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Al-Shahrour F, Carbonell J, Minguez P, et al. Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments. Nucleic Acids Res. 2008;36:W341-6. Available at: http://nar.oxfordjournals.org/content/36/suppl_2/W341.long.
Al-Shahrour F, Minguez P, Tarraga J, et al. BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Res. 2006;34:W472-6. Available at: http://nar.oxfordjournals.org/content/34/suppl_2/W472.long.
Al-Shahrour F, Minguez P, Tarraga J, et al. BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Res. 2006;34:W472-6. Available at: http://nar.oxfordjournals.org/content/34/suppl_2/W472.long.
Al-Shahrour F, Minguez P, Vaquerizas JM, Conde L, Dopazo J. BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. Nucleic Acids Res. 2005;33:W460-4. Available at: http://nar.oxfordjournals.org/content/33/suppl_2/W460.long.
Alonso R, Salavert F, Garcia-Garcia F, et al. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic acids research. 2015;43:W117-W121. doi:10.1093/nar/gkv384.
Alonso R, Salavert F, Garcia-Garcia F, et al. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic acids research. 2015;43:W117-W121. doi:10.1093/nar/gkv384.
Alonso R, Salavert F, Garcia-Garcia F, et al. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic acids research. 2015;43:W117-W121. doi:10.1093/nar/gkv384.
Götz S, Arnold R, Sebastián-Leon P, et al. B2G-FAR, a species centered GO annotation repository. Bioinformatics (Oxford, England). 2011;27:919-924.
A
Gonzalez S, Clavijo B, Rivarola M, et al. ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data. BMC Bioinformatics. 2017;18(1):121. doi:10.1186/s12859-017-1494-2.
Ruiz-Llorente S, Montero-Conde C, Milne RL, et al. Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma. Cancer Res. 2007;67:9561-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17909067.
Ruiz-Llorente S, Montero-Conde C, Milne RL, et al. Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma. Cancer Res. 2007;67:9561-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17909067.
Ruiz-Llorente S, Montero-Conde C, Milne RL, et al. Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma. Cancer Res. 2007;67:9561-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17909067.
Ruiz-Llorente S, Montero-Conde C, Milne RL, et al. Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma. Cancer Res. 2007;67:9561-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17909067.
Lupo V, Garcia-Garcia F, Sancho P, et al. Assessment of Targeted Next-Generation Sequencing as a Tool for the Diagnosis of Charcot-Marie-Tooth Disease and Hereditary Motor Neuropathy. The Journal of molecular diagnostics : JMD. 2016. doi:10.1016/j.jmoldx.2015.10.005.
Capriotti E, Marti-Renom MA. Assessment of protein structure predictions. In: Computational Structural Biology. Computational Structural Biology. New Jersey, USA: World Scientific Publishing Company; 2008. Available at: http://www.amazon.com/dp/9812778772/.
Loucera C, Perez-Florido J, Casimiro-Soriguer CS, et al. Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival. Viruses. 2022;14(9). doi:10.3390/v14091893.
Loucera C, Perez-Florido J, Casimiro-Soriguer CS, et al. Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival. Viruses. 2022;14(9). doi:10.3390/v14091893.
Loucera C, Perez-Florido J, Casimiro-Soriguer CS, et al. Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival. Viruses. 2022;14(9). doi:10.3390/v14091893.
Hernansaiz-Ballesteros RD, Salavert F, Sebastián-Leon P, Alemán A, Medina I, Dopazo J. Assessing the impact of mutations found in next generation sequencing data over human signaling pathways. Nucleic acids research. 2015;43:W270-W275. doi:10.1093/nar/gkv349.
Minguez P, Dopazo J. Assessing the biological significance of gene expression signatures and co-expression modules by studying their network properties. PloS one. 2011;6:e17474. doi:doi:10.1371/journal.pone.0017474.
Munro SA, Lund SP, P Pine S, et al. Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. Nature communications. 2014;5:5125. doi:10.1038/ncomms6125.
Munro SA, Lund SP, P Pine S, et al. Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. Nature communications. 2014;5:5125. doi:10.1038/ncomms6125.
Munro SA, Lund SP, P Pine S, et al. Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. Nature communications. 2014;5:5125. doi:10.1038/ncomms6125.
Ariño J, Casamayor A, Pérez JPerez, et al. Assessing Differential Expression Measurements by Highly Parallel Pyrosequencing and DNA Microarrays: A Comparative Study. Omics : a journal of integrative biology. 2013. doi:10.1089/omi.2011.0065.
Dopazo J, Mendoza A, Herrero J, et al. Annotated draft genomic sequence from a Streptococcus pneumoniae type 19F clinical isolate. Microb Drug Resist. 2001;7:99-125. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11442348.