%0 Journal Article %J BMC Bioinformatics %D 2021 %T A comprehensive database for integrated analysis of omics data in autoimmune diseases. %A Martorell-Marugán, Jordi %A López-Domínguez, Raúl %A García-Moreno, Adrián %A Toro-Domínguez, Daniel %A Villatoro-García, Juan Antonio %A Barturen, Guillermo %A Martín-Gómez, Adoración %A Troule, Kevin %A Gómez-López, Gonzalo %A Al-Shahrour, Fátima %A González-Rumayor, Víctor %A Peña-Chilet, Maria %A Dopazo, Joaquin %A Saez-Rodriguez, Julio %A Alarcón-Riquelme, Marta E %A Carmona-Sáez, Pedro %K Autoimmune Diseases %K Computational Biology %K Databases, Factual %K Humans %X

BACKGROUND: Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field.

RESULTS: Here, we present Autoimmune Diseases Explorer ( https://adex.genyo.es ), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis.

CONCLUSIONS: This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

%B BMC Bioinformatics %V 22 %P 343 %8 2021 Jun 24 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/34167460?dopt=Abstract %R 10.1186/s12859-021-04268-4 %0 Journal Article %J Brief Bioinform %D 2019 %T Precision medicine needs pioneering clinical bioinformaticians. %A Gómez-López, Gonzalo %A Dopazo, Joaquin %A Cigudosa, Juan C %A Valencia, Alfonso %A Al-Shahrour, Fátima %K Cohort Studies %K Computational Biology %K Humans %K Precision Medicine %X

Success in precision medicine depends on accessing high-quality genetic and molecular data from large, well-annotated patient cohorts that couple biological samples to comprehensive clinical data, which in conjunction can lead to effective therapies. From such a scenario emerges the need for a new professional profile, an expert bioinformatician with training in clinical areas who can make sense of multi-omics data to improve therapeutic interventions in patients, and the design of optimized basket trials. In this review, we first describe the main policies and international initiatives that focus on precision medicine. Secondly, we review the currently ongoing clinical trials in precision medicine, introducing the concept of 'precision bioinformatics', and we describe current pioneering bioinformatics efforts aimed at implementing tools and computational infrastructures for precision medicine in health institutions around the world. Thirdly, we discuss the challenges related to the clinical training of bioinformaticians, and the urgent need for computational specialists capable of assimilating medical terminologies and protocols to address real clinical questions. We also propose some skills required to carry out common tasks in clinical bioinformatics and some tips for emergent groups. Finally, we explore the future perspectives and the challenges faced by precision medicine bioinformatics.

%B Brief Bioinform %V 20 %P 752-766 %8 2019 05 21 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/29077790?dopt=Abstract %R 10.1093/bib/bbx144 %0 Journal Article %J Leuk Lymphoma %D 2009 %T Functional signatures identified in B-cell non-Hodgkin lymphoma profiles. %A Aggarwal, Mohit %A Sánchez-Beato, Margarita %A Gómez-López, Gonzalo %A Al-Shahrour, Fátima %A Martínez, Nerea %A Rodríguez, Antonia %A Ruiz-Ballesteros, Elena %A Camacho, Francisca I %A Pérez-Rosado, Alberto %A de la Cueva, Paloma %A Artiga, María J %A Pisano, David G %A Kimby, Eva %A Dopazo, Joaquin %A Villuendas, Raquel %A Piris, Miguel A %K Adult %K Cluster Analysis %K Gene Expression Profiling %K Gene Expression Regulation, Leukemic %K Genetic Heterogeneity %K Humans %K Lymphoma, B-Cell %K Neoplasm Proteins %K Oligonucleotide Array Sequence Analysis %K RNA, Messenger %K RNA, Neoplasm %K Transcription, Genetic %X

Gene-expression profiling in B-cell lymphomas has provided crucial data on specific lymphoma types, which can contribute to the identification of essential lymphoma survival genes and pathways. In this study, the gene-expression profiling data of all major B-cell lymphoma types were analyzed by unsupervised clustering. The transcriptome classification so obtained, was explored using gene set enrichment analysis generating a heatmap for B-cell lymphoma that identifies common lymphoma survival mechanisms and potential therapeutic targets, recognizing sets of coregulated genes and functional pathways expressed in different lymphoma types. Some of the most relevant signatures (stroma, cell cycle, B-cell receptor (BCR)) are shared by multiple lymphoma types or subclasses. A specific attention was paid to the analysis of BCR and coregulated pathways, defining molecular heterogeneity within multiple B-cell lymphoma types.

%B Leuk Lymphoma %V 50 %P 1699-708 %8 2009 Oct %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/19863341?dopt=Abstract %R 10.1080/10428190903189035