3 citations · 4 across the 8 of their papers we have counts for
9 papers
Masked Symmetric Nonnegative Matrix Factorization for Community Detection in Incomplete Networks
Anqi Liu, Ran Gu, Rui-Jin Zhang
Community detection in complex networks is frequently challenged by incomplete or noisy adjacency matrices. Traditional symmetric nonnegative matrix factorization methods typically…
Annotation-Informed Block-Sparse Bayesian Modeling for cis-Expression Prediction
Lei Huang, Hui Shen, Kuan-Jui Su +9
Genotype-based cis-expression prediction depends on accurately modeling local regulatory architecture. We present block-sparse Bayesian sparse linear mixed model (bsBSLMM), an exte…
GenoBERT: A Language Model for Accurate Genotype Imputation
Lei Huang, Chuan Qiu, Kuan-Jui Su +13
Genotype imputation enables dense variant coverage for genome-wide association and risk-prediction studies, yet conventional reference-panel methods remain limited by ancestry bias…
A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds
Anton Orlichenko, Gang Qu, Ziyu Zhou +7
Objective: fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinic…
Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
Chen Zhao, Kuan-Jui Su, Chong Wu +13
Background: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing…
Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results
Anton Orlichenko, Gang Qu, Kuan-Jui Su +4
Functional magnetic resonance (fMRI) is an invaluable tool in studying cognitive processes in vivo. Many recent studies use functional connectivity (FC), partial correlation connec…
CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data
Chen Zhao, Anqi Liu, Xiao Zhang +6
Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding genetic data. Each omics technique only provides a limited vi…
ImageNomer: description of a functional connectivity and omics analysis tool and case study identifying a race confound
Anton Orlichenko, Grant Daly, Ziyu Zhou +4
Most packages for the analysis of fMRI-based functional connectivity (FC) and genomic data are used with a programming language interface, lacking an easy-to-navigate GUI frontend.…
A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure
Xuewei Cao, Joyce H Keyak, Sigurdur Sigurdsson +7
Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break…