title: Towards a piRNA prediction using multiple kernel fusion and support vector machine.
abstract: BACKGROUND
  Piwi-interacting RNA (piRNA) is the most recently discovered and the least investigated class of Argonaute/Piwi protein-interacting small non-coding RNAs. The piRNAs are mostly known to be involved in protecting the genome from invasive transposable elements. But recent discoveries suggest their involvement in the pathophysiology of diseases, such as cancer. Their identification is therefore an important task, and computational methods are needed. However, the lack of conserved piRNA sequences and structural elements makes this identification challenging and difficult.
  
  
  RESULTS
  In the present study, we propose a new modular and extensible machine learning method based on multiple kernels and a support vector machine (SVM) classifier for piRNA identification. Very few piRNA features are known to date. The use of a multiple kernels approach allows editing, adding or removing piRNA features that can be heterogeneous in a modular manner according to their relevance in a given species. Our algorithm is based on a combination of the previously identified features [sequence features (k-mer motifs and a uridine at the first position) and piRNAs cluster feature] and a new telomere/centromere vicinity feature. These features are heterogeneous, and the kernels allow to unify their representation. The proposed algorithm, named piRPred, gives promising results on Drosophila and Human data and outscores previously published piRNA identification algorithms.
  
  
  METHODS
  piRPred is freely available to non-commercial users on our Web server EvryRNA http://EvryRNA.ibisc.univ-evry.fr.
authors.affiliation: IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de l'Internationale, 91002 Evry Cedex, France IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de l'Internationale, 91002 Evry Cedex, France.
authors.forename: Jocelyn
authors.initials: J
authors.lastname: Brayet
authors.affiliation: IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de l'Internationale, 91002 Evry Cedex, France.
authors.forename: Farida
authors.initials: F
authors.lastname: Zehraoui
authors.affiliation: IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de l'Internationale, 91002 Evry Cedex, France.
authors.forename: Laurence
authors.initials: L
authors.lastname: Jeanson-Leh
authors.affiliation: IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de l'Internationale, 91002 Evry Cedex, France.
authors.forename: David
authors.initials: D
authors.lastname: Israeli
authors.affiliation: IBISC EA 4526, UEVE/Genopole, IBGBI, 23 bv. de France, 91000 Evry, France and Genethon, 1, bis rue de l'Internationale, 91002 Evry Cedex, France.
authors.forename: Fariza
authors.initials: F
authors.lastname: Tahi
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D004330:Drosophila / Q000235:genetics; D006801:Humans; D034741:RNA, Small Interfering / Q000737:chemistry*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D060388:Support Vector Machine
chemical_list: D034741:RNA, Small Interfering