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Updated: May 13, 2026
10:00
An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
Published on: May 23, 2018
New insights from existing sequence data: generating breakthroughs without a pipette.
Alex M Plocik1, Brenton R Graveley
1Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT 06030, USA.
Molecular Cell
|February 27, 2013
Summary
Analyzing existing sequencing data is crucial for discovering biological phenomena and gene expression mechanisms. Researchers must address technical and bioinformatic challenges in these massive datasets.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- The cost of data generation is rapidly declining, leading to massive datasets in molecular biology.
- Analysis of existing data is becoming increasingly important for scientific discovery.
Purpose of the Study:
- To discuss resources for publicly available sequencing data.
- To explore the interrogation of gene expression mechanisms using existing data.
- To highlight challenges and breakthroughs in analyzing large sequencing datasets.
Main Methods:
- Review of publicly available sequencing data resources.
- Discussion of technical and bioinformatic artifacts in next-generation sequencing data.
- Case studies of breakthroughs from analyzing existing data, particularly in the RNA field.
Main Results:
- Identification of key resources for gene expression mechanism studies.
- Detailed discussion of artifacts impacting data analysis.
- Examples of significant discoveries derived from re-analyzing existing datasets.
Conclusions:
- The analysis of existing sequencing data is a powerful approach for advancing molecular biology.
- Addressing data artifacts is essential for reliable insights.
- Past successes underscore the potential for future discoveries through data re-analysis.
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