them. While various computational tools using different mathematical methods have been developed to infer clusters, marker genes, and cell lineage, none yet integrate these within a mathematical framework to perform multiple tasks coherently. Such coherence is critical for the inference of cell–cell communication, a major remaining challenge.
Many signaling systems execute adaptation under circumstances that require noise attenuation. Here, we identify an intrinsic trade-off existing between sensitivity and noise attenuation in the three-node networks. We demonstrate that although fine-tuning timescales in three-node adaptive networks can partially mediate this trade-off in this context, it prolongs adaptation time and imposes unrealistic parameter constraints.
Implementation of pattern recognition algorithms and visualization tools for similarity and communication between cells and populations of cells.
Shuxiong Wang, Matthew Karikomi, Adam L MacLean, Qing Nie. Cell lineage and communication network inference via optimization for single-cell transcriptomics. Nucleic Acids Research, Volume 47, Issue 11, 20 June 2019, Page e66. DOI: 10.1093/nar/gkz204.
10.1093/nar/gkz204
