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Literature DB >> 16761367

Machine learning in bioinformatics.

Pedro Larrañaga¹, Borja Calvo, Roberto Santana, Concha Bielza, Josu Galdiano, Iñaki Inza, José A Lozano, Rubén Armañanzas, Guzmán Santafé, Aritz Pérez, Victor Robles.

Abstract

This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochastic heuristics for optimization. Applications in genomics, proteomics, systems biology, evolution and text mining are also shown.

Mesh：

Year: 2006 PMID： 16761367 DOI： 10.1093/bib/bbk007

Source DB: PubMed Journal: Brief Bioinform ISSN： 1467-5463 Impact factor: 11.622

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Cited

133 in total

1. KID--an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information of enzymes.

Authors: Stephanie Heinen; Bernhard Thielen; Dietmar Schomburg
Journal: BMC Bioinformatics Date: 2010-07-13 Impact factor: 3.169

Review 2. Computational approaches to study the effects of small genomic variations.

Authors: Kamil Khafizov; Maxim V Ivanov; Olga V Glazova; Sergei P Kovalenko
Journal: J Mol Model Date: 2015-09-08 Impact factor: 1.810

3. RNA secondary structure mediates alternative 3'ss selection in Saccharomyces cerevisiae.

Authors: Mireya Plass; Carles Codony-Servat; Pedro Gabriel Ferreira; Josep Vilardell; Eduardo Eyras
Journal: RNA Date: 2012-04-26 Impact factor: 4.942

4. Data mining validation of fluconazole breakpoints established by the European Committee on Antimicrobial Susceptibility Testing.

Authors: Isabel Cuesta; Concha Bielza; Pedro Larrañaga; Manuel Cuenca-Estrella; Fernando Laguna; Dolors Rodriguez-Pardo; Benito Almirante; Albert Pahissa; Juan L Rodríguez-Tudela
Journal: Antimicrob Agents Chemother Date: 2009-05-11 Impact factor: 5.191

5. The evolution of biology. A shift towards the engineering of prediction-generating tools and away from traditional research practice.

Authors: Lawrence Kelley; Michael Scott
Journal: EMBO Rep Date: 2008-11-14 Impact factor: 8.807

Machine learning in bioinformatics.

1. KID--an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information of enzymes.

Review 2. Computational approaches to study the effects of small genomic variations.

3. RNA secondary structure mediates alternative 3'ss selection in Saccharomyces cerevisiae.

4. Data mining validation of fluconazole breakpoints established by the European Committee on Antimicrobial Susceptibility Testing.

5. The evolution of biology. A shift towards the engineering of prediction-generating tools and away from traditional research practice.

6. Analyse multiple disease subtypes and build associated gene networks using genome-wide expression profiles.

7. Identification of non-coding RNAs with a new composite feature in the Hybrid Random Forest Ensemble algorithm.

Review 8. Towards the automatic classification of neurons.

9. DNA-binding residues and binding mode prediction with binding-mechanism concerned models.

10. DOTcvpSB, a software toolbox for dynamic optimization in systems biology.