Computational Methods for the Analysis of Genomic Data and Biological Processes

• Autore: Gómez Vela Francisco A
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (222 p.)
• Soggetto topico: Biology, life sciences; Research & information: general
• Soggetto non controllato: binding sites; bioinformatics; bioinformatics analysis; CAMTA1; cancer; CBF; chilling stress; Chou's 5-steps rule; chromatin interactions; classification; clustering; computational biology; computational intelligence; Convolution Neural Network (CNN); CRISPR-Cas9; data mining; deep learning; differential genes expression; differentiation; DNA methylation; DNA N6-methyladenine; DREB; ensembles; eQTL; exercise; fine-mapping; gene co-expression network; Gene Ontology; gene-set enrichment; genome architecture; genomics; hepatocellular carcinoma; HIGD2A; high-fat diet; hypoxia; immune response; infiltration; infiltration tactics optimization algorithm; Long Short-Term Memory (LSTM); machine learning; machine-learning; meta-analysis; methylation; microarray; miRNA; mRNA expression; murine coronavirus; n/a; obesity; pathway; pathways; potential therapeutic targets; power; prediction; proteomics; quercetin; Reactome Pathways; RNA N6-methyladenosine site; single-cell clone; systems biology; text mining; transcription factor; transcriptomics; viral infection; yeast genome
• Persona (resp. second.): DivinaFederico; García-TorresMiguel; Gómez VelaFrancisco A
• Sommario/riassunto: In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.
• Titolo autorizzato: Computational Methods for the Analysis of Genomic Data and Biological Processes
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557129603321
• Lo trovi qui: Univ. Federico II