Yale University · BiologyImmunoinformatics Lab
Gisela Gabernet · New Haven, Connecticut
Research Focus
Dr. Gisela Gabernet's lab at Yale University focuses on developing advanced computational tools for analyzing immune system data, particularly related to B cell and T cell responses. The lab works on processing high-throughput sequencing data to better understand immune reactions to infections and diseases, creating user-friendly software tools to help other researchers. By making data analysis easier and more accessible, the lab aims to enhance research in infectious diseases and immune-mediated conditions.
adaptive immunityB cell receptorsT cell receptorsdata analysismachine learninghigh-throughput sequencingbioinformaticssoftware developmentcloud computing
Research Aims
5AIM 01Develop scalable computational workflows for high-throughput immune receptor sequencing.
AIM 02Integrate data from large clinical cohorts to enhance analysis capabilities.
AIM 03Improve data accessibility by incorporating public databases into workflows.
AIM 04Facilitate user engagement through hands-on training and feedback sessions.
AIM 05Enhance the Immcantation framework for better reproducibility and interoperability.
Skills the Lab Values
Python programmingR programmingNextflow workflowshigh-throughput data analysisdata integrationmachine learningsoftware usability testingcommunity engagementdatabase management
Output against the department
Publications94bottom 32% of dept.702nd of 1,033
this lab
most publishedleast published
Citations2.6kbottom 19% of dept.839th of 1,033
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.