Nikos Kyrpides

Computational Biologist Senior Scientist

DOE Joint Genome Institute

Secondary Affiliation: Environmental Genomics and Systems Biology

Biosystems Data Science

Building: 91, Room 439
Mail Stop: 100PGF100
Phone: (925) 998-0788
NCKyrpides@lbl.gov

Research Interests

Metagenomics, Microbial Genomics, Microbial Diversity, Microbiology, Bioinformatics

Selected Publications

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JGI Helps Develop Computational Pipeline for RNA virus Sequences

October 3, 2022

In the journal Cell, researchers from a team led by researchers at Tel Aviv University in Israel, the National Center for Biotechnology Information, and the JGI describe a computational pipeline that can specifically scan for those snowflakes, or RNA virus sequences. Using this workflow, the team combed through more than 5,000 data sets of RNA sequences generated from diverse environmental samples around the world, resulting in a five-fold increase of RNA virus diversity. The JGI authors, who are also affiliated with the EGSB, are Simon Roux, Antonio Camargo, I. Min Chen, Natalia Ivanova, and Nikos Kyrpides. Learn more here on the JGI website.

Microbial Fingerprints for Cities

July 16, 2021

Vibrant cities around the world are made up of a unique blend of cultures, languages, cuisines, and – as scientists recently revealed – microbes. Nearly 1,000 scientists from around the world, including three from Berkeley Lab, collected and analyzed microbial samples from public transit stations across 60 global cities. They probed ticket kiosks, benches, and rails to see what tiny organisms like bacteria, viruses, and archaea were in residence.

Solving a Genetic Mystery at the Heart of the COVID-19 Pandemic

March 4, 2021

As the COVID-19 pandemic enters its second year, scientists are still working to understand how the SARS-CoV-2 strain evolved, and how it became so much more dangerous than other coronaviruses, which humans have been living alongside for millennia. Virologists and epidemiologists worldwide have speculated for months that a protein called ORF8 likely holds the answer, and a recent study by Berkeley Lab scientists has helped confirm this hypothesis.

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