Evaluation of the role of atherogenic index of plasma in the reversion from Prediabetes to normoglycemia or progression to Diabetes: a multi-center retrospective …
H Yang, M Kuang, R Yang, G Xie, G Sheng… - Cardiovascular …, 2024 - Springer
Background Atherosclerosis is closely linked with glucose metabolism. We aimed to
investigate the role of the atherogenic index of plasma (AIP) in the reversal of prediabetes to …
investigate the role of the atherogenic index of plasma (AIP) in the reversal of prediabetes to …
Joint representation learning for retrieval and annotation of genomic interval sets
As available genomic interval data increase in scale, we require fast systems to search
them. A common approach is simple string matching to compare a search term to metadata …
them. A common approach is simple string matching to compare a search term to metadata …
Graph embedding and geometric deep learning relevance to network biology and structural chemistry
P Lecca, M Lecca - Frontiers in Artificial Intelligence, 2023 - frontiersin.org
Graphs are used as a model of complex relationships among data in biological science
since the advent of systems biology in the early 2000. In particular, graph data analysis and …
since the advent of systems biology in the early 2000. In particular, graph data analysis and …
Methods for constructing and evaluating consensus genomic interval sets
The amount of genomic region data continues to increase. Integrating across diverse
genomic region sets requires consensus regions, which enable comparing regions across …
genomic region sets requires consensus regions, which enable comparing regions across …
[PDF][PDF] Methods for evaluating unsupervised vector representations of genomic regions
Abstract Representation learning models have become a mainstay of modern genomics.
These models are trained to yield vector representations, or embeddings, of various …
These models are trained to yield vector representations, or embeddings, of various …
Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings
Data from the single-cell assay for transposase-accessible chromatin using sequencing
(scATAC-seq) are now widely available. One major computational challenge is dealing with …
(scATAC-seq) are now widely available. One major computational challenge is dealing with …
GenomicDistributions: fast analysis of genomic intervals with Bioconductor
Background Epigenome analysis relies on defined sets of genomic regions output by widely
used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of …
used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of …
Relative importance of triglyceride glucose index combined with body mass index in predicting recovery from prediabetic state to normal fasting glucose: a cohort …
H Yang, M Kuang, J Qiu, S He, C Yu, G Sheng… - Lipids in Health and …, 2024 - Springer
Background Prediabetes is a high-risk state for diabetes, and numerous studies have shown
that the body mass index (BMI) and triglyceride-glucose (TyG) index play significant roles in …
that the body mass index (BMI) and triglyceride-glucose (TyG) index play significant roles in …
NetREm Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation
Transcription factor (TF) coordination plays a key role in target gene (TG) regulation via
protein-protein interactions (PPIs) and DNA co-binding to regulatory elements. Single-cell …
protein-protein interactions (PPIs) and DNA co-binding to regulatory elements. Single-cell …
[HTML][HTML] Simple and scalable algorithms for cluster-aware precision medicine
AM Buch, C Liston, L Grosenick - Proceedings of machine learning …, 2024 - ncbi.nlm.nih.gov
AI-enabled precision medicine promises a transformational improvement in healthcare
outcomes. However, training on biomedical data presents significant challenges as they are …
outcomes. However, training on biomedical data presents significant challenges as they are …