Author

Husam B. R. Alabed

University of CambridgeORCID 0000-0002-9229-088XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:database / resource· 3 Assay:metabolomics· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Dorotea Frongia ManciniiD· 3 shared Roberto Maria PellegrinoiD· 3 shared Albert KoulmaniD· 1 shared Luigina Romani· 1 shared Martina Pergola· 1 shared Sabata MartinoiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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3 shared papersBioinformatics

Dorotea Frongia ManciniORCID

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Author profile →

3 papers

Recent·Most cited

From molecular lipidomics to interpretable food lipid profiles: the Lipid Food Profile module in LipidOne

Dorotea Frongia Mancini, Husam B. R. Alabed, Roberto Maria Pellegrino

The paper introduces Lipid Food Profile (LFP), a module that converts LC/MS lipidomics data into interpretable food-relevant lipid indices, enhancing analysis of food composition and quality.

Food Bioscience · Jul 22, 2026Peer-reviewedBiochemistry

Nutritional-Metabolic Lipid Profiling with LipidOne for plasma lipidomics interpretation in metabolic health

Dorotea Frongia Mancini, Husam B. R. Alabed, Roberto Maria Pellegrino

The paper introduces NMLP, a module within LipidOne that translates plasma lipidomics data into interpretable nutritional-metabolic indices, revealing metabolic shifts and phenotypes across different dietary and health conditions.

bioRxiv · May 18, 2026 · PreprintBioinformatics

Functional Lipid Analysis via Index-Based Lipidomics Profile: A New Computational Module in LipidOne

Husam B. R. Alabed, Dorotea Frongia Mancini, Martina Pergola, Luigina Romani, Sabata Martino, Albert Koulman, Roberto Maria Pellegrino

The paper introduces a new computational module, Functional Lipid Analysis (FLA), to assess lipid function through 42 indices, linking lipidomic data to biological pathways and enabling systems-level insights.

Bioinformatics · Feb 26, 2026Peer-reviewedBioinformatics