Predicting post-synaptic activity in proteins with data mining
Abstract
Summary: The bioinformatics problem being addressed in this paper is to predict whether or not a protein has post-synaptic activity. This problem is of great intrinsic interest because proteins with post-synaptic activities are connected with functioning of the nervous system. Indeed, many proteins having post-synaptic activity have been functionally characterized by biochemical, immunological and proteomic exercises. They represent a wide variety of proteins with functions in extracellular signal reception and propagation through intracellular apparatuses, cell adhesion molecules and scaffolding proteins that link them in a web. The challenge is to automatically discover features of the primary sequences of proteins that typically occur in proteins with post-synaptic activity but rarely (or never) occur in proteins without post-synaptic activity, and vice-versa. In this context, we used data mining to automatically discover classification rules that predict whether or not a protein has post-synaptic activity. The discovered rules were analysed with respect to their predictive accuracy (generalization ability) and with respect to their interestingness to biologists (in the sense of representing novel, unexpected knowledge). Contact: A.A.Freitas@kent.ac.uk
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“Even though this sort of exception analysis is hardly performed, it can be more informative than the direct explanation, and it can also provide clues about the application domain [37, 85].”
Background
- Authors
- Pappa, G. L., Baines, A. J., & Freitas, A. A.
- Affiliations
- University of Kent (GB)
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-09-01
- Volume
- 21
- Issue
- suppl_2
- Pages
- ii19-ii25
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2123497007
- Cited by
- 20
- References
- 17
- Citations by year
- 2023: 1 · 2020: 2 · 2019: 1 · 2018: 1 · 2017: 1 · 2014: 1 · 2013: 1 · 2012: 1
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Kent Academic Repository (University of Kent) (submittedVersion)
- Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- postsynaptic proteins, protein function prediction, classification rules, adhesion molecules, scaffold proteins, rule interestingness
- MeSH terms
- Database Management Systems, Nerve Endings, Nerve Tissue Proteins, Structure-Activity Relationship, Synapses, Information Storage and Retrieval, Neurotransmitter Agents, Excitatory Postsynaptic Potentials, Sequence Analysis, Protein, Databases, Protein
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