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Heath AP, Ferretti V, Agrawal S, et al. The NCI Genomic Data Commons. Nature Genetics. 2021. doi:10.1038/s41588-021-00791-5.
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Jimenez RC, Salazar GA, Gel B, Dopazo J, Mulder N, Corpas M. myKaryoView: a light-weight client for visualization of genomic data. PLoS One. 2011;6(10):e26345. doi:10.1371/journal.pone.0026345.
Ibáñez M, Carbonell-Caballero J, García-Alonso L, et al. The Mutational Landscape of Acute Promyelocytic Leukemia Reveals an Interacting Network of Co-Occurrences and Recurrent Mutations. PLoS One. 2016;11(2):e0148346. doi:10.1371/journal.pone.0148346.
Jones AR, Lister AL, Hermida L, et al. Modeling and managing experimental data using FuGE. OMICS. 2009;13:239-51.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.
Rizza S, Conesa A, Juarez J, et al. Microarray analysis of Etrog citron (Citrus medica L.) reveals changes in chloroplast, cell wall, peroxidase and symporter activities in response to viroid infection. Molecular plant pathology. 2012. doi:10.1111/j.1364-3703.2012.00794.x.
Mateos A, Herrero J, Tamames J, Dopazo J. Methods of Microarray Data Analysis IISupervised Neural Networks for Clustering Conditions in DNA Array Data After Reducing Noise by Clustering Gene Expression Profiles. (Lin SM, Johnson KF, eds.). Boston: Kluwer Academic Publishers; 2002:91 - 103. doi:10.1007/b11298210.1007/0-306-47598-7_7.
Carbonell J, Alloza E, Arce P, et al. A map of human microRNA variation uncovers unexpectedly high levels of variability. Genome medicine. 2012;4:62. doi:10.1186/gm363.
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Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0–it’s better than sharing your toothbrush!. Brief Bioinform. 2008;9:220-31. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18238804.
Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0--it's better than sharing your toothbrush!. Brief Bioinform. 2008;9(3):220-31. doi:10.1093/bib/bbn003.
Jaime MDLA, Lopez-Llorca LVicente, Conesa A, et al. Identification of yeast genes that confer resistance to chitosan oligosaccharide (COS) using chemogenomics. BMC genomics. 2012;13:267. doi:10.1186/1471-2164-13-267.
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Roca-Ayats N, Balcells S, Garcia-Giralt N, et al. GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates. N Engl J Med. 2017;376(18):1794-1795. doi:10.1056/NEJMc1612804.PDF icon Roca-Ayats-2017NEJM - GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates.pdf (214.03 KB)
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Shi W, Bessarabova M, Dosymbekov D, et al. Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes. Pharmacogenomics J. 2010;10(4):310-23. doi:10.1038/tpj.2010.35.
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Bonifaci N, Górski B, Masojć B, et al. Exploring the link between germline and somatic genetic alterations in breast carcinogenesis. PLoS One. 2010;5(11):e14078. doi:10.1371/journal.pone.0014078.
Tort F, García-Silva MTeresa, Ferrer-Cortès X, et al. Exome sequencing identifies a new mutation in SERAC1 in a patient with 3-methylglutaconic aciduria. Mol Genet Metab. 2013;110(1-2):73-7. doi:10.1016/j.ymgme.2013.04.021.
Puerto-Camacho P, Diaz-Martin J, Olmedo-Pelayo J, et al. Endoglin and MMP14 Contribute to Ewing Sarcoma Spreading by Modulation of Cell-Matrix Interactions. Int J Mol Sci. 2022;23(15). doi:10.3390/ijms23158657.
Salgado D, Armean IM, Baudis M, et al. The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research. F1000Res. 2020;9. doi:10.12688/f1000research.24887.1.
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Niarakis A, Ostaszewski M, Mazein A, et al. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. Front Immunol. 2024;14:1282859. doi:10.3389/fimmu.2023.1282859.
Niarakis A, Ostaszewski M, Mazein A, et al. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. Front Immunol. 2024;14:1282859. doi:10.3389/fimmu.2023.1282859.