Multi-label hierarchical classification of protein functions with artificial immune systems

Alves, Roberto T. and Delgado, Myriam and Freitas, Alex A. (2008) Multi-label hierarchical classification of protein functions with artificial immune systems. In: Advances in Bioinformatics and Computational Biology (Proc. 2008 Brazilian Symposium in Bioinformatics (BSB-2008)), Lecture Notes in Bioinformatics 5167, Aug 28-30, 2008, Santo Andre, Brazil. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not available from this repository. (Contact us about this Publication)
Official URL


This work proposes two versions of an Artificial Immune System (AIS) - a relatively recent computational intelligence paradigm - for predicting protein functions described in the Gene Ontology (GO). The GO has functional classes (GO terms) specified in the form of a directed acyclic graph, which leads to a very challenging multi-label hierarchical classification problem where a protein can be assigned multiple classes (functions, GO terms) across several levels of the GO's term hierarchy. Hence, the proposed approach, called MHC-AIS (Multi-label Hierarchical Classification with an Artificial Immune System), is a sophisticated classification algorithm tailored to both multi-label and hierarchical classification. The first version of the MHC-AIS builds a global classifier to predict all classes in the application domain, whilst the second version builds a local classifier to predict each class. In both versions of the MHC-AIS the classifier is expressed as a set of IF-THEN classification rules, which have the advantage of representing comprehensible knowledge to biologist users. The two MHC-AIS versions are evaluated on a dataset of DNA-binding and ATPase proteins.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: classification, data mining, artificial immune systems
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 29 Mar 2010 12:12
Last Modified: 14 Jul 2014 12:38
Resource URI: (The current URI for this page, for reference purposes)
  • Depositors only (login required):