6th International Conference on Practical Applications of by Sandrine Mouysset, Ronan Guivarch (auth.), Miguel P. Rocha,

By Sandrine Mouysset, Ronan Guivarch (auth.), Miguel P. Rocha, Nicholas Luscombe, Florentino Fdez-Riverola, Juan M. Corchado Rodríguez (eds.)

The progress within the Bioinformatics and Computational Biology fields during the last few years has been amazing and the craze is to extend its velocity. in reality, the necessity for computational suggestions which could successfully deal with the large quantities of information produced by means of the recent experimental ideas in Biology continues to be expanding pushed via new advances in subsequent iteration Sequencing, various kinds of the so referred to as omics information and picture acquisition, simply to identify a number of. The research of the datasets that produces and its integration demand new algorithms and techniques from fields akin to Databases, information, info Mining, computer studying, Optimization, desktop technology and synthetic Intelligence. inside this situation of accelerating information availability, platforms Biology has additionally been rising as a substitute to the reductionist view that ruled organic learn within the final many years. certainly, Biology is an increasing number of a technological know-how of knowledge requiring instruments from the computational sciences. within the previous couple of years, we've seen the surge of a brand new new release of interdisciplinary scientists that experience a robust history within the organic and computational sciences. during this context, the interplay of researchers from diversified clinical fields is, greater than ever, of most excellent value boosting the examine efforts within the box and contributing to the schooling of a brand new new release of Bioinformatics scientists. PACBB‘12 hopes to give a contribution to this attempt selling this fruitful interplay. PACBB'12 technical software incorporated 32 papers from a submission pool of sixty one papers spanning many alternative sub-fields in Bioinformatics and Computational Biology. as a result, the convention will surely have promoted the interplay of scientists from different examine teams and with a unique history (computer scientists, mathematicians, biologists). The clinical content material will surely be not easy and may advertise the development of the paintings that's being built through all of the participants.

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Machine learning techniques have been successfully applied on biological data and SVMs are known to be a powerful method to solve classification problems obtaining high performance values. Hence we proposed to classify RNA sequences, as binding or as not binding to CELF1 protein, using SVMs trained on CLIP-seq data. Two experiments are described to test the prediction ability of our model. The first experiment applies SVM and localSVM on a CLIP-seq dataset. Due to the unbalanced data the application of a balancing algorithm was necessary.

So far there is no other approach to detect specific RNA-protein binding in vivo. Machine learning techniques have been successfully applied on biological data and SVMs are known to be a powerful method to solve classification problems obtaining high performance values. Hence we proposed to classify RNA sequences, as binding or as not binding to CELF1 protein, using SVMs trained on CLIP-seq data. Two experiments are described to test the prediction ability of our model. The first experiment applies SVM and localSVM on a CLIP-seq dataset.

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