Mapping our molecular world

The chemical make-up of biology is incredibly complex. It is difficult to analyze the molecular make up of one organism but what about 100s or 1000s of different organisms? How can we look at the molecular make-up of all such organisms at once? How many molecules do they have in common? How many are different? As mass spectrometers are becoming faster and more sensitive we can detect a lot of molecular information. There are now mass spectrometers that can analyze 10,000 samples a day. However, there is no infrastructure to analyze this amount of molecular information or to correlate this information to other Big Data generating approaches such as sequencing. On average, however, only 1-5% of all the molecular information that is collected by mass spectrometry can be annotated. It is simply too much information for one person or lab to analyze this information with the existing tools that are available. In this lecture we will explore the strategies for organizing and visualizing the massive amount of information. Topics such as molecular networking, crowd source molecular analysis, large scale mass spectrometry based genome mining, cross correlative analysis with molecular networking and pattern based genome mining will be covered.