UniGene
UniGene is a database of the NCBI that provides a non-redundant set of gene-oriented clusters of EST sequences. It is a valuable resource for researchers in the field of genomics and bioinformatics.
Overview[edit | edit source]
UniGene was developed to organize EST sequences into clusters that represent a unique gene or a set of closely related genes. Each UniGene cluster contains sequences that are believed to come from the same transcription locus, along with related information such as tissue types in which the gene is expressed and chromosomal location.
Functionality[edit | edit source]
UniGene serves several important functions in the field of genomics:
- Gene Discovery: By clustering ESTs, UniGene helps in identifying new genes and understanding gene expression patterns across different tissues.
- Expression Analysis: Researchers can use UniGene to study the expression of genes in various tissues and developmental stages.
- Sequence Alignment: UniGene provides alignments of ESTs to known genomic sequences, aiding in the annotation of genomes.
Data Organization[edit | edit source]
UniGene organizes data into clusters based on sequence similarity. Each cluster is assigned a unique identifier and includes:
- A list of EST sequences
- Information about the tissues from which the sequences were derived
- Links to related gene information in other databases
Applications[edit | edit source]
UniGene is widely used in bioinformatics and genomics research for:
- Gene Annotation: Assisting in the annotation of genomic sequences by providing evidence of transcription.
- Comparative Genomics: Facilitating the comparison of gene expression patterns across different species.
- Functional Genomics: Supporting studies on gene function and regulation by providing expression data.
Limitations[edit | edit source]
While UniGene is a powerful tool, it has some limitations:
- Redundancy: Some clusters may contain sequences from closely related genes, leading to potential redundancy.
- Incomplete Coverage: Not all genes are represented in UniGene, especially those with low expression levels.
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Contributors: Prab R. Tumpati, MD
