Cigdem Ak, PhD
@cigdemak.bsky.social
Interpretable ML | Computational and Systems Biology | Postdoc at Cancer Early Detection Advanced Research (CEDAR) Center @ohsuknight.bsky.social
Paper: nature.com/articles/s4200…
Code: github.com/ohsu-cedar-com�#InterpretableMLr#AIinCancerI#SingleCelli#MultiOmicsu#InterpretableAIr#CancerGenomicsr#OpenSciencee#Bioinformaticsf#ComputationalBiologya#MachineLearningeLearning
@commsbio.nature.com @ohsunews.bsky.social @ohsuknight.bsky.social
Code: github.com/ohsu-cedar-com�#InterpretableMLr#AIinCancerI#SingleCelli#MultiOmicsu#InterpretableAIr#CancerGenomicsr#OpenSciencee#Bioinformaticsf#ComputationalBiologya#MachineLearningeLearning
@commsbio.nature.com @ohsunews.bsky.social @ohsuknight.bsky.social
August 15, 2025 at 10:02 AM
Unlike black-box models that rely on post hoc interpretation, scMKL is designed to highlight the regulatory mechanisms that drive its predictions from the beginning.
August 14, 2025 at 1:18 PM
Unlike black-box models that rely on post hoc interpretation, scMKL is designed to highlight the regulatory mechanisms that drive its predictions from the beginning.
We developed scMKL, a framework that integrates single-cell multiomics data using biologically informed kernels by leveraging decades of knowledge on gene sets and transcription factor motifs.
August 14, 2025 at 1:17 PM
We developed scMKL, a framework that integrates single-cell multiomics data using biologically informed kernels by leveraging decades of knowledge on gene sets and transcription factor motifs.