Track topics on Twitter Track topics that are important to you
Uncovering rare susceptibility variants that contribute to the causes of complex diseases requires large sample sizes and massively parallel sequencing technologies. These sample sizes, often made up of exome and genome data from tens to hundreds of thousands of individuals, are often too large for current analytical tools to process. A team at Baylor College of Medicine, led by Dr. Suzanne Leal, professor of molecular and human genetics, has developed new software called SEQSpark to overcome this processing obstacle. A study on the new technology appears in The American Journal of Human Genetics.
Original Article: Researchers build SEQSpark to analyze massive genetic data setsNEXT ARTICLE
DNA sequencing is the process of determining the precise order of nucleotides within a DNA molecule. During DNA sequencing, the bases of a small fragment of DNA are sequentially identified from signals emitted as each fragment is re-synthesized from a ...
Bioinformatics is the application of computer software and hardware to the management of biological data to create useful information. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied...