DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype–phenotype prediction
Background Genotypes are strongly associated with disease phenotypes, particularly in
brain disorders. However, the molecular and cellular mechanisms behind this association …
brain disorders. However, the molecular and cellular mechanisms behind this association …
Computational Methods for Data Integration and Imputation of Missing Values in Omics Datasets
Y Schumann, A Gocke, JE Neumann - Proteomics, 2025 - Wiley Online Library
Molecular profiling of different omic‐modalities (eg, DNA methylomics, transcriptomics,
proteomics) in biological systems represents the basis for research and clinical decision …
proteomics) in biological systems represents the basis for research and clinical decision …
Graph quilting: graphical model selection from partially observed covariances
Graphical model selection is a seemingly impossible task when many pairs of variables are
never jointly observed; this requires inference of conditional dependencies with no …
never jointly observed; this requires inference of conditional dependencies with no …
[PDF][PDF] Brooklyn plots to identify co-expression dysregulation in single cell sequencing
Altered open chromatin regions, impacting gene expression, is a feature of some human
disorders. We discovered it is possible to detect global changes in genomically-related …
disorders. We discovered it is possible to detect global changes in genomically-related …
DeepGAMI: Deep biologically guided auxiliary learning for multimodal integration and imputation to improve phenotype prediction
Genotype-phenotype association is found in many biological systems, such as brain-related
diseases and behavioral traits. Despite the recent improvement in the prediction of …
diseases and behavioral traits. Despite the recent improvement in the prediction of …
Covariance matrix completion via auxiliary information
J Steneman, G Vinci - arxiv preprint arxiv:2402.05767, 2024 - arxiv.org
Covariance matrix estimation is an important task in the analysis of multivariate data in
disparate scientific fields, including neuroscience, genomics, and astronomy. However …
disparate scientific fields, including neuroscience, genomics, and astronomy. However …
Some Research Progress in Generative Modeling and the Related Applications to Single-Cell RNA-Sequencing and Spatially Resolved Transcriptomics Data
M Zhu - 2023 - search.proquest.com
Generative modeling is a major statistical learning approach that has found successes in
numerous application fields including natural language processing, computer vision and …
numerous application fields including natural language processing, computer vision and …