Data integration, Modelling and prediction

Data integration is the procedure of combining data generated using a variety of different research various in order to enable detection of underlying themes and in Computational biology and bioinformatics, biological principles. Data Analysis in this arena is dataintensive, which means data sets are large and highly heterogeneous, to create knowledge from data, researchers must integrate these large and diverse datasets. Predictive genomics is at the intersection of multiple disciplines as predictive medicine, translational bioinformatics and personal genomics. Specifically, predictive genomics deals with the future phenotypic outcomes through prediction in areas such as complex multifactorial diseases in humans. Prediction and Modelling involves the use of computer simulations of biological systems, including cellular subsystems, such as the networks of enzymes and metabolites which comprise metabolism, signal transduction pathways and gene technology regulatory networks, to both visualize and analyze the complex connections of these cellular processes.

 

 

  • Data Modelling Process and Virtualization
  • Generic Data Modelling
  • Presenting and using the Results of a Predictive model
  • Propagation and Consolidation
  • Scientific Hypothesis and Prediction
  • Judgement-based Prediction
  • Supernatural Prediction
  • Ecological Models

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