MEDICAL BIOTECHNOLOGY
Research Interests
Development of bioinformatics tools for the analysis of multivariate data. Optimisation of Standard Operating Procedures. Metabolomics and genomics analysis.
Description of Research
The last few decades have witnessed an explosion of data in almost all fields, from health sciences to plant biology, to the extent that the bottleneck in research has shifted from data generation to data analysis. As a result, there is an increasing need for approaches to manage and extract useful knowledge from complex data and to develop data-based bioinformatics solutions.
The Bioinformatics Unit focuses on the development of bioinformatics tools and statistical approaches to facilitate the interpretation of data generated from high-throughput platforms, including metabolomics and genomics data. The Group’s research strategy focus is on medical sciences and plant biology, which include:
- Design of high-throughput experiments. Planning an experiment properly is very important in order to ensure that the right type of data and sufficient sample size and power are available to answer the research questions of interest as clearly and efficiently as possible.
- Developing the optimal standard operating procedures for data managing, sample collection, and processing.
- Exploratory approaches to data mining, especially those geared toward the discovery of patterns in the data for exploratory tasks using clustering and feature extraction methods. These methods are important to stratify an ensemble of samples into groups on the basis of their molecular profile.
- Classification and regression analyses of molecular profiles using machine learning algorithms. Multi-parameters models can be built to improve, for example, the diagnosis of disease using standard methods.
- Interpreting the results to gain insights into biological mechanisms through Functional analysis methods.
Recent Publications
Vignoli A, Cacciatore S, Tenori L. Deriving three one dimensional NMR spectra from a single experiment through machine learning. Nat Commun. 2025 Nov 19;16(1):10159. doi: 10.1038/s41467-025-65294-x. PMID: 41257833; PMCID: PMC12630646.
Devar J, Elebo N, Makan A, Pincus A, Lahoud N, Cacciatore S, Candy G, Smith M, Nweke EE. Distinct Metabolomic and Lipoprotein Signatures in Gall Bladder Cancer Patients of Black African Ancestry. Cancers (Basel). 2025 Sep 6;17(17):2925. doi: 10.3390/cancers17172925. PMID: 40941022; PMCID: PMC12428709.
Duarte-Delgado NP, Bello-Gualtero JM, Fernández-Ávila DG, Romero-Sánchez C, Cacciatore S, Cala MP, Rodríguez Camacho LS. Metabolic Alterations in Colombian Women with Rheumatoid Arthritis and Systemic Lupus Erythematosus Reveal Potential Lipid Biomarkers Associated with Inflammation and Cardiovascular Risk. Int J Mol Sci. 2025 May 9;26(10):4527. doi: 10.3390/ijms26104527. PMID: 40429671; PMCID: PMC12111616.
Zinga MM, Kassim Mohamed M, Ojo D, Mohamed Abdoul-Latif F, Mkassy FI, Wilfred D, Marwa KJ, Cacciatore S. Exploratory Serum Metabolomic Profiling of Asymptomatic Malaria Children Infected with Plasmodium falciparum in Tanzania. J Proteome Res. 2026 Jan 2;25(1):395-404. doi: 10.1021/acs.jproteome.5c00742. Epub 2025 Dec 9. PMID: 41363101.
Duarte-Delgado NP, Rodríguez C LS, Cacciatore S. Comparative 1H NMR Lipoprotein Profiling of Rheumatoid Arthritis and Systemic Lupus Erythematosus Patients Highlights Disease-Specific Lipoprotein Dysregulation. J Proteome Res. 2026 Apr 3;25(4):1903-1913. doi: 10.1021/acs.jproteome.5c00957. Epub 2026 Mar 17. PMID: 41843662.
Onyia AF, Olasehinde OE, Shagaya U, Nwachukwu E, Oyekan A, Fatiregun O, Olatunji T, Lawal A, Alabi A, Aje EA, Sowunmi A, Ogunniyi OB, Ogo CN, Nkom ES, De Campos OC, Rotimi OA, Oyelade J, Ajibola TOP, Anake TA, Elebo N, Nweke EE, Zerbini LF, Cacciatore S, Rotimi SO. 1H NMR-Based Plasma Metabolomics and Machine Learning Reveal Distinct Metabolic Signatures of Breast Cancer in Nigerian Women. J Proteome Res. 2026 Jun 5;25(6):2709-2722. doi: 10.1021/acs.jproteome.5c00965. Epub 2026 Apr 27. PMID: 42045116.
Programme Officer
Stefano Cacciatore
ICGEB Cape Town, South Africa
E-mail: [email protected]
Tel: +27 21 650 1865
Group Leader CV
Dalia Ahmed (Postdoctoral Fellow)
Moussa Kassim (PhD student)
Martin Ocharo (PhD student)
Dupe Ojo – Research Technician
