Molecular Signature Database
Molecular Signature Database - 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...
09:11
Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures
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Cited by 1 •
2021
Here, we present a protocol to investigate the impacts of hydraulic fracturing on nearby streams by analyzing their water and sediment microbial communities.
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.
09:55
Molecular Cloning
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2023
Molecular cloning is a set of methods, which are used to insert recombinant DNA into a vector - a carrier of DNA molecules that will replicate recombinant DNA fragments in host organisms. The DNA fragment, which may be a gene, can be isolated from a prokaryotic or eukaryotic specimen. Following isolation of the fragment of interest, or insert, both the vector and insert must be cut with restriction enzymes and purified. The purified pieces are joined together though a technique called...
FAQs
Coordinated patterns can reveal a biological program even when changes in individual genes are modest or varied. By grouping genes that share a defined feature, MSigDB helps relate expression changes to pathways, cellular processes, regulatory programs, or disease-associated states. This broader view supports interpretation at the level of functional systems rather than isolated molecular measurements.
Gene set enrichment analysis and related computational methods compare an expression profile with groups of genes represented in MSigDB. The analysis asks whether genes associated with a particular pathway, process, or state show a coordinated relationship with the experimental phenotype or condition. Results can therefore connect transcriptomic patterns to broader biological programs.
The collections encompass signatures linked to biological pathways, cellular processes, regulatory programs, and disease-associated states. This range allows the same expression dataset to be examined from several perspectives, such as functional activity, regulation, or disease relevance. Using standardized collections also gives researchers a consistent framework for comparing molecular patterns across experiments.
A typical workflow begins with an expression profile from an experiment, followed by comparison with relevant MSigDB gene sets through gene set enrichment analysis or a related method. Researchers then examine which signatures are associated with the phenotype, treatment, or experimental condition. Those associations provide a structured basis for interpreting coordinated molecular changes.
MSigDB is useful when researchers need to determine which biological programs accompany a phenotype, treatment, or experimental condition. Instead of interpreting a long list of altered transcripts separately, they can assess whether pathway or regulatory signatures show coordinated associations. This approach helps organize high-throughput results and identify processes that may deserve further biological investigation.
Associations between an expression profile and selected signatures can suggest broader cellular or disease processes underlying an observed result. These findings do not simply catalog altered genes; they connect molecular changes with interpretable biological programs. Researchers can use those connections to formulate mechanistic hypotheses about how a phenotype or treatment relates to pathways, regulation, or disease-associated states.