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A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach
Tan MS, Cheah PL, Chin AV, Looi LM, Chang SW.. Computers in biology and medicine, 2021-10-14
Topic: Amyloid, tau and blood-test diagnosis
Plain-language summary
Alzheimer's Disease (AD) is a neurodegenerative disease that affects cognition and is the most common cause of dementia in the elderly. As the number of elderly individuals increases globally, the incidence and prevalence of AD are expected to increase. At present, AD is diagnosed clinically, according to accepted criteria. The essential elements in the diagnosis of AD include a patients history, a physical examination and neuropsychological testing, in addition to appropriate investigations such as neuroimaging. The omics-based approach is an emerging field of study that may not only aid in the diagnosis of AD but also facilitate the exploration of factors that influence the development of the disease. Omics techniques, including genomics, transcriptomics, proteomics and metabolomics, may reveal the pathways that lead to neuronal death and identify biomolecular markers associated with AD. This will further facilitate an understanding of AD neuropathology. In this review, omics-based approaches that were implemented in studies on AD were assessed from a bioinformatics perspective. Current state-of-the-art statistical and machine learning approaches used in the single omics analysis of AD were compared based on correlations of variants, differential expression, functional analysis and network analysis. This was followed by a review of the approaches used in the integration and analysis of multi-omics of AD. The strengths and limitations of multi-omics analysis methods were explored and the issues and challenges associated with omics studies of AD were highlighted. Lastly, future studies in this area of research were justified.
What this study adds
Evidence grade: Low
This is a narrative review. This review compares statistical and machine learning approaches used in omics-based studies of Alzheimer's disease. It suggests omics techniques may help identify biomolecular markers and pathways, but it is a review of methods, not a treatment or cure.
Taken from this record’s own fields, not from reading the paper. The grade is assigned from the abstract’s wording; what that means.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Tan, M. S., Cheah, P. L., Chin, A. V., Looi, L. M., & Chang, S. W. (2021). A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach. Computers in biology and medicine. https://doi.org/10.1016/j.compbiomed.2021.104947
Vancouver
Tan MS, Cheah PL, Chin AV, Looi LM, Chang SW. A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach. Computers in biology and medicine. 2021. doi:10.1016/j.compbiomed.2021.104947. PMID: 34678481.
BibTeX
@article{tan2021-34678481,
author = {Tan, M. S. and Cheah, P. L. and Chin, A. V. and Looi, L. M. and Chang, S. W.},
title = {{A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach}},
journal = {Computers in biology and medicine},
year = {2021},
doi = {10.1016/j.compbiomed.2021.104947},
pmid = {34678481},
url = {https://doi.org/10.1016/j.compbiomed.2021.104947}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
Key findings
- Omics techniques, including genomics, transcriptomics, proteomics and metabolomics, may reveal the pathways that lead to neuronal death and identify biomolecular markers associated with AD.
- The strengths and limitations of multi-omics analysis methods were explored and the issues and challenges associated with omics studies of AD were highlighted.
Why it matters
This review compares statistical and machine learning approaches used in omics-based studies of Alzheimer's disease. It suggests omics techniques may help identify biomolecular markers and pathways, but it is a review of methods, not a treatment or cure.
New to this subject? Start with our plain-English guide: Digital health →
Study details
- Evidence strengthLow
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Computers in biology and medicine) |
| Journal's citation record | 2 / 4 | Computers in Biology and Medicine: journal h-index 189 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2021 — within 6 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 62 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 8.9 citations a year over 7 year(s) since 2021 |
| Impact for its field and year | 3 / 6 | Cited 6.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 2 / 4 | Cited 36 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Siow‐Wee Chang: h-index 18 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | University of Malaya: institution h-index 615 (OpenAlex) |
| Multicenter collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 34678481) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 39 / 100 | — |
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