Sergii Domanskyi

DIANNE: Segmentation-Free Localization of Histology Differential Attributes

DIANNE enables rapid training and inference of spatial differential attributes in histology images without manual annotations, using mixup augmentation and foundation models.

Distinct senescent β-cell senotypes differentially drive islet aging and dysfunction

The paper identifies two distinct senescent β-cell subpopulations with different functional roles in islet aging and dysfunction using single-cell proteomics and transcriptomics.

SenNet Portal: Build, Optimization and Usage

The paper introduces the SenNet Portal, a resource for senescent cell data and tools, and discusses its usage and future developments.

A human and mouse subpopulation of senescent β-cells induces pathologic dysfunction through targetable paracrine signaling

The paper identifies senescent β-cell subpopulations in humans and mice that induce pathologic dysfunction through paracrine signaling and shows JAK inhibitors can reverse this effect.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples

The paper develops a Nextflow pipeline for processing Visium spatial transcriptomics and H&E images from PDX samples, enabling multi-modal analysis and integration of spatial gene expression and morphometric features.

Spatiotemporal profiling defines persistence and resistance dynamics during targeted treatment of melanoma

This study uses spatial transcriptomics and deep learning to analyze melanoma treatment resistance, identifying persister states and resistance mechanisms with spatiotemporal resolution.

ACDA: Implementation of an Augmented Drug Synergy Prediction Algorithm

The paper improves a drug synergy prediction algorithm by using random forest regression and cross-validation, achieving better performance and robustness than the original method and competing algorithms.

Naturally occurring combinations of receptors from single cell transcriptomics in endothelial cells

The paper identifies naturally occurring receptor combinations in endothelial cells using single-cell data and introduces a software tool to analyze them, showing evolutionary conservation and relevance to angiogenesis.

Visibility Graph Based Community Detection for Biological Time Series

The paper introduces a visibility graph-based method to detect temporal communities in biological time series and validates it on simulated and experimental data.

Digital Cell Sorter (DCS): a cell type identification, anomaly detection, and Hopfield landscapes toolkit for single-cell transcriptomics

The paper introduces DCS, a toolkit for scRNA-seq analysis that includes cell type identification, anomaly detection, and visualization tools, demonstrating its effectiveness on PBMC and plasma cell datasets.

Longitudinal Saliva Omics Responses to Immune Perturbation: A Case Study

This study tracks saliva omics changes over time in response to immune perturbation, revealing broad immune responses in both innate and adaptive timeframes.

PyIOmica: Longitudinal Omics Analysis and Classification

PyIOmica integrates and classifies longitudinal omics datasets using tools for normalization, visualization, and pathway analysis.

Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters

The paper introduces a tool for automatically assigning cell types to scRNA-seq clusters using a voting algorithm based on molecular markers, validated on bone marrow data from the Human Cell Atlas.