UWMUniversity of Wisconsin-Madison · Mathematics & Statistics
Genomic Phenotype Prediction Lab
Mark W. Craven · Madison, Wisconsin
Research Focus
Dr. Mark W. Craven's lab focuses on harnessing advanced computational methods, particularly deep learning, to predict how genetic variations influence biological traits (phenotypes) across different scales. The research aims to enhance our understanding of human health and disease by improving genomic analyses, especially in the context of diseases resulting from rare genetic mutations. The lab collaborates with other research centers to build a comprehensive dataset that maps genetic variants to their phenotypic impacts.
genetic variationphenotype predictiondeep learningmachine learninggene expressiongenome-wide association studiesrare diseasessubnetwork inferencecomputational biology
Research Aims
5AIM 01Develop a machine learning model to predict phenotypic impacts of genetic variations.
AIM 02Integrate genomic knowledge with learned models for a broader phenotypic analysis.
AIM 03Collaborate with IGVF Consortium for data collection and analysis.
AIM 04Create and contribute to a catalog mapping genetic variants to phenotypes.
AIM 05Enhance analytic methods for identifying genetic modifiers in disease contexts.
Skills the Lab Values
data analysismachine learningdeep learningbiostatistical modelinggenomic data interpretationpathway analysisactive learning algorithmsstatistical inference
Output against the department
Publications156bottom 31% of dept.90th of 131
this lab
most publishedleast published
Citations10ktop 40% of dept.52nd of 131
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.