Resources

A curated index of articles, updates, events, and published work across single-cell research.

Showing 46–60 of 71

No-Code Marker Gene Identification Workflow in ScarfWeb

No-Code Marker Gene Identification Workflow in ScarfWeb

Find marker genes in scRNA-seq without code using ScarfWeb. Step-by-step walkthrough from upload and QC through clustering, marker detection, pseudotime, and export.

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UMH Alicante x Nygen - Accelerated Single Cell Data Analysis Course
09:00 CET UMH, Alicante, Spain

UMH Alicante x Nygen - Accelerated Single Cell Data Analysis Course

Hands-on single-cell data analysis course at UMH Alicante.

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Accelerate Marker Gene Detection in scRNA-seq: A No-Code Approach

Accelerate Marker Gene Detection in scRNA-seq: A No-Code Approach

Uncover the essentials of marker gene identification in single-cell RNA sequencing. This article covers no-code solutions, methodologies, and case studies across various fields.

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Med Uni Graz x Nygen - Accelerated Single Cell Data Analysis Course
14:30 CET Online

Med Uni Graz x Nygen - Accelerated Single Cell Data Analysis Course

Accelerated single-cell data analysis course with Medical University of Graz.

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Designing Robust Single-Cell RNA-Seq Experiments: A Practical Guide

Designing Robust Single-Cell RNA-Seq Experiments: A Practical Guide

Learn the essentials of designing robust single-cell RNA-seq experiments with our practical guide for wet-lab scientists. Covers sample preparation, controls, sequencing parameters, and analysis approaches, including how no-code platforms eliminate computational barriers.

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AGI is Far, but ASI is Here

AGI is Far, but ASI is Here

Explore how ASI transforms drug discovery by harnessing domain-specific models and advanced computing tools for faster, smarter biomedical innovation.

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A Practical Guide to Single-Cell RNA-Seq Cluster Annotation

A Practical Guide to Single-Cell RNA-Seq Cluster Annotation

How to annotate scRNA-seq clusters in 2026: marker genes, reference mapping, supervised tools, and separating cell identity from cell state.

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Best scRNA-seq Analysis Tools in 2026: Compared

Best scRNA-seq Analysis Tools in 2026: Compared

Compare ScarfWeb, Loupe Browser, Trailmaker, Partek Flow, BBrowserX Pro, Omics Playground, Pluto Bio, and ROSALIND for scRNA-seq and multi-omics analysis in 2026.

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Transcriptional Roadmap of the Human Airway Epithelium Identifying HLF as a Novel Regulator of Basal Stem Cell Function

Transcriptional Roadmap of the Human Airway Epithelium Identifying HLF as a Novel Regulator of Basal Stem Cell Function

Pavan Prabhala et al. map the transcriptional landscape of human airway epithelium, identifying HLF as a key regulator.

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Chromatin Accessibility Shapes Developmental-Specific Lineage Plasticity in Hematopoiesis

Chromatin Accessibility Shapes Developmental-Specific Lineage Plasticity in Hematopoiesis

Sara Palo et al. reveal how chromatin accessibility patterns shape lineage plasticity during blood cell development.

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Alphavirus replicon particle expressing IL-12 reprograms tumor-associated macrophages and neutrophils and induces anti-tumor immunity

Alphavirus replicon particle expressing IL-12 reprograms tumor-associated macrophages and neutrophils and induces anti-tumor immunity

Momoko Ishikawa et al. show IL-12-expressing alphavirus particles reprogram tumor immune cells to induce anti-tumor responses.

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Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics

Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics

Gautam Ahuja et al. demonstrate how multi-agent AI systems enable evidence-based cell annotation in scRNA-seq data.

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Building Cell Atlases: Mapping Biology Like Google Maps

Building Cell Atlases: Mapping Biology Like Google Maps

Discover how building cell atlases parallels Google Maps - transforming scattered cellular data into integrated, navigable maps for drug discovery.

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Batch Effect Correction and Normalization in scRNA-Seq

Batch Effect Correction and Normalization in scRNA-Seq

Compare scRNA-seq normalization and batch correction methods, with current Seurat, Scanpy, Monocle 3, scran, Harmony, BBKNN and scVI workflows.

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Navigating the Complexity of Single-Cell RNA-Seq Data Analysis

Navigating the Complexity of Single-Cell RNA-Seq Data Analysis

Explore key challenges and advanced strategies in scRNA-seq data analysis for both new and experienced researchers.

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