Computational Methods for the Analysis of Genomic Data and Biological Processes
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 bi...
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| Ձևաչափ: | Online |
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| Լեզու: | անգլերեն |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Խորագրեր: | |
| Առցանց հասանելիություն: | ONIX_20210501_9783039437719_110 |
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Չկան պիտակներ, Եղեք առաջինը, ով նշում է այս գրառումը!
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| _version_ | 1869526878922997760 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-68364 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-683642024-03-28T03:33:48Z Computational Methods for the Analysis of Genomic Data and Biological Processes Gómez Vela, Francisco A. Divina, Federico García-Torres, Miguel 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences 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. 2021-05-01T15:08:11Z 2021-05-01T15:08:11Z 2021 book ONIX_20210501_9783039437719_110 9783039437719 9783039437726 https://directory.doabooks.org/handle/20.500.12854/68364 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3374 https://mdpi.com/books/pdfview/book/3374 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03943-772-6 10.3390/books978-3-03943-772-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039437719 9783039437726 222 Basel, Switzerland open access |
| spellingShingle | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences Computational Methods for the Analysis of Genomic Data and Biological Processes |
| title | Computational Methods for the Analysis of Genomic Data and Biological Processes |
| title_full | Computational Methods for the Analysis of Genomic Data and Biological Processes |
| title_fullStr | Computational Methods for the Analysis of Genomic Data and Biological Processes |
| title_full_unstemmed | Computational Methods for the Analysis of Genomic Data and Biological Processes |
| title_short | Computational Methods for the Analysis of Genomic Data and Biological Processes |
| title_sort | computational methods for the analysis of genomic data and biological processes |
| topic | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences |
| topic_facet | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences |
| url | ONIX_20210501_9783039437719_110 |