Scan this barcode to access this page with your mobile phone.

Presented by Dr. C. Titus Brown. Many data analysis problems are not easily parallelizable, often because the relevant analyses require an all-by-all analysis step. Applying heuristics often requires approximation, which introduces errors, noise, and bias. Recently, in confronting the sequence assembly problem, Dr. C. Titus Brown's lab has applied probabilistic data structures as a lightweight and scalable approach to taking large assembly graphs and partitioning them so that they can be treated independently.

o'reilly, webcast, data, strata