Howard University · BiologyXu Lab
Jinrui Xu · Washington, District of Columbia
Research Focus
Dr. Jinrui Xu's research lab focuses on understanding essential genes—those that are crucial for cell survival and function. The lab employs advanced computational methods, particularly a novel framework that uses graph neural networks, to predict gene essentiality and identify important protein structures. This research aims to bridge the gap between computational models and biological insights, ultimately contributing to advancements in drug discovery and precision medicine.
gene essentialitygraph neural networksbiochemical featuresdisease mechanismsprotein substructuresdrug discoverycomputational biologysystems biologyprecision medicinebiomedical research
Research Aims
5AIM 01Develop a novel computational framework to analyze gene essentiality using Graph Attention Networks.
AIM 02Identify biologically meaningful protein substructures related to gene essentiality.
AIM 03Enhance prediction accuracy by incorporating interpretable biochemical features.
AIM 04Move beyond binary classification of gene essentiality to continuous fitness modeling.
AIM 05Engage undergraduate students in interdisciplinary research to develop skills in biology and data science.
Skills the Lab Values
Graph Attention Networks (GATs)bioinformaticsdata analysisPython programmingbiochemical feature analysisprotein structure predictiondataset curationmachine learningmodel validationcollaborative research
Output against the department
Publications45bottom 10% of dept.929th of 1,033
this lab
most publishedleast published
Citations9.7ktop 39% of dept.402nd 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.