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Reproducible proteomics

The lack of reproducible science in proteomics analyses – a bioinformatics perspective

Objective and aims: The objective of this literature review is to critically examine the challenges associated with the complexity and variability of available frameworks in proteomics analyses. Specifically, it aims to:

  • Assess the extent and impact of inherent proteomics data analysis heterogeneity.
  • Evaluate the role of non-standardized protocols and data analysis pipelines in contributing to the lack of reproducibility in proteomics research.
  • Investigate the proposed solution of establishing community-wide efforts to develop standardized protocols and guidelines for data analysis in proteomics, with a focus on its feasibility, effectiveness, and adoption within the scientific community.
  • Develop a recommended scoring system for reproducible proteomics frameworks. By addressing these objectives, this literature review seeks to provide a comprehensive overview of the challenges and potential solutions related to reproducibility in proteomics research, offering insights into the current state of the field and avenues for improvement.

An attempted literature search for reproducible proteomics analyses:

lit search

Team members:

Coetzer, K.C(1), Aidoo, A.S(2), Adomako N.A(1,4), Ajiboye, I.O(5,6), Nortey H.(3), Okello, O.I(7), and Awe, O.I(8)

  1. Department Biomedical Sciences, Division of Molecular Biology and Human Genetics, Stellenbosch University, Cape Town, South Africa

  2. Department of Virology, Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Legon, Accra, Ghana.

  3. Department of Clinical Pathology, Noguchi Memorial Institute for Medical Research, College of Health Sciences, University of Ghana, Legon, Accra, Ghana.

  4. Department of Molecular Medicine, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

  5. Covenant Applied Informatics and Communication Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Nigeria.

  6. Department of Computer and Information Sciences, College of Science and Technology, Covenant University, Ota, Nigeria.

  7. Department of Immunology and Molecular Biology, College of Health Sciences, School of Biomedical Sciences, Makerere University, Kampala, Uganda.

  8. African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.