Mathematical technique de-clutters cancer-cell data, revealing tumor evolution
- Posted: June 7, 2013
Using increasingly cheap and rapid methods to read the billions of “letters” that comprise human genomes – including the genomes of individual cells sampled from cancerous tumors -- scientists are generating far more data than they can easily interpret. Scientists from Cold Spring Harbor Laboratory (CSHL) have published a mathematical method of simplifying and interpreting genome data bearing evidence of mutations, such as those that characterize specific cancers. Not only is the technique highly accurate; it has immediate utility in efforts to parse tumor cells, in order to determine a patient’s prognosis and the best approach to treatment.
Among the research institutions NCI funds across the United States, it currently designates 67 as Cancer Centers. Largely based in research universities, these facilities are home to many of the NCI-supported scientists who conduct a wide range of intense, laboratory research into cancer’s origins and development. The Cancer Centers Program also focuses on trans-disciplinary research, including population science and clinical research. The centers’ research results are often at the forefront of studies in the cancer field.