By Sérgio Campos
ISBN-10: 331912417X
ISBN-13: 9783319124179
ISBN-10: 3319124188
ISBN-13: 9783319124186
This ebook constitutes the refereed lawsuits of the ninth Brazilian Symposium on Bioinformatics, BSB 2014, held in Belo Horizonte, Brazil, in October 2014. The 18 revised complete papers offered have been conscientiously reviewed and chosen from 32 submissions. The papers disguise all elements of bioinformatics and computational biology.
Read or Download Advances in Bioinformatics and Computational Biology: 9th Brazilian Symposium on Bioinformatics, BSB 2014, Belo Horizonte, Brazil, October 28-30, 2014, Proceedings PDF
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Extra info for Advances in Bioinformatics and Computational Biology: 9th Brazilian Symposium on Bioinformatics, BSB 2014, Belo Horizonte, Brazil, October 28-30, 2014, Proceedings
Example text
Faria-Campos et al. Fig. 1. NMO Interface where the already executed and available activities are shown in different colors have been specified by a specialist in the disease, and the workflow development has been done by a informatics student working with the specialist. Tipically development takes a few hours spread over a number of sessions which interactively refine the workflow until the system is considered finished. All systems have been tested by doctors which verified that the system can be used for real patient consultation.
This way, the objective of the experiments conducted in this work is to evaluate the impact of the sequence length variation on the classifiers performance. 1 Computational Experiments Classifiers and Experimental Setup SVM (Support Vector Machine) and k-NN (k-Nearest Neighbours) classifiers, usually adopted in data mining works, were chosen to evaluate the impact of the sequence length variation on the performance of predictive models. Experiments were conducted using the caret package (short for classification and regression training) in R [15], which is a programming language and an environment widely used in statistical and graphics computation for data analysis.
On the other hand, the other eager learner, ANN, presents competitive results. 9097). Table 5. The comparison performance of classifiers in accordance to the ACC and Kappa measures. The highlighted cells show the best results. 737 Random Forest Classifier Evaluation In Figure 2 we show the importance of each of the 6 variables used by RF. The size of the sequence was selected as the most important attribute, maybe due to the fact that the coding regions are in most cases higher than non-coding. Among the GC content measures applied, the concentration of GC in second position of codons showed a very significant importance as compared to the others.
Advances in Bioinformatics and Computational Biology: 9th Brazilian Symposium on Bioinformatics, BSB 2014, Belo Horizonte, Brazil, October 28-30, 2014, Proceedings by Sérgio Campos
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