Journal Article DZNE-2024-01015

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AAontology: An Ontology of Amino Acid Scales for Interpretable Machine Learning

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2024
Elsevier Amsterdam [u.a.]

Journal of molecular biology 436(19), 168717 () [10.1016/j.jmb.2024.168717]

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Abstract: Amino acid scales are crucial for protein prediction tasks, many of them being curated in the AAindex database. Despite various clustering attempts to organize them and to better understand their relationships, these approaches lack the fine-grained classification necessary for satisfactory interpretability in many protein prediction problems. To address this issue, we developed AAontology-a two-level classification for 586 amino acid scales (mainly from AAindex) together with an in-depth analysis of their relations-using bag-of-word-based classification, clustering, and manual refinement over multiple iterations. AAontology organizes physicochemical scales into 8 categories and 67 subcategories, enhancing the interpretability of scale-based machine learning methods in protein bioinformatics. Thereby it enables researchers to gain a deeper biological insight. We anticipate that AAontology will be a building block to link amino acid properties with protein function and dysfunctions as well as aid informed decision-making in mutation analysis or protein drug design.

Keyword(s): Machine Learning (MeSH) ; Amino Acids: chemistry (MeSH) ; Computational Biology: methods (MeSH) ; Proteins: chemistry (MeSH) ; Proteins: metabolism (MeSH) ; Databases, Protein (MeSH) ; Cluster Analysis (MeSH)

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Contributing Institute(s):
  1. Molecular Neurodegeneration (AG Haass)
  2. Biochemistry of γ-Secretase (AG Steiner)
Research Program(s):
  1. 352 - Disease Mechanisms (POF4-352) (POF4-352)

Appears in the scientific report 2024
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Medline ; Creative Commons Attribution CC BY 4.0 ; OpenAccess ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Document types > Articles > Journal Article
Institute Collections > M DZNE > M DZNE-AG Steiner
Institute Collections > M DZNE > M DZNE-AG Haass
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Software: AAanalysis, v1.0.0
Zenodo () [10.5281/ZENODO.15320204] BibTeX | EndNote: XML, Text | RIS


 Record created 2024-08-07, last modified 2025-07-20