Computational era of science
One trigger for a new ICT era is the shift in the way that science is conducted. The old trial and error lab experimentation has been supplemented with informatics and computational science for characterizing, modeling, simulating, predicting and designing. Life sciences is the most prominent area of science requiring ICT advances, for a variety of purposes including biological process characterization and simulation. Genomics is possibly the field with the most ICT urgency; genomic data is growing at 10x/year vs. Moore’s Law at 1.5x/year for example, however nearly every field of science has progressed to large data sets and computational models.
One trigger for a new ICT era is the shift in the way that science is conducted. The old trial and error lab experimentation has been supplemented with informatics and computational science for characterizing, modeling, simulating, predicting and designing. Life sciences is the most prominent area of science requiring ICT advances, for a variety of purposes including biological process characterization and simulation. Genomics is possibly the field with the most ICT urgency; genomic data is growing at 10x/year vs. Moore’s Law at 1.5x/year for example, however nearly every field of science has progressed to large data sets and computational models.