Results 321-330 of about 359
- Single-cell genome and transcriptome sequencing methods are generating a fresh wave of biological insights into development, cancer and neuroscience. Kelly Rae Chi reports.
Date: (2014) Authors: Kelly Rae Chi - Transcriptional profiling is a powerful approach for studying mouse development, physiology and disease models. Here we describe a protocol for mouse thiouracil tagging (TU tagging), a transcriptome analysis technology that includes in vivo covalent
Date: (2014) Authors: Leslie Gay , Kate V Karfilis , Michael R Miller , Chris Q Doe , Kryn Stankunas - Image-based transcriptomics in thousands of single human cells at single-molecule resolution new windowFluorescence in situ hybridization (FISH) is widely used to obtain information about transcript copy number and subcellular localization in single cells. However, current approaches do not readily scale to the analysis of whole transcriptomes. Here
Date: (2013) Authors: Nico Battich , Thomas Stoeger , Lucas Pelkmans - A number of studies have shown that functionally related genes are often co-expressed and that computational based co-expression analysis can be used to accurately identify functional relationships between genes and by inference, their encoded
Date: (2013) Authors: May Alqurashi , Stuart Meier Ref: Cyclic Nucleotide Signaling in Plants - Next generation sequencing technologies may now be applied to the study of transcriptomics. RNA-Seq or RNA sequencing employs high-throughput sequencing of complementary DNA fragments delivering a transcriptional profile. In this chapter, we aim to
Date: (2012) Authors: Dasfne Lee-Liu , Leonardo I. Almonacid , Fernando Faunes , Francisco Melo , Juan Larrain Ref: Xenopus Protocols - Transcriptomics has played an essential role as proof of concept in the development of experimental and bioinformatics approaches for the generation and analysis of Omics data. We are giving an introduction on how large-scale technologies for gene
Date: (2011) Authors: Fátima Sánchez-Cabo , Johannes Rainer , Ana Dopazo , Zlatko Trajanoski , Hubert Hackl Ref: Bioinformatics for Omics Data - Progress in experimental procedures has led to rapid availability of Omics profiles. Various open-access as well as commercial tools have been developed for storage, analysis, and interpretation of transcriptomics, proteomics, and metabolomics data.
Date: (2011) Authors: Irmgard Mühlberger , Julia Wilflingseder , Andreas Bernthaler , Raul Fechete ... Paul Perco Ref: Bioinformatics for Omics Data - Modeling is a means for integrating the results from Genomics, Transcriptomics, Proteomics, and Metabolomics experiments and for gaining insights into the interaction of the constituents of biological systems. However, sharing such large amounts of
Date: (2011) Authors: Michael Kohl Ref: Data Mining in Proteomics - In this protocol, we describe a pipeline for transcript analysis in yeast via the quantification of mRNA expression levels. In the first section, we consider the well-established, proprietary Affymetrix GeneChip® approach to generating
Date: (2011) Authors: Andrew Hayes , Bharat M. Rash , Leo A.H. Zeef Ref: Yeast Systems Biology - The diverse fields of Omics research share a common logical structure combining a cataloging effort for a particular class of molecules or interactions, the underlying -ome, and a quantitative aspect attempting to record spatiotemporal patterns of
Date: (2011) Authors: Sonja J. Prohaska , Peter F. Stadler Ref: Bioinformatics for Omics Data