Siwen Xu
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View article: Profiling Cell-state Fingerprints Based on Deep Learning Model with Meta-programs of Pan-cancer
Profiling Cell-state Fingerprints Based on Deep Learning Model with Meta-programs of Pan-cancer Open
Cell states within cancer have garnered significant attention, yet the mechanisms through which malignant cells assert dominance in pan-cancer commonalities remain elusive. In this study, we employed label-free multiplexed single-cell RNA …
View article: Linkage: an interactive web application for linking of DNA regulatory peaks to genes
Linkage: an interactive web application for linking of DNA regulatory peaks to genes Open
View article: scQTLtools: An R/Bioconductor Package for Comprehensive Identification and Visualization of Single-Cell eQTLs
scQTLtools: An R/Bioconductor Package for Comprehensive Identification and Visualization of Single-Cell eQTLs Open
Single-cell RNA sequencing (scRNA-seq) enables expression quantitative trait locus (eQTL) analysis at cellular resolution, offering new opportunities to uncover regulatory variants with cell-type-specific effects. However, existing tools a…
View article: Dynamic heterogeneity towards drug resistance in AML cells is primarily driven by epigenomic mechanism unveiled by multi-omics analysis
Dynamic heterogeneity towards drug resistance in AML cells is primarily driven by epigenomic mechanism unveiled by multi-omics analysis Open
This study demonstrates that AML drug resistance is predominantly driven by epigenomic mechanisms rather than genetic mutations. This study provides a detailed cellular and molecular characterization of AML drug response and resistance, id…
View article: Metal-Organic Frameworks for CRISPR/Cas9 Gene Editing Delivery: Innovations in Therapeutic and Diagnostic Applications
Metal-Organic Frameworks for CRISPR/Cas9 Gene Editing Delivery: Innovations in Therapeutic and Diagnostic Applications Open
View article: A Frequency-Dependent Assimilation Algorithm: Ensemble Optimal Smoothing
A Frequency-Dependent Assimilation Algorithm: Ensemble Optimal Smoothing Open
Motivated by the need for a simple and effective assimilation scheme that could be used in a relocatable ocean model, a new assimilation algorithm called ensemble optimal smoothing (EnOS) was developed. This scheme was a straightforward ex…
View article: Sample-multiplexing approaches for single-cell sequencing
Sample-multiplexing approaches for single-cell sequencing Open
View article: Methods for predicting single-cell miRNA in breast cancer
Methods for predicting single-cell miRNA in breast cancer Open
It has been demonstrated that miRNAs are involved in many biological processes including cell proliferation and differentiation, apoptosis, and stress responses. Although single-cell RNA sequencing technology is prevailing nowadays, it sti…
View article: Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease Open
We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information “impressions,” which allow individual ce…
View article: Additional file 5 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
Additional file 5 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease Open
Additional file 5. Differential gene expression for Subtype 1 cells
View article: Additional file 3 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
Additional file 3 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease Open
Additional file 3. HAM markers derived from Srinivasan et. al. [64]
View article: Additional file 6 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
Additional file 6 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease Open
Additional file 6. Differential gene expression for Subtype 2 cells
View article: Additional file 2 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
Additional file 2 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease Open
Additional file 2. DAA markers derived from Habib et al. [63]
View article: Additional file 4 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease
Additional file 4 of Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease Open
Additional file 4. DAM markers were derived from Keren-Shaul et al. [65]
View article: Hippocampal Subregion and Gene Detection in Alzheimer’s Disease Based on Genetic Clustering Random Forest
Hippocampal Subregion and Gene Detection in Alzheimer’s Disease Based on Genetic Clustering Random Forest Open
The distinguishable subregions that compose the hippocampus are differently involved in functions associated with Alzheimer’s disease (AD). Thus, the identification of hippocampal subregions and genes that classify AD and healthy control (…
View article: Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer
Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer Open
View article: regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data
regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data Open
Expression quantitative trait loci (eQTL) analysis is useful for identifying genetic variants correlated with gene expression, however, it cannot distinguish between causal and nearby non-functional variants. Because the majority of diseas…
View article: Extensive Involvement of Alternative Polyadenylation in Single-Nucleus Neurons
Extensive Involvement of Alternative Polyadenylation in Single-Nucleus Neurons Open
Cleavage and polyadenylation are essential processes that can impact many aspects of mRNA fate. Most eukaryotic genes have alternative polyadenylation (APA) events. While the heterogeneity of mRNA polyadenylation isoform choice has been st…
View article: Diagnostic Evidence GAuge of Single cells (DEGAS): A flexible deep-transfer learning framework for prioritizing cells in relation to disease
Diagnostic Evidence GAuge of Single cells (DEGAS): A flexible deep-transfer learning framework for prioritizing cells in relation to disease Open
We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information “impressions,” which allow individual ce…
View article: Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data
Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data Open
PURPOSE Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers.…
View article: Additional file 2 of Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer
Additional file 2 of Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer Open
Additional file 2: Supplemental Table 1. The epithelial tissue proportion data of 54 TCGA ER-positive BRCA cases. Supplemental Table 2. The ATAC-seq peak signal data of 54 TCGA ER-positive BRCA cases. Supplemental Table 3. Significant epit…