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Items: 9

1.

LRH-1 agonism favours an immune-islet dialogue which protects against diabetes mellitus.

Cobo-Vuilleumier N, Lorenzo PI, Rodríguez NG, Herrera Gómez IG, Fuente-Martin E, López-Noriega L, Mellado-Gil JM, Romero-Zerbo SY, Baquié M, Lachaud CC, Stifter K, Perdomo G, Bugliani M, De Tata V, Bosco D, Parnaud G, Pozo D, Hmadcha A, Florido JP, Toscano MG, de Haan P, Schoonjans K, Sánchez Palazón L, Marchetti P, Schirmbeck R, Martín-Montalvo A, Meda P, Soria B, Bermúdez-Silva FJ, St-Onge L, Gauthier BR.

Nat Commun. 2018 Apr 16;9(1):1488. doi: 10.1038/s41467-018-03943-0.

2.

Evolution of the Quorum network and the mobilome (plasmids and bacteriophages) in clinical strains of Acinetobacter baumannii during a decade.

López M, Rueda A, Florido JP, Blasco L, Fernández-García L, Trastoy R, Fernández-Cuenca F, Martínez-Martínez L, Vila J, Pascual A, Bou G, Tomas M.

Sci Rep. 2018 Feb 6;8(1):2523. doi: 10.1038/s41598-018-20847-7.

3.

Genomic Evolution of Two Acinetobacter baumannii Clinical Strains from ST-2 Clones Isolated in 2000 and 2010 (ST-2_clon_2000 and ST-2_clon_2010).

López M, Rueda A, Florido JP, Blasco L, Gato E, Fernández-García L, Martínez-Martínez L, Fernández-Cuenca F, Pachón J, Cisneros JM, Garnacho-Montero J, Vila J, Rodríguez-Baño J, Pascual A, Bou G, Tomás M.

Genome Announc. 2016 Oct 20;4(5). pii: e01182-16. doi: 10.1128/genomeA.01182-16.

4.

267 Spanish Exomes Reveal Population-Specific Differences in Disease-Related Genetic Variation.

Dopazo J, Amadoz A, Bleda M, Garcia-Alonso L, Alemán A, García-García F, Rodriguez JA, Daub JT, Muntané G, Rueda A, Vela-Boza A, López-Domingo FJ, Florido JP, Arce P, Ruiz-Ferrer M, Méndez-Vidal C, Arnold TE, Spleiss O, Alvarez-Tejado M, Navarro A, Bhattacharya SS, Borrego S, Santoyo-López J, Antiñolo G.

Mol Biol Evol. 2016 May;33(5):1205-18. doi: 10.1093/molbev/msw005. Epub 2016 Jan 13.

5.

ngsCAT: a tool to assess the efficiency of targeted enrichment sequencing.

López-Domingo FJ, Florido JP, Rueda A, Dopazo J, Santoyo-Lopez J.

Bioinformatics. 2014 Jun 15;30(12):1767-8. doi: 10.1093/bioinformatics/btu108. Epub 2014 Feb 26.

PMID:
24578402
6.

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

Ortuño FM, Valenzuela O, Rojas F, Pomares H, Florido JP, Urquiza JM, Rojas I.

Bioinformatics. 2013 Sep 1;29(17):2112-21. doi: 10.1093/bioinformatics/btt360. Epub 2013 Jun 21.

PMID:
23793754
7.

Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques.

Ortuño FM, Valenzuela O, Pomares H, Rojas F, Florido JP, Urquiza JM, Rojas I.

Nucleic Acids Res. 2013 Jan 7;41(1):e26. doi: 10.1093/nar/gks919. Epub 2012 Oct 11.

8.

Using machine learning techniques and genomic/proteomic information from known databases for defining relevant features for PPI classification.

Urquiza JM, Rojas I, Pomares H, Herrera J, Florido JP, Valenzuela O, Cepero M.

Comput Biol Med. 2012 Jun;42(6):639-50. doi: 10.1016/j.compbiomed.2012.01.010. Epub 2012 May 9.

PMID:
22575173
9.

Generating balanced learning and test sets for function approximation problems.

Florido JP, Pomares H, Rojas I.

Int J Neural Syst. 2011 Jun;21(3):247-63. doi: 10.1142/S0129065711002791.

PMID:
21656926

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