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International Journal of Data Mining and Bioinformatics is a peer-reviewed journal published by Inderscience, covering Gene expression and cancer classification, Bioinformatics and Genomic Networks, Machine Learning in Bioinformatics.
| Publisher | Inderscience |
|---|---|
| Reference style | Author–year (Harvard/AGSM) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', International Journal of Data Mining and Bioinformatics, 12(3), pp. 45–58.
Formats any DOI in International Journal of Data Mining and Bioinformatics style. No sign-up. |
| Publishes research in | Gene expression and cancer classification Bioinformatics and Genomic Networks Machine Learning in Bioinformatics Genomics and Phylogenetic Studies Biomedical Text Mining and Ontologies |
| ISSN | 1748-5673 |
| Citation impact (2-yr) | 0.7 |
| h-index | 30 |
| i10-index | 144 |
| Total citations | 5,036 |
| Top institutions publishing here | Seoul National University |
| Journal website | www.inderscience.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
The identification of disease-related microRNAs is vital for understanding the pathogenesis of disease at the molecular level and may lead to the design of specific molecular tools for diagnosis, treatment and prevention. Experimental identification of disease-related microRNAs poses difficulties. Computational prediction of microRNA-disease associations is one of the complementary means. However, one major issue in…
We describe here a new mapping method able to find out connectivity traces among variables thanks to an artificial adaptive system, the Auto Contractive Map (AutoCM), able to define the strength of the associations of each variable with all the others in a dataset. After the training phase, the weights matrix of the AutoCM represents…
In this paper, the bat-inspired algorithm (BA) is tolerated to gene selection for cancer classification using microarray datasets. Microarray data consists of irrelevant, redundant, and noisy genes. Gene selection problem is tackled by determining the most informative genes taken from microarray data to accurately diagnose the cancer disease. Gene selection problem is widely solved by…
This study presents three feature selection methods for identifying the metabolite features in nuclear magnetic resonance spectra that contribute to the distinction of samples among varying nutritional conditions. Principal component analysis, Fisher discriminant analysis, and Partial Least Square Discriminant Analysis (PLS-DA) were used to calculate the importance of individual metabolite feature in spectra. Moreover, an…
MentalSquares (MSQs)--an equilibrium-based dimensional approach is presented for the classification and diagnostic analysis of psychological conditions with Bipolar Disorders (BPDs) as an example. While a Support Vector Machine (SVM) is defined in Hilbert space. A MSQ can be considered as a generic SVM for improved classification. Different from the traditional categorical model of BPDs, the…
