Computational Methods for the Analysis of Genomic Data and Biological Processes

• Muut tekijät: Gómez Vela, Francisco A. (Toimittaja), Divina, Federico (Toimittaja), García-Torres, Miguel (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Aiheet: Research & information: general; Biology, life sciences; HIGD2A; cancer; DNA methylation; mRNA expression; miRNA; quercetin; hypoxia; eQTL; CRISPR-Cas9; single-cell clone; fine-mapping; power; RNA N6-methyladenosine site; yeast genome; methylation; computational biology; deep learning; bioinformatics; hepatocellular carcinoma; transcriptomics; proteomics; bioinformatics analysis; differentiation; Gene Ontology; Reactome Pathways; gene-set enrichment; meta-analysis; transcription factor; binding sites; genomics; chilling stress; CBF; DREB; CAMTA1; pathway; text mining; infiltration tactics optimization algorithm; classification; clustering; microarray; ensembles; machine learning; infiltration; computational intelligence; gene co-expression network; murine coronavirus; viral infection; immune response; data mining; systems biology; obesity; differential genes expression; exercise; high-fat diet; pathways; potential therapeutic targets; DNA N6-methyladenine; Chou's 5-steps rule; Convolution Neural Network (CNN); Long Short-Term Memory (LSTM); machine-learning; chromatin interactions; prediction; genome architecture; n/a
• Linkit: DOAB: download the publication; DOAB: description of the publication

Yhteenveto

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.

Ulkoasu

1 electronic resource (222 p.)

ISBN

books978-3-03943-772-6
9783039437719
9783039437726

Pääsy

Open Access