Genomic Databases
Genomic Databases - Related Videos
16:17
The ITS2 Database
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Cited by 52 •
2012
The ITS2 Database is a workbench for phylogenetic inference simultaneously considering sequence and secondary structure of the internal transcribed spacer 2. This includes data collection with accurate annotation, structure prediction, multiple sequence-structure alignment and fast tree calculation. In a nutshell, this workbench simplifies first phylogenetic analyses to a few clicks.
01:28
Database Searching
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2026
Effective research begins with the ability to navigate academic databases efficiently. Unlike general web search engines, scholarly databases are designed to index peer-reviewed articles, conference proceedings, and other credible academic publications. Developing a structured search strategy ensures that researchers can identify relevant, high-quality sources with precision. For example, when studying how sleep patterns relate to circadian rhythms in humans, researchers should move beyond...
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.
11:18
Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
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Cited by 5 •
2011
A thoracic oncology database was developed to serve as a comprehensive repository for clinical and laboratory data for the purposes of translational research. The database will serve translational cancer researchers within the Thoracic Oncology Research Program. This database is adaptable to other cancer models, as well as other human diseases.
02:02
Genomics
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2020
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
FAQs
Indexing makes genomic database records searchable by organizing sequence data, gene annotations, and metadata so that users can retrieve relevant entries rather than examine records individually. This organization also supports links among genes, genomes, and species. As a result, a search can connect a sequence with its biological annotation and broader genomic context, supporting more efficient investigation.
Gene annotations add interpretive information to sequence records, while metadata describes the context associated with those records. Keeping these elements connected helps researchers examine not only DNA sequences but also the information attached to them. This distinction matters because sequence data alone may be difficult to interpret, whereas annotations and metadata provide context for biological analysis.
Genomic Databases support sequence comparisons by placing DNA records alongside one another to reveal similarities and differences among genes, genomes, or species. Indexed records and cross-connections make these comparisons easier to initiate and interpret. Researchers can therefore examine genome structure, investigate evolutionary relationships, or assess how genetic information varies across organisms.
Genomic databases support genetic-variation research by bringing sequence records together with annotations and metadata, allowing researchers to examine differences in a biological context. They can also connect variation with genes, genomes, and species, helping organize questions about how genetic changes relate to gene function or disease-associated changes. This supports interpretation beyond simply observing sequence differences.
A typical investigation starts with a search for relevant sequence records, followed by review of the associated gene annotations and metadata. Researchers can then compare sequences or follow connections among genes, genomes, and species. This workflow helps them move from locating a record to examining its biological meaning, while keeping sequence information available for reproducible analysis.
Researchers apply these resources to questions about gene function, genome structure and evolution, genetic variation, disease-associated changes, and biodiversity. The same database-based approach can therefore serve different biological goals, including comparing organisms, examining relationships among genomic records, or interpreting changes in DNA. Its usefulness comes from matching relevant records and associated information to the research question.
As sequencing projects expand, genomic databases become increasingly important for organizing the growing body of sequence data and related annotations. They provide a shared basis for searching, comparing, and connecting records, which supports reproducible biological analysis. Continued growth also enables researchers to revisit questions about genes, genomes, species, and variation as additional information becomes available.