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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.

Publications for advancing spatial insight

Publications

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

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Research Paper

Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model

In this joint work we partnered with Frontier Diagnostics, Vanderbilt and several board certified pathologists to develop a classification model capable of distinguishing melanoma from benign nevus tissue, using a MALDI-imaging based proteomics assay.
Cell segmentation / typing
Research Paper

Classification of cirrhotic patient samples based on imaging MS of multiplexed N-glycan markers in biofluids.

This poster is an example of how Aspect Analytics can be your partner to develop specialized bioinformatic and data analysis workflows for your specific use-case or application.
Pathway Analyses
Targeted Analyses
Research Paper

Annotation Studio: a web portal to support the development of IMS-based diagnostic assays

In this poster we showcased Annotation Studio, a software solution we co-developed with Frontier Diagnostics to aid them in annotating whole-slide images to develop MALDI imaging-based diagnostic assays.
Other
Research Paper

An integrated approach for analyzing spatially resolved multi-omics datasets from the same tissue section

As spatial biology methods mature, users are increasingly combining multiple readouts for a holistic view of tissue biology. This paper presents a software and a computational framework for integration and data analysis of same-section spatial transcriptomics and spatial proteomics data acquired using different spatial platforms.
Cell segmentation / typing
Cancer Research
Exploratory Analyses
spatial technologies
spatial transcriptomics
Research Paper

Evaluation of Distance Metrics and Spatial Autocorrelation in Uniform Manifold Approximation and Projection Applied to Mass Spectrometry Imaging Data

In this work, we explored the utility of a recently introduced, nonlinear dimensionality reduction method named Uniform Manifold Approximation (UMAP) for MSI data analysis.
Cell segmentation / typing
UMAP
Research Paper

Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Through the Use of Pre-trained Neural Networks

This project concerns improving unsupervised methods to cluster ion images, which enables identifying m/z bins with similar spatial expressions.
No items found.
Research Paper

Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Using Deep Learning

In this work, we use a pre-trained neural network to extract high-level features from ion images in MSI data, and test whether this improves downstream data analysis
Spatially-aware Clustering
Research Paper

Metabolite Explorer: A Software Tool for Targeted Analysis of Mass Spectrometry Imaging Data

In this poster we introduce Metabolite Explorer, a software tool that facilitates high-throughput, targeted data analysis, given data from multiple MSI experiments.
Exploratory Analyses
Research Paper

Unsupervised Machine Learning for Exploratory Data Analysis in Imaging Mass Spectrometry

In this review paper we give an extensive overview of the wide range of unsupervised machine learning methods that have been applied in the analysis of Mass Spectrometry Imaging (MSI) data.
Other

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.