International journal of data mining and bioinformatics
Jan 1, 2015
The scarcity of large labelled datasets comprising clinical text that can be exploited within the paradigm of supervised machine learning creates barriers for the secondary use of data from electronic health records. It is therefore important to deve...
International journal of data mining and bioinformatics
Jan 1, 2015
In silico prediction of novel miRNAs from genomic sequences remains a challenging problem. This study presents a genome-wide miRNA discovery software package called GenoScan and evaluates two hairpin classification methods. These methods, one ensembl...
International journal of data mining and bioinformatics
Jan 1, 2015
Prediction of different classes within the human leukocyte antigen (HLA) gene family can provide insight into the human immune system and its response to viral pathogens. Therefore, it is desirable to develop an efficient and easily interpretable met...
International journal of data mining and bioinformatics
Jan 1, 2015
Analysing and classifying sequences based on similarities and differences is a mathematical problem of escalating relevance and importance in many scientific disciplines. One of the primary challenges in applying machine learning algorithms to sequen...
The objective of this study is to build a fuzzy linguistic prediction model (FLPM) for analyzing the actuation duration of acute hyperglycemia to sinoatrial node field potential. The field potential was recorded using microelectrode arrays (MEA). The...
Applications of neural machine interfaces have received increased attention during the last decades. It is crucial to realize the continuous control of prosthetic devices based on biological signals. In order to deal with the highly nonlinear relatio...
Multi-label classification is useful in many bioinformatics tasks such as gene function prediction and protein site localization. This paper presents an improved neural network algorithm, Max Label Distance Back Propagation Algorithm for Multi-Label ...
Microarray data has small samples and high dimension, and it contains a significant amount of irrelevant and redundant genes. This paper proposes a hybrid ensemble method based on double disturbance to improve classification performance. Firstly, ori...
Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approac...
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