Skip to content
#explainable ai Review Open access

MALDI-Based Multiomics and Spatial Molecular Profiling—Principles, Integrated Workflows, Biomedical Applications, and Future Perspectives: A Systematic Review

Sep 2026 · Biophysica · 183 references
Mass Spectrometry Techniques and Applications

Abstract

Although expression-based omics has greatly contributed to biological research, the biochemical state of cells or tissues cannot be fully explained by transcript or gene expression data alone. This systematic review investigated when matrix-assisted laser desorption/ionisation (MALDI)-based approaches can support the integration of multiple molecular layers and when they remain limited to single-class molecular mapping. PubMed was searched between 1 February and 8 June 2026. English-language peer-reviewed publications relevant to the principles, methods, molecular classes, or biomedical applications of matrix-assisted laser desorption/ionisation-based multiomics were eligible. Publications outside this scope were excluded. Records were independently screened by two reviewers, and disagreements were resolved through discussion. The findings were narratively synthesised based on the analytical platform, molecular layer, integrated spatial multiomics, spatial application, and biomedical use. The methodological quality and risk of bias were not formally assessed, which limits the certainty and strength of the conclusions drawn from this narrative synthesis. Following the reapplication of the relevance criteria, 111 publications from 1633 identified records were included in the final review. The evidence was reclassified and presented separately as true multilayer MALDI studies, MALDI integrated with orthogonal modalities, and background uniomics or spatial molecular profiling studies. These publications included human, animal, cellular, tissue-based, and methodological studies. These publications cover many molecular classes and biomedical applications. As many publications did not involve human participants, a single pooled participant total was not applicable to this study. Matrix-assisted laser desorption/ionisation-based techniques were used to analyse metabolites, lipids, glycans, peptides, and intact proteins in the reviewed literature. The literature also shows that spatial information can be retained using matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI-IMS). Its ability to map molecular signals back to specific tissue regions or areas associated with disease supports its potential clinical utility. Specific areas of application, such as cancer, neurological, and infectious disease research, are also reviewed. The use of matrix-assisted laser desorption/ionisation-based techniques for biomarker discovery has been evaluated. Small sample sizes, proof-of-concept designs, inconsistent outcome reporting, and limited external validation have limited the evidence. Technical limitations include ion suppression, limited quantification, sample preparation variability, and differing analyte sensitivity. Emerging developments, such as single-cell imaging and AI analysis, have also been explored. Matrix-assisted laser desorption/ionisation enables multiomics when two or more complementary molecular layers are analysed and integrated within the same biological system. When only a single molecular class is analysed, the approach remains spatial molecular mapping rather than multiomic analysis. However, before matrix-assisted laser desorption/ionisation-based approaches can be applied in routine clinical practice, standardised workflows and better quantitative methods are needed. This review received no external funding and was not registered.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations
#artificial intelligence Conference Open access Jun 2018

The Key Concepts of Ethics of Artificial Intelligence

It is suggested that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.

Ville Vakkuri, P. Abrahamsson · 39 citations · ⚡2

Related blog posts

GPT-Lab Sep 17, 2026

Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering

AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.

MIT News · Artificial Intelligence Sep 14, 2026

New method enables AI for safety-critical situations

The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.