25th BioPharma Drug Discovery Nexus 2026, Zurich
Nygen at the 25th BioPharma Drug Discovery Nexus in Zurich, April 29–30, 2026. Session with Parashar Dhapola on AI agents versus AI workflows for single-cell annotation at scale.
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A curated index of articles, updates, events, and published work across single-cell research.
Beyond Biotech - the podcast from Labiotech
Parashar and Dylan discusses where AI truly delivers in biopharma, the persistent gaps in exploratory data analytics, and the critical bottlenecks in single-cell annotation. In a world abounding in AI hype, Parashar helps us cut through the noise and point out paths to data driven success.
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Everyone Is Building AI Agents for Drug Discovery. We Built a Workflow for One Task. Here's Why.
Why we rebuilt CyteType as a deterministic AI workflow instead of an agent, and why that distinction matters for production cell annotation pipelines.
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What We Got Wrong About AI Agents for Cell Annotation
Running CyteType's AI agents across thousands of single-cell RNA-seq datasets in production exposed run-to-run variance, selective evidence gathering, and inconsistent depth. We rebuilt cell type annotation as a deterministic LLM workflow for reproducible, auditable results in drug discovery pipelines.
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Accelerated Single-Cell Data Analysis | Free Course by Nygen
A free, hands-on single-cell RNA-seq and multi-omics course. Learn to go from raw data to biologically interpretable results in under 3 hours using ScarfWeb.
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Integrating Multi-Omics Data for Effective Target Identification in Drug Discovery
Discover how multi-omics integration is reshaping drug discovery by uncovering disease mechanisms, prioritizing drug targets, and connecting genomics, epigenomics, transcriptomics, proteomics, and metabolomics into a usable biological model.
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Public single-cell RNA-seq databases worth using in 2026
An updated guide to the most useful public single-cell RNA-seq databases in 2026, including archives, atlas portals, and domain-specific resources for data discovery and reuse.
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Startups & Single Cells: A Fireside Chat on CyteType - a Multi-Agent AI for Robust Cell Annotation
Fireside chat with Parashar Dhapola on building Nygen and how CyteType uses multi-agent AI for evidence-grounded cell annotation. Hosted by BIOTECH XYZ.
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Glasgow Computational Biology Community Event
Deep learning and agentic AI analysis of single-cell RNAseq data.
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DYRK1A & Striatal Development: A Single-Cell Analysis Journey
Veronique Brault uses single-cell RNA-seq to study how DYRK1A gene dosage affects striatal development in Down syndrome and intellectual disability mouse models.
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Insights from single-cell omics: cellular heterogeneity as a foundation of clinical outcome in chronic myeloid leukemia
Ram Krishna Thakur, Göran Karlsson explore how single-cell omics reveals cellular heterogeneity driving clinical outcomes in CML.
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CyteType: Evidence-Based Cell Annotation with Multi-Agent AI
CyteType uses a five-agent AI framework for accurate cell type annotation in scRNA-seq data. Outperforms reference-based methods by 300%+ in benchmarking.
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CyteType: Multi-Agent AI Transforming Single-Cell Annotation
Explore why LLMs alone fail at cell annotation and how CyteType fixed it.
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VLP Therapeutics Teams with Swedish AI Biotech Nygen Analytics on Vinnova-Funded Cancer Immunotherapy Research
Nygen Analytics wins 1M SEK Vinnova grant to develop AI-powered predictive models for cancer immunotherapy with VLP Therapeutics, advancing personalized treatment selection.
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The Laboratory Advancing Polish Science One Cell at a Time
Inside the Institute of Bioorganic Chemistry Polish Academy of Sciences, a state-of-the-art laboratory charts an ambitious course for single-cell analysis in Poland.
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IBCH Poznan x Nygen - Accelerated Single Cell Data Analysis Course
Hands-on single-cell RNA-Seq and multi-omics analysis course at IBCH Poznan.
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LMU Klinikum x Nygen - Accelerated Single Cell Data Analysis Course
Accelerated single-cell data analysis course with LMU Klinikum.
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University of St. Andrews x Nygen - Accelerated Single Cell Data Analysis Course
Hands-on single-cell data analysis course at University of St. Andrews.
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SCOP King's College x Nygen - Accelerated Single Cell Data Analysis Course
Hands-on single-cell data analysis course at King's College London.
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Why We Built AI Agents That Actually Understand Single Cell Data
CyteType is multi-agentic annotation system designed for single-cell RNA-seq cluster annotation. Designed to deploy three specialized AI agents to provide accurate cell type identification, literature validation, and pathway-level reasoning beyond traditional marker-based methods and beyond. Built for researchers seeking precise, evidence-backed single-cell data analysis with comprehensive biological context.
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Pioneering Partnership: King's College London's SCOP is Redefining Collaborative Science
An year-old facility is quietly revolutionizing how core services support cutting-edge research. Through a partnership built on scientific curiosity and shared problem-solving,
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Max-Planck-Institut x Nygen - Accelerated Single Cell Data Analysis Course
Accelerated single-cell data analysis course with Max-Planck-Institut.
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Porto's Bioinformatics Core Democratizing Single-Cell Analysis
Discover how Porto's i3S bioinformatics core facility is democratizing single-cell analysis for researchers across cancer, neurobiology, and infectious disease studies.
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i3S Porto x Nygen - Accelerated Single Cell Data Analysis Course
Hands-on single-cell RNA-Seq and multi-omics analysis course at i3S Porto.
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One Scientist, Many Discoveries: Scotland's Nimble Single-Cell Facility
Meet Aleksandra Wcislo, the sole operator of BBSRC's Single Cell Sequencing Platform at St Andrews. Discover how one scientist manages everything from bat genomes to placental cells, proving that excellence in genomics doesn't require a large team.
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IGBMC x Nygen - Accelerated Single Cell Data Analysis Course
Accelerated single-cell data analysis course with IGBMC.
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Spatial Transcriptomics and Single-cell RNA-seq: Complementary Technologies for Next-Generation Biology
Discover how spatial transcriptomics and single-cell RNA-seq complement each other to drive next-generation biological insights. Learn about emerging platforms, multi-omics integration, and how Nygen Analytics empowers researchers to leverage both technologies.
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Enriching Insights with Single-cell RNA-seq: Integrating Spatial Data Strategically
Discover how integrating spatial transcriptomics with scRNA-seq data enhances biological insights by mapping gene expression to tissue architecture. Learn key integration methods and real-world applications.
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UCM Madrid x Nygen - Accelerated Single Cell Data Analysis Course
Accelerated single-cell data analysis course with UCM Madrid.
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Punching Above Their Weight: The Hidden Genomics Powerhouse of Spain's Sun-Soaked Coast
In sunny Alicante, two specialists have built an impressive Omics Core Facility that rivals larger institutions. We sat down with Antonio and José to understand their science, approach to experiment design and collaborative methods drives breakthrough research with a lean, efficient operation.
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Nygen Secures ISO 27001 and SOC 2 Certifications
Nygen Analytics, the only single-cell–focused omics data-analytics platform to pair ISO 27001 certification and SOC 2 compliance with full GDPR alignment
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When is Single-cell RNA-seq Enough? Practical Guidance for Choosing Your Analysis Method
Discover when single-cell RNA sequencing is sufficient for your research needs. This guide explains ideal use cases, analysis techniques, and practical implementations for leveraging scRNA-seq data effectively.
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No-Code Workflow for Marker Gene Identification (Step-by-Step) on Nygen
Learn how to identify marker genes in single-cell RNA-seq data without coding using Nygen's intuitive platform. This step-by-step guide covers data upload, quality control, clustering, marker detection, and dynamic analysis with detailed screenshots and expert tips.
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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
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
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
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
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 scRNA-seq cluster annotation in 2026, covering marker gene inspection, reference atlas mapping, supervised classification tools, and strategies for resolving ambiguous or disease-associated populations.
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Powerful scRNA-seq Data Analysis Tools in 2025
Uncover the top single-cell RNA sequencing (scRNA-seq) and multi-omics data analytics tools of 2025. This comprehensive guide reviews 8 platforms to facilitate data analysis and reveal cellular insights.
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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
Gautam Ahuja et al. demonstrate how multi-agent AI systems enable evidence-based cell annotation in scRNA-seq data.
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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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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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Building Cell Atlases - Navigating Biology Like Google Maps Navigates the World
Discover how building cell atlases parallels Google Maps - transforming scattered cellular data into integrated, navigable maps for drug discovery.
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Understanding Batch Effect and Normalization in scRNA-Seq Data
A practical guide to batch effect correction and normalization in scRNA-seq data, covering when integration is justified, leading tools including Harmony, Seurat, BBKNN, and scVI, evaluation strategies, and how to avoid overcorrection.
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Overcoming Bioinformatics Skill Gaps in Single-Cell Research
Discover solutions to bridge bioinformatics skill gaps in single-cell research, enabling easier scRNA-seq analysis for wet-lab scientists.
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What is Single Cell Transcriptomics?
Discover single-cell transcriptomics, a transformative technique for analyzing gene expression at the cellular level in biology and medicine.
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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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Spatiotemporal transcriptomic map of glial cell response in a mouse model of acute brain ischemia
Daniel Zucha et al. map glial cell responses over time in a mouse brain ischemia model using spatial transcriptomics.
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Tracking early mammalian organogenesis – prediction and validation of differentiation trajectories at whole organism scale
Ivan Imaz-Rosshandler et al. predict and validate cell differentiation trajectories during early mammalian organogenesis.
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EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data
Sijie Li et al. introduce EpiCarousel for efficient metacell identification in large-scale chromatin accessibility datasets.
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Characterization of regeneration initiating cells during Xenopus laevis tail regeneration
Radek Sindelka et al. characterize cells that initiate regeneration during Xenopus tail regrowth.
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CTEC: a cross-tabulation ensemble clustering approach for single-cell RNA sequencing data analysis
Liang Wang et al. present CTEC, an ensemble clustering method for robust scRNA-seq data analysis.
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Single cell multi-omics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response
Rebecca Warfvinge et al. link single-cell multi-omics heterogeneity in CML to variations in therapy response.
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A guide to single-cell RNA sequencing analysis using web-based tools for non-bioinformatician
Sagnik Yarlagadda and Todd D. Giorgio provide a practical guide to scRNA-seq analysis using web-based platforms.
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Single-cell multiomics of human fetal hematopoiesis define a developmental-specific population and a fetal signature
Mikael N. E. Sommarin et al. define developmental-specific populations in human fetal blood formation using multi-omics.
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Scarf enables a highly memory-efficient analysis of large-scale single-cell genomics data
Parashar Dhapola et al. introduce Scarf for memory-efficient single-cell sequencing analysis, published in Nature Communications.
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