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Xosé M Fernández

Bio: Xosé M Fernández is an academic researcher from Curie Institute. The author has contributed to research in topics: Ensembl & Genome browser. The author has an hindex of 5, co-authored 10 publications receiving 152 citations.

Papers
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Journal ArticleDOI
TL;DR: This issue contains three breakthrough articles: AntiBodies Chemically Defined curates antibody sequences and their cognate antigens; SCOP returns with a new schema and breaks away from a purely hierarchical structure; while the new Alliance of Genome Resources brings together a number of Model Organism databases to pool knowledge and tools.
Abstract: The 2020 Nucleic Acids Research Database Issue contains 148 papers spanning molecular biology. They include 59 papers reporting on new databases and 79 covering recent changes to resources previously published in the issue. A further ten papers are updates on databases most recently published elsewhere. This issue contains three breakthrough articles: AntiBodies Chemically Defined (ABCD) curates antibody sequences and their cognate antigens; SCOP returns with a new schema and breaks away from a purely hierarchical structure; while the new Alliance of Genome Resources brings together a number of Model Organism databases to pool knowledge and tools. Major returning nucleic acid databases include miRDB and miRTarBase. Databases for protein sequence analysis include CDD, DisProt and ELM, alongside no fewer than four newcomers covering proteins involved in liquid-liquid phase separation. In metabolism and signaling, Pathway Commons, Reactome and Metabolights all contribute papers. PATRIC and MicroScope update in microbial genomes while human and model organism genomics resources include Ensembl, Ensembl genomes and UCSC Genome Browser. Immune-related proteins are covered by updates from IPD-IMGT/HLA and AFND, as well as newcomers VDJbase and OGRDB. Drug design is catered for by updates from the IUPHAR/BPS Guide to Pharmacology and the Therapeutic Target Database. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been revised, updating 305 entries, adding 65 new resources and eliminating 125 discontinued URLs; so bringing the current total to 1637 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

67 citations

Journal ArticleDOI
TL;DR: The 2018 Nucleic Acids Research Database Issue contains 181 papers spanning molecular biology, with update papers from the IUPHAR/BPS Guide to Pharmacology and DrugBank and a number of proteomics databases including proteomicsDB are also covered.
Abstract: The 2018 Nucleic Acids Research Database Issue contains 181 papers spanning molecular biology. Among them, 82 are new and 84 are updates describing resources that appeared in the Issue previously. The remaining 15 cover databases most recently published elsewhere. Databases in the area of nucleic acids include 3DIV for visualisation of data on genome 3D structure and RNArchitecture, a hierarchical classification of RNA families. Protein databases include the established SMART, ELM and MEROPS while GPCRdb and the newcomer STCRDab cover families of biomedical interest. In the area of metabolism, HMDB and Reactome both report new features while PULDB appears in NAR for the first time. This issue also contains reports on genomics resources including Ensembl, the UCSC Genome Browser and ENCODE. Update papers from the IUPHAR/BPS Guide to Pharmacology and DrugBank are highlights of the drug and drug target section while a number of proteomics databases including proteomicsDB are also covered. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, reviewing 138 entries, adding 88 new resources and eliminating 47 discontinued URLs, bringing the current total to 1737 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

62 citations

Journal ArticleDOI
TL;DR: This Issue contains two Breakthrough articles, on the Virtual Metabolic Human database which links human and gut microbiota metabolism with diet and disease, and Vibrism DB, a database of mouse brain anatomy and gene (co-)expression with sophisticated visualization and session sharing.
Abstract: The 2019 Nucleic Acids Research (NAR) Database Issue contains 168 papers spanning molecular biology. Among them, 64 are new and another 92 are updates describing resources that appeared in the Issue previously. The remaining 12 are updates on databases most recently published elsewhere. This Issue contains two Breakthrough articles, on the Virtual Metabolic Human (VMH) database which links human and gut microbiota metabolism with diet and disease, and Vibrism DB, a database of mouse brain anatomy and gene (co-)expression with sophisticated visualization and session sharing. Major returning nucleic acid databases include RNAcentral, miRBase and LncRNA2Target. Protein sequence databases include UniProtKB, InterPro and Pfam, while wwPDB and RCSB cover protein structure. STRING and KEGG update in the section on metabolism and pathways. Microbial genomes are covered by IMG/M and resources for human and model organism genomics include Ensembl, UCSC Genome Browser, GENCODE and Flybase. Genomic variation and disease are well-covered by GWAS Catalog, PopHumanScan, OMIM and COSMIC, CADD being another major newcomer. Major new proteomics resources reporting here include iProX and jPOSTdb. The entire database issue is freely available online on the NAR website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, reviewing 506 entries, adding 66 new resources and eliminating 147 discontinued URLs, bringing the current total to 1613 databases. It is available at http://www.oxfordjournals.org/nar/database/c.

38 citations

Journal ArticleDOI
TL;DR: The NAR database issue as discussed by the authors contains 189 papers spanning a wide range of biological fields and investigation, including 89 papers reporting on new databases and 90 covering recent changes to resources previously published in the issue.
Abstract: The 2021 Nucleic Acids Research database Issue contains 189 papers spanning a wide range of biological fields and investigation. It includes 89 papers reporting on new databases and 90 covering recent changes to resources previously published in the Issue. A further ten are updates on databases most recently published elsewhere. Seven new databases focus on COVID-19 and SARS-CoV-2 and many others offer resources for studying the virus. Major returning nucleic acid databases include NONCODE, Rfam and RNAcentral. Protein family and domain databases include COG, Pfam, SMART and Panther. Protein structures are covered by RCSB PDB and dispersed proteins by PED and MobiDB. In metabolism and signalling, STRING, KEGG and WikiPathways are featured, along with returning KLIFS and new DKK and KinaseMD, all focused on kinases. IMG/M and IMG/VR update in the microbial and viral genome resources section, while human and model organism genomics resources include Flybase, Ensembl and UCSC Genome Browser. Cancer studies are covered by updates from canSAR and PINA, as well as newcomers CNCdatabase and Oncovar for cancer drivers. Plant comparative genomics is catered for by updates from Gramene and GreenPhylDB. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been substantially updated, revisiting nearly 1000 entries, adding 90 new resources and eliminating 86 obsolete databases, bringing the current total to 1641 databases. It is available at https://www.oxfordjournals.org/nar/database/c/.

30 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular-omics data from clinical data warehouses and biobanks.
Abstract: BACKGROUND Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. METHODS The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. RESULTS This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. CONCLUSIONS The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.

13 citations


Cited by
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Journal ArticleDOI
TL;DR: WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.
Abstract: WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output.

1,155 citations

01 Feb 2015
TL;DR: Current progress toward developing programmable nuclease–based therapies as well as future prospects and challenges are discussed.
Abstract: Recent advances in the development of genome editing technologies based on programmable nucleases have substantially improved our ability to make precise changes in the genomes of eukaryotic cells. Genome editing is already broadening our ability to elucidate the contribution of genetics to disease by facilitating the creation of more accurate cellular and animal models of pathological processes. A particularly tantalizing application of programmable nucleases is the potential to directly correct genetic mutations in affected tissues and cells to treat diseases that are refractory to traditional therapies. Here we discuss current progress toward developing programmable nuclease–based therapies as well as future prospects and challenges.

846 citations

Journal ArticleDOI
TL;DR: The submission process was completely overhauled to enable MetaboLights to deliver a far more user-friendly submission process and to facilitate the growing demand for reproducibility and integration with other ‘omics.
Abstract: MetaboLights is a database for metabolomics studies, their raw experimental data and associated metadata. The database is cross-species and cross-technique and it covers metabolite structures and their reference spectra as well as their biological roles and locations. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information. In this article, we describe the significant updates that we have made over the last two years to the resource to respond to the increasing amount and diversity of data being submitted by the metabolomics community. We refreshed the website and most importantly, our submission process was completely overhauled to enable us to deliver a far more user-friendly submission process and to facilitate the growing demand for reproducibility and integration with other 'omics. Metabolomics resources and data are available under the EMBL-EBI's Terms of Use via the web at https://www.ebi.ac.uk/metabolights and under Apache 2.0 at Github (https://github.com/EBI-Metabolights/).

426 citations

Journal ArticleDOI
TL;DR: AFND has become more popular in terms of clinical and scientific usage, with a recent increase in genotyping data as a necessary component of Short Population Report article submissions to another scientific journal, and a user-friendly desktop application for HLA and KIR genotype/population data submissions.
Abstract: The Allele Frequency Net Database (AFND, www.allelefrequencies.net) provides the scientific community with a freely available repository for the storage of frequency data (alleles, genes, haplotypes and genotypes) related to human leukocyte antigens (HLA), killer-cell immunoglobulin-like receptors (KIR), major histocompatibility complex Class I chain related genes (MIC) and a number of cytokine gene polymorphisms in worldwide populations. In the last five years, AFND has become more popular in terms of clinical and scientific usage, with a recent increase in genotyping data as a necessary component of Short Population Report article submissions to another scientific journal. In addition, we have developed a user-friendly desktop application for HLA and KIR genotype/population data submissions. We have also focused on classification of existing and new data into 'gold-silver-bronze' criteria, allowing users to filter and query depending on their needs. Moreover, we have also continued to expand other features, for example focussed on HLA associations with adverse drug reactions. At present, AFND contains >1600 populations from >10 million healthy individuals, making AFND a valuable resource for the analysis of some of the most polymorphic regions in the human genome.

350 citations

Journal ArticleDOI
TL;DR: The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community and encapsulating current knowledge of human metabolism within five interlinked resources.
Abstract: A multitude of factors contribute to complex diseases and can be measured with 'omics' methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, www.vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources 'Human metabolism', 'Gut microbiome', 'Disease', 'Nutrition', and 'ReconMaps'. The VMH captures 5180 unique metabolites, 17 730 unique reactions, 3695 human genes, 255 Mendelian diseases, 818 microbes, 632 685 microbial genes and 8790 food items. The VMH's unique features are (i) the hosting of the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; (ii) seven human metabolic maps for data visualization; (iii) a nutrition designer; (iv) a user-friendly webpage and application-programming interface to access its content; (v) user feedback option for community engagement and (vi) the connection of its entities to 57 other web resources. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

228 citations