Visualization, as a principle, allows us to both analytically monitor the process of biomarker discovery and explore data in unique ways.
Advances in biotechnology have empowered researchers to generate enormous amounts of biological data. However, the ability to understand these data lags far behind. Complex multivariate data lack an inherent distinction between signal and noise. Hidden among the data are correlations and variations that include everything from biological signal to instrument fluctuations.
Applied Proteomics has eased navigation through such data by developing advanced methods for visualization along with automated interpretation of complex proteomic data. With our multidimensional visualization tools, Applied Proteomics can quickly explore relationships between data populations from the big picture (hundreds of clinical samples) down to the smallest of details (peptide isotope profiles). In effect, Applied Proteomics has become consummate mapmakers and navigators of proteomics data - a compass only points to your destination, detailed cartography can show you the way.
Shown here is a demonstration of API's automated Data Analysis Pipeline, which has the ability to handle enormous amounts of data generated from proteomics experiments, in realtime. This system delivers amalgamated summary statistics to scientists from hundreds of informatics computations, providing critical feedback to drive process control.