Two computational biology senior concentrators, Madeleine Pittigher and Smriti Vaidyanathan, are receiving awards from the Dean of the College for outstanding graduating seniors in the Computational Biology concentration.

As gene sequencing has gotten faster and cheaper, clinicians and researchers are able to use genomic data to study, diagnose, and develop a course of treatment for a variety of individual cancers.

Cancers often involve far more than a genetic mutation acting alone. Multiple mutations, many of which are rare, may occur in different networks of multiple genes. HotNet2 is a powerful algorithm that analyzes genes at the network level and can help cancer researchers search for genetic associations and likely sources of disease across almost unimaginable genetic complexities.

Brown University evolutionary biologist Sohini Ramachandran has joined with colleagues in publishing a sweeping analysis of genetic and linguistic patterns across the world’s populations. Among the findings is that geographic distance predicts differentiation in both language and genes.

Ebola has a lot of company. In a novel database now made publicly available, Brown University researchers found that since 1980 the world has seen an increasing number of infectious disease outbreaks from an increasing number of sources. The good news, however, is that they are affecting a shrinking proportion of the world population.

A new study of the biology of aging shows that complex interactions among diet, mitochondrial DNA and nuclear DNA appear to influence lifespan at least as much as single factors alone. The findings may help scientists better understand the underlying mechanisms of aging and explain why studies of single factors sometimes produce contradictory results.

A computer algorithm developed by Brown computer scientists is helping to unlock the genetic drivers behind a variety of cancers. Research reported in the journal Nature identified a suite of mutations common in 12 types of cancer, including cancers of the breast, uterus, lung, colon, brain, and kidney.

CCMB Ph.D. students Hsin-Ta Wu and Max Leiserson, working in Ben Raphael's group, use powerful algorithms to assemble the most complete genetic profile yet of acute myeloid leukemia, an aggressive form of blood cancer, in collaboration with researchers at Washington University in St., Louis and The Cancer Genome Atlas (TCGA).

Animal cells contain two genomes: one in the nucleus and one in the mitochondria. When mutations occur in each, they can become incompatible, leading to disease.

Eli Upfal and Fabio Vandin of the Computer Science Department, and Ben Raphael of the Computer Science Department and the CCMB at Brown University, from left, are developing Big Data analytical tools that make sense of large datasets and eliminate the noise of data errors.

Researchers from Brown University have developed a method that they say can generate more accurate haplotype assemblies for genome-wide and whole-exome studies than current methods.

Researchers at Brown University and Stanford University have pieced together ancient human migration in North and South America.

This summer, more than a hundred scientists from dozens of research institutions published a landmark paper that identified a single gene responsible for the most prevalent form of ovarian cancer.