Aleksandr Ianevski

Selective scoring of drug effects in multicellular co-culture systems

The paper introduces CES, a computational framework to score drug effects in multicellular co-culture systems, distinguishing between immunomodulatory effects and toxicity.

Improving reproducibility in pharmacogenomic screens through cross-study benchmarking

This paper benchmarks pharmacogenomic studies to improve reproducibility by identifying key factors causing inconsistency and introducing a standardized Drug Response Score (DRS) and resource.

Multimodal immunopharmacologic screens identify drugs rewiring the cancer-immune interface

The paper identifies drugs that rewiring the cancer-immune interface by enhancing NK cell function and tumor susceptibility through multimodal screening approaches.

A statistical framework for defining synergistic anticancer drug interactions

The paper establishes a statistical framework to identify synergistic anticancer drug interactions using large-scale cell line data and reference null distributions.

Spatial artefact detection improves reproducibility of drug screening experiments

The paper introduces a control-independent QC method to detect spatial artefacts in drug screening experiments, improving reproducibility between technical replicates and cross-dataset correlation.

JAK inhibitors remove innate immune barriers facilitating viral propagation

This study shows JAK inhibitors like baricitinib suppress IFN-stimulated genes, aiding viral propagation by reducing antiviral defenses.

Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones

The paper develops a machine learning model to identify patient-specific multi-targeting therapies using single-cell transcriptomic data for hematological cancers and solid tumors.

Discovery of host-directed modulators of virus infection by probing the SARSCoV-2-host protein-protein interaction network

The paper identifies host proteins modulating SARS-CoV-2 infection by expanding the virus-host protein interaction network and testing chemical inhibitors of these targets.

Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data

ScType automates cell-type identification from scRNA-seq data using marker genes, achieving accurate and unbiased annotations across human and mouse tissues.

Patient-tailored design of AML cell subpopulation-selective drug combinations

This paper develops a computational-experimental approach to design patient-specific drug combinations for AML that are synergistic and minimally toxic.

Histopathological Landscape of Molecular Genetics and Clinical Determinants in MDS Patients

This study uses deep learning to analyze bone marrow histopathology in MDS patients, linking morphological features to genetic and clinical outcomes.

SynToxProfiler: an approach for top drug combination selection based on integrated profiling of synergy, toxicity and efficacy

SynToxProfiler prioritizes drug combinations by integrating synergy, efficacy, and toxicity profiles to improve clinical success likelihood.