Computational Biology

Genome-wide association studies, minus the Winner’s Curse, are shown to be reliable and replicable

Columbia researchers de-bias the effects of the Winner’s Curse across a broad set of traits, finding that reporting deficiencies, not the paradigm of GWAS, are to blame for the failure to replicate.

How Can We Keep Genetic Data Safe?

Crowdsourced family tree yields new insights about humanity

A study published in Science describes how researchers created, from 86M genealogy profiles, population-scale family trees to reassess longevity and marriage and migration patterns. Yaniv Erlich is the study’s senior author.

About

The Computational Biology Group brings together interdisciplinary and cross-disciplinary individuals and skillsets to tackle problems in high throughput genomics, systems biology, and genetics.

The group develops computational methods to analyze high throughput data on genetic variants within species, primarily human SNP, and sequencing data.

The student and postdoc body in the group is very diverse in terms of undergraduate background as well as current PhD program or postdoctoral affiliation. The group meets weekly giving an opportunity for students to present their research internally and feedback on one another’s work. Weekly meetings occasionally give host to guest speakers, include a journal club, or extracurricular activities.