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Explore peer-reviewed studies, technical notes, and posters that show how spatial and multimodal data can reveal mechanisms, guide decisions, and accelerate discovery.

News & Blogs for advancing spatial insight

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News & blogs

See how research teams use Weave to align modalities, analyze multicellular environments, validate mechanisms, and compare cohorts with reproducible workflows.

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Blog Post

MSI hardware part 2: mass analyzers

In continuation of our quest to elucidate technical terms in mass spectrometry, this post describes the most commonly used mass analyzers in imaging, namely time of flight (TOF), Orbitrap and Fourier transform ion cyclotron resonance (FTICR).
Neighbourhood Analysis
Targeted Analyses
Spatially-aware Clustering
Blog Post

MSI hardware part 1: ionization techniques

Are you confused by all the acronyms used in mass spectrometry imaging? In this post, we will describe the main ionization techniques and tackle some of those pesky acronyms in the process.
Other
Blog Post

Non-negative matrix factorization in MSI

In this blog post, we continue our overview of unsupervised data analysis approaches commonly used in MSI, diving deeper into factorization methods. This time we will take a closer look at the results of principal component analysis (PCA) in MSI, and compare these to the results of nonnegative matrix factorization (NMF).
Other
Blog Post

Factorization of MSI data - part 1

In this first post of the series, we will discuss three linear approaches to factorization of MSI data, namely Principal Component Analysis (PCA), PCA + Varimax and Independent Component Analysis (ICA).
Neighbourhood Analysis
Pathway Analyses
Blog Post

Clojure, I Choose You!

As a software development company, choosing the right tools for the job is of paramount importance. In this post, we will explain why we opted to use Clojure for the full web stack of our platform. When building complex software, leveraging a language that not just supports but actively promotes good engineering practices provides key benefits in terms of efficiency, readability, maintenance and robustness.
Other
Blog Post

Introduction to mass spectrometry imaging data analysis

In this post, we provide a high-level introduction to MSI technology along with the specific challenges and opportunities it brings in terms of data analysis. This post focuses on introducing some nomenclature and describing the main aspects about working with MSI data from a data science perspective.
Exploratory Analyses
Targeted Analyses
Webinar On Demand: From Spatial Biology to Clinical Insight, Aspect Analytics
Webinar

Webinar On Demand: From Spatial Biology to Clinical Insight

Spatial biology is entering a new phase, moving from technology development to real-world clinical applications. In this webinar, Prof. Arutha Kulasinghe (University of Queensland) and Dr. Marc Claesen (CTO, Aspect Analytics) explore how to turn complex tissue biology into actionable insight.
spatialomics
Videos
cellular neighborhoods
spatial proteomics
spatial technologies
Blog Post

Introduction to mass spectrometry data analysis

Mass spectrometry (MS) is an analytical technology that measures the mass-to-charge ratio (m/z) of one or more molecules present within a sample and determines their relative abundance. In this introductory post, we will briefly discuss how mass spectrometry works and point out some intricacies of MS data.
Other
Pathway Analyses
Targeted Analyses

FAQs

Understanding Weave®, spatial biology, and multimodal analysis

Still have questions?

Does Weave support collaboration across teams and projects?

Weave supports multi-user, multi-team projects. With our shareable and compliant workspaces, different team members can collaborate in real-time on the same datasets in one governed workspace. Biologists, pathologists, computational biologists, and data leaders can interactively visualize and explore the same measurements and derived results, for both single and multi omics datasets. True democratization of spatial biology insights.

Can Weave be operationalized at the enterprise level?

Yes. Weave is enterprise-ready – not only do we have ISO 27001 and ISO 27018-certified data security and handling of PII, but also SSO integration with industry-standard federated authentication servers. In addition, we have scalable storage and computation resources with hosted and on-premise deployment options with SDK and CLI interfaces for systems integration. Our users routinely manage up to petabytes of spatial biology and associated data within Weave.

Can I see examples of published work using Weave?

Yes. Browse our publication section above to explore peer-reviewed studies, application notes, posters, and collaborative projects demonstrating how Weave supports spatial and multimodal research across disease areas.

How do I know if Weave is right for my project?

If your research involves tissue architecture, spatial biomarkers, spatial multi-omics integration, PK/PD readouts, or mechanistic interpretation, Weave provides a reproducible and scalable analytical framework. You can start with a single study and expand to multi-cohort programs.

Is it possible to automate recurring analyses?

Yes. Using the Weave SDK, our team can help you integrate your in-house pipelines, build reusable workflows, visualization modules, or reporting templates to reduce manual work and support high-throughput projects.

Can Aspect Analytics help if we don’t have internal computational resources?

Yes. Aspect Analytics offers data analysis services from our expert team who have over a decade of experience in spatial bioinformatics and data analysis. Weave is entirely cloud-based, so you don’t need local processing power or specialized infrastructure to analyze spatial multi omics data. Taken together, our team can remotely support you with study-level data integration, cellular neighborhood analysis, workflow development and more, while your teams access the results and reusable workflows directly in the cloud. This collaboration keeps your projects moving even without in-house computing or engineering support.

How does Weave support translational and drug development teams?

Weave enables spatial PK/PD analysis, MoA exploration, responder vs. non-responder comparisons, and more. The platform produces deeper insights, and makes it easy to interpret and share across preclinical and translational groups. By providing a collaborative and secure environment, Weave turns massive, multi-modal spatial datasets into actionable insights to accelerate your drug discovery and development pipelines.

What makes Weave different from other spatial analysis tools?

Weave provides the computational foundation to unify and analyze data across the multiple layers of spatial biology, histology, and metadata. It supports multimodal co-registration, comparative cohort analysis, model-ready outputs, and custom workflow development, bringing clarity to complex spatial data. Weave is also certified against the ISO 27001 and ISO 27018 standards for information security and handling of Personally Identifiable Information (PII).

What kinds of biological questions can Weave help answer?

Weave is used to explore cell-cell interactions, cellular neighborhoods & spatial niches, ligand–receptor communication, PK/PD and drug distribution, pathway activity, and tissue-level mechanisms that drive disease progression or therapeutic response. Weave enables finding spatial and/or molecular signatures indicative of disease status, treatment response, etc.

How does Weave help with multi-site or multi-cohort studies?

Weave standardizes quality control, spatial alignment and integration, and lineage tracking across sites, batches, and instruments. This creates reproducible, comparable datasets that support biomarker discovery, patient stratification, and translational analysis.

Can I integrate data generated outside of Weave?

Yes. External transcriptomics, proteomics, MSI, or histology annotation files can be ingested and integrated. You can also load data that has been preprocessed using your in-house pipelines, or cell segmentation results from a pipeline you have optimized for your use-case. This lets you build complete, multi-layered datasets even when parts of the workflow happen elsewhere.

Can Weave analyze data from different platforms or vendors?

Yes. Aspect Analytics is vendor-neutral and works with all major spatial biology technologies. Supported platforms include Xenium, Visium, CosMx, COMET, PhenoCycler, IMC, assorted microscopy vendors, MALDI and DESI-MSI, and more. Core capabilities of Weave include analysis of large-scale projects using single or a limited number of spatial assays, or cross-platform harmonization across different modalities for comprehensive multi-omic characterization.

Do I need advanced computational expertise to use Weave?

No. Biologists, pathologists, and computational scientists can all work within Weave. The Weave GUI supports visual analysis without coding, while the Weave SDK allows computational users to extend workflows or build custom analyses.

What kinds of data can I analyze with Weave?

Weave software supports histology, spatial transcriptomics, spatial proteomics, multiplex imaging, mass spectrometry imaging (MSI), and complementary single-cell omics at scale. These layers can be aligned, harmonized, and compared within one governed analytical backbone.