Tissue engineers have generally seen bioreactors as ‘black boxes’
within which tissue engineering constructs (TECs) are cultured. It is accepted that a more detailed description of fluid mechanics and nutrient transport within process equipment can be achieved by using computational fluid dynamics (CFD) technology. This review discusses applications of CFD for tissue engineering-related bioreactors – fluid flow processes have direct implications on cellular responses such as attachment, migration and proliferation. We conclude that CFD should be seen as an invaluable tool for analyzing and visualizing the impact of fluidic forces and stresses on cells and TECs.”
“An efficient one-pot multi-component CHIR-99021 datasheet synthesis of flavans using perchloric acid supported on silica as a recyclable heterogeneous catalyst has been described. This is the first report of direct one-step construction of a flavan skeleton from a phenolic precursor. The method involves a Knoevenagel-type
condensation leading to in situ formation of transient O-quinone methide which further undergoes [4 + 2]-Diels-Alder cycloaddition with styrene to yield selleckchem a flavan skeleton. The method provides easy access to a wide range of bio-active natural products viz. flavonoids, anthocyanins and catechins.”
“Background: Linkage Disequilibrium (LD) bin-tagging algorithms identify a reduced set of tag SNPs that can capture the genetic variation in a population without genotyping every
single SNP. However, existing tag SNP selection algorithms for designing custom genotyping panels do not take into account all platform dependent factors affecting Fosbretabulin the likelihood of a tag SNP to be successfully genotyped and many of the constraints that can be imposed by the user.\n\nResults: SNPPicker optimizes the selection of tag SNPs from common bin-tagging programs to design custom genotyping panels. The application uses a multi-step search strategy in combination with a statistical model to maximize the genotyping success of the selected tag SNPs. User preference toward functional SNPs can also be taken into account as secondary criteria. SNPPicker can also optimize tag SNP selection for a panel tagging multiple populations. SNPPicker can optimize custom genotyping panels including all the assay-specific constraints of Illumina’s GoldenGate and Infinium assays.\n\nConclusions: A new application has been developed to maximize the success of custom multi-population genotyping panels. SNPPicker also takes into account user constraints including options for controlling runtime. Perl Scripts, Java source code and executables are available under an open source license for download at http://mayoresearch.mayo.edu/mayo/research/biostat/software.cfm”
“Feature selection plays an important role in pattern classification. Its purpose is to remove redundant features from data set as many as possible.