Highly sensitive, non-invasive detection of colorectal cancer mutations using single molecule, third generation sequencing.

Colorectal cancer (CRC) represents one of the most prevalent and lethal malignant neoplasms and every individual of age 50 and above should undergo regular CRC screening. Currently, the most effective preventive screening procedure to detect adenomatous polyps, the precursors to CRC, is colonoscopy. Since every colorectal cancer starts as a polyp, detecting all polyps and removing them is crucial.

Neural networks evaluating NMR data: an approach to visualize similarities and relationships of sol-gel derived inorganic-organic and organometallic hybrid polymers.

An artificial neural network (ANN)--the Kohonen Self-Organizing Feature Map (SOM)-is used to evaluate solid-state NMR spectroscopic derived data of 72 siloxane-based phosphine and organometallic functionalized hybrid polymers. The data set consists of parameters that describe their structural features and their dynamic behavior. The ANN visualizes similarities of the investigated compounds by reducing the dimension of the data set.