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By Julio Saez-Rodriguez, Miguel P. Rocha, Florentino Fdez-Riverola, Juan F. De Paz Santana

Biological and biomedical learn are more and more pushed by way of experimental ideas that problem our skill to examine, technique and extract significant wisdom from the underlying facts. The notable features of subsequent new release sequencing applied sciences, including novel and ever evolving exact forms of omics facts applied sciences, have positioned an more and more advanced set of demanding situations for the turning out to be fields of Bioinformatics and Computational Biology. The research of the datasets produced and their integration demand new algorithms and methods from fields comparable to Databases, information, facts Mining, computing device studying, Optimization, computing device technology and synthetic Intelligence. essentially, Biology is a growing number of a technology of knowledge requiring instruments from the computational sciences. within the previous couple of years, we've seen the surge of a brand new iteration of interdisciplinary scientists that experience a powerful historical past within the organic and computational sciences. during this context, the interplay of researchers from assorted medical fields is, greater than ever, of finest significance boosting the study efforts within the box and contributing to the schooling of a brand new new release of Bioinformatics scientists. PACBB‘14 contributes to this attempt selling this fruitful interplay. PACBB'14 technical software integrated 34 papers spanning many various sub-fields in Bioinformatics and Computational Biology. consequently, the convention promotes the interplay of scientists from different learn teams and with a unique history resembling desktop scientists, mathematicians or biologists.

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Extra info for 8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014)

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M. ElGokhy, T. Shibuya, and A. Shoukry 1. The local sequence structure features described in [9] correspond to the number of contiguous nucleotide triplets. These 32 features have been defined in our method as the frequency of each sequence structure triplet. 2. The minimum free energy (MFE) of the secondary structure has been predicted using the RNA Vienna package [14]. Five normalized features of MFE have been considered. MFE adjusted by the hairpin length, MFE adjusted by the stem length, MFE corrected for GC-content, MFE adjusted by the hairpin length and corrected for GC-content and MFE adjusted by the stem length and corrected for GC-content.

The main techniques are represented in the squares. This sequence of steps is a methodology that is explained in the following section, also showing examples of the results obtained. 1 P. Chamoso et al. Phases The methodology used to obtain o the functionality of the platform may be divided iinto two phases. Firstly, a phasee called "digitization of the retina", in which the differrent parts of the eye image are identified. i Here a data structure is created, which makees it possible to represent and prrocess the retina without requiring the original image.

Yang, J. ) VDMB 2006. LNCS (LNBI), vol. 4316, pp. 131–145. Springer, Heidelberg (2006) 11. : Micropred: effective classification of pre-mirnas for human mirna gene prediction. Bioinformatics 25, 989–995 (2009) Improving miRNA Classification Using an Exhaustive Set of Features 39 12. : Yet another svm for mirna recognition: yasmir. Technical report, Citeseer (2010) 13. : Prediction of viral microrna precursors based on human microrna precursor sequence and structural features. Virology Journal 6 (2009) 14.

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