Automated bioinformatics workflows

Xem 1-6 trên 6 kết quả Automated bioinformatics workflows
  • Automated bioinformatics workflows are more robust, easier to maintain, and results more reproducible when built with command-line utilities than with custom-coded scripts. Command-line utilities further benefit by relieving bioinformatics developers to learn the use of, or to interact directly with, biological software libraries.

    pdf7p viconnecticut2711 28-10-2020 7 0   Download

  • Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats.

    pdf10p vicolorado2711 23-10-2020 4 0   Download

  • The development of high-throughput experimental technologies, such as next-generation sequencing, have led to new challenges for handling, analyzing and integrating the resulting large and diverse datasets. Bioinformatical analysis of these data commonly requires a number of mutually dependent steps applied to numerous samples for multiple conditions and replicates.

    pdf13p viconnecticut2711 28-10-2020 6 0   Download

  • Technical advances in Next Generation Sequencing (NGS) provide a means to acquire deeper insights into cellular functions. The lack of standardized and automated methodologies poses a challenge for the analysis and interpretation of RNA sequencing data.

    pdf11p vioklahoma2711 19-11-2020 1 0   Download

  • Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes.

    pdf4p vioklahoma2711 19-11-2020 3 0   Download

  • DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data.

    pdf15p vicolorado2711 22-10-2020 4 0   Download


207 tài liệu
948 lượt tải

p_strKeyword=Automated bioinformatics workflows

nocache searchPhinxDoc


Đồng bộ tài khoản