The Razavi Newman
Integrative Genomics and Bioinformatics Core


Salk Institute for Biological Studies - The Razavi Newman
Integrative Genomics and Bioinformatics Core - People

Facility Staff

Max Shokhirev

Lead Bioinformatics Analyst and Staff Scientist
Integrative Genomics and Bioinformatics Core

Max got his Ph. D. in Bioinformatics and Systems Biology at UCSD in the Signaling Systems Lab with Dr. Alex Hoffmann studying how immune cells make decisions. During this time, he designed and developed methods and models for the analysis of multi-dimensional noisy biological data (microscopy, single-cell sequencing, flow cytometry).

As the lead Bioinformatics Analyst at the Salk Razavi Newman Integrative Genomics and Bioinformatics Core, Max works one-on-one with biologists, chemists, and immunologists on deriving biological meaning from next generation sequencing data and can help biologists plan experiments, analyze a diverse array of next-gen sequencing data (RNA-Seq, ChIP-Seq, HiC, DamID, Bisulfite-Seq, *-Seq), and look for patterns between datasets. Max also helps develop custom tools and pipelines, provides training in bioinformatics analysis, and helps write papers. Please feel free to contact Max if you have specific questions about NSG analysis or bioinformatics.

Galina Erikson

Bioinformatics Analyst I
Integrative Genomics and Bioinformatics Core

Galina joined Salk Institute in 2016. Prior to Salk she worked at the Scripps Translational Science Institute as a bioinformatics programmer where she developed several pipelines and tools, specializing in whole genome and exome analyses. She is the author of several papers including a recent one that aims to understand the genetics of disease free aging. Prior to STSI she completed the bioinformatics graduate certificate from UCSD Extension and worked under the supervision of Dr. Gerard Manning studying the evolution of kinases here at Salk. She is excited to be back and looks forward to establishing new collaborations in all aspects of next generation sequencing analysis.