AIMC Topic: Transcriptome
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Gene expression prediction using low-rank matrix completion.
BMC bioinformatics
Jun 17, 2016
BACKGROUND: An exponential growth of high-throughput biological information and data has occurred in the past decade, supported by technologies, such as microarrays and RNA-Seq. Most data generated using such methods are used to encode large amounts ...
REGene: a literature-based knowledgebase of animal regeneration that bridge tissue regeneration and cancer.
Scientific reports
Mar 15, 2016
Regeneration is a common phenomenon across multiple animal phyla. Regeneration-related genes (REGs) are critical for fundamental cellular processes such as proliferation and differentiation. Identification of REGs and elucidating their functions may ...
GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.
BMC bioinformatics
Mar 11, 2016
BACKGROUND: Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of ...
Transcriptomes of lineage-specific Drosophila neuroblasts profiled by genetic targeting and robotic sorting.
Development (Cambridge, England)
Dec 23, 2015
A brain consists of numerous distinct neurons arising from a limited number of progenitors, called neuroblasts in Drosophila. Each neuroblast produces a specific neuronal lineage. To unravel the transcriptional networks that underlie the development ...
Predicting target proteins for drug candidate compounds based on drug-induced gene expression data in a chemical structure-independent manner.
BMC medical genomics
Dec 18, 2015
BACKGROUND: Phenotype-based high-throughput screening is a useful technique for identifying drug candidate compounds that have a desired phenotype. However, the molecular mechanisms of the hit compounds remain unknown, and substantial effort is requi...
Putative synaptic genes defined from a Drosophila whole body developmental transcriptome by a machine learning approach.
BMC genomics
Sep 15, 2015
BACKGROUND: Assembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Although roughly a thousand genes are expected to be important for this function in Drosophila melanogaster, just a few hund...
Seq-ing improved gene expression estimates from microarrays using machine learning.
BMC bioinformatics
Sep 4, 2015
BACKGROUND: Quantifying gene expression by RNA-Seq has several advantages over microarrays, including greater dynamic range and gene expression estimates on an absolute, rather than a relative scale. Nevertheless, microarrays remain in widespread use...
OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.
Bioinformatics (Oxford, England)
Aug 12, 2015
MOTIVATION: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task.
Computational assignment of cell-cycle stage from single-cell transcriptome data.
Methods (San Diego, Calif.)
Jul 2, 2015
The transcriptome of single cells can reveal important information about cellular states and heterogeneity within populations of cells. Recently, single-cell RNA-sequencing has facilitated expression profiling of large numbers of single cells in para...
A tuberculosis ontology for host systems biology.
Tuberculosis (Edinburgh, Scotland)
Jun 30, 2015
A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a mea...
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