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A Hierarchical Multi-Label Classification Algorithm for Gene Function Prediction
- Source :
- Algorithms; Volume 10; Issue 4; Pages: 138, Algorithms, Vol 10, Iss 4, p 138 (2017)
- Publication Year :
- 2017
- Publisher :
- MDPI AG, 2017.
-
Abstract
- Gene function prediction is a complicated and challenging hierarchical multi-label classification (HMC) task, in which genes may have many functions at the same time and these functions are organized in a hierarchy. This paper proposed a novel HMC algorithm for solving this problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph (DAG) and is more difficult to tackle. In the proposed algorithm, the HMC task is firstly changed into a set of binary classification tasks. Then, two measures are implemented in the algorithm to enhance the HMC performance by considering the hierarchy structure during the learning procedures. Firstly, negative instances selecting policy associated with the SMOTE approach are proposed to alleviate the imbalanced data set problem. Secondly, a nodes interaction method is introduced to combine the results of binary classifiers. It can guarantee that the predictions are consistent with the hierarchy constraint. The experiments on eight benchmark yeast data sets annotated by the Gene Ontology show the promising performance of the proposed algorithm compared with other state-of-the-art algorithms.
- Subjects :
- 0301 basic medicine
lcsh:T55.4-60.8
Computer science
02 engineering and technology
lcsh:QA75.5-76.95
Theoretical Computer Science
Task (project management)
Set (abstract data type)
hierarchical multi-label classification
the Gene Ontology
gene function prediction
DAG
03 medical and health sciences
0202 electrical engineering, electronic engineering, information engineering
lcsh:Industrial engineering. Management engineering
Multi-label classification
Numerical Analysis
Hierarchy (mathematics)
Function (mathematics)
Directed acyclic graph
Computational Mathematics
ComputingMethodologies_PATTERNRECOGNITION
030104 developmental biology
Computational Theory and Mathematics
Binary classification
Benchmark (computing)
020201 artificial intelligence & image processing
lcsh:Electronic computers. Computer science
Algorithm
Subjects
Details
- ISSN :
- 19994893
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Algorithms
- Accession number :
- edsair.doi.dedup.....257b4ad475051ac50620cbcdd7b1460e
- Full Text :
- https://doi.org/10.3390/a10040138