Genomic Scale Measurement
Genomic Scale Measurement - Related Videos
06:56
Micro/Nano-scale Strain Distribution Measurement from Sampling Moiré Fringes
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Cited by 7 •
2017
A sampling moiré technique featuring 2-pixel and multi-pixel sampling methods for high-accuracy strain distribution measurements at the micro/nano-scale is presented here.
10:56
Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
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Cited by 217 •
2014
Ribosomes play a central role in protein synthesis. Polyribosome (polysome) fractionation by sucrose density gradient centrifugation allows direct determination of translation efficiencies of individual mRNAs on a genome-wide scale. In addition, this method can be used for biochemical analysis of ribosome- and polysome-associated factors such as chaperones and signaling molecules.
06:40
Small-Scale Extraction of Caenorhabditis elegans Genomic DNA
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Cited by 3 •
2022
Presented here is a description of the straightforward and relatively rapid isolation of Caenorhabditis elegans genomic DNA from one or a few animals using a commercially available tissue kit. The resulting gDNA preparation is a suitable template for PCR.
10:49
Power Input Measurements in Stirred Bioreactors at Laboratory Scale
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Cited by 9 •
2018
The power input in stirred bioreactors can be measured through the torque that acts on the impeller shaft during rotation. This manuscript describes how an air bearing can be used to effectively reduce friction losses observed in mechanical seals and improve the accuracy of power input measurements in small-scale vessels.
08:31
Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
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Cited by 2 •
2013
Single Virus Genomics (SVG) is a method to isolate and amplify the genomes of single virons. Viral suspensions of a mixed assemblage are sorted using flow cytometry onto a microscope slide with discrete wells containing agarose, thereby capturing the virion and reducing genome shearing during downstream processing. Whole genome amplification is achieved using multiple displacement amplification (MDA) resulting in genomic material that is suitable for sequencing.
FAQs
The process links high-throughput sequencing or related molecular assays with computational analysis. Software processes large numbers of DNA or RNA signals, aligns them to reference genomes, and searches for recurring patterns. Depending on the assay, those patterns can indicate sequence changes, differences in gene activity, or regulatory features across the genome.
A reference genome provides a framework for organizing and comparing DNA or RNA signals from a sample. Alignment places those signals in genomic context, allowing researchers to recognize where patterns occur and evaluate variation across the genome. Without this common framework, broad measurements would be more difficult to interpret consistently or compare across studies.
A targeted test focuses on a selected gene or genomic location, whereas genomic-scale measurement examines patterns across the entire genome. This wider scope can reveal relationships that a single-locus analysis may miss, including coordinated changes in sequence, gene activity, or regulatory features. The approach therefore supports broader comparative and systems-level interpretation.
The information obtained depends on the molecular signals measured and the computational analysis applied to them. DNA-focused measurements can support examination of sequence changes, while RNA-related measurements can reveal patterns of gene activity. Analyses that capture regulatory features provide another layer of interpretation, connecting genomic locations with broader biological organization.
A typical workflow begins with a high-throughput sequencing or related molecular assay that generates many DNA or RNA signals. Computational methods then process those signals, align them to a reference genome, and identify relevant patterns. The resulting measurements can be organized for comparisons among genomes, biological samples, populations, or experimental conditions.
Researchers apply it to genome mapping, population studies, disease research, and investigations of cellular responses to environmental or developmental conditions. By measuring broad genomic patterns, they can compare biological states and examine relationships across many features at once. The same data also support comparative research and systems-level studies of biological organization.