SERBA-2

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SERBA-2 is a bioinformatics tool used for the identification and annotation of serine and arginine rich proteins. These proteins, often referred to as SR proteins, play a crucial role in RNA splicing, a process that is essential for gene expression in eukaryotic cells.

Overview[edit | edit source]

SERBA-2 is an updated version of the original SERBA tool, offering improved accuracy and a wider range of features. It utilizes a combination of machine learning algorithms and sequence alignment techniques to identify SR proteins in a given protein sequence. The tool also provides detailed annotation information, including the location of RNA recognition motifs (RRMs) and SR domains.

Functionality[edit | edit source]

The primary function of SERBA-2 is to identify and annotate SR proteins in protein sequences. Users input a protein sequence, and the tool outputs a list of potential SR proteins, along with detailed annotation information. This includes the location of RRMs and SR domains, which are key features of SR proteins.

In addition to identifying SR proteins, SERBA-2 also provides information on their potential roles in RNA splicing. This is achieved through the use of gene ontology (GO) terms, which provide a standardized way of representing gene product attributes across all species.

Applications[edit | edit source]

SERBA-2 has a wide range of applications in bioinformatics and molecular biology. It can be used to identify SR proteins in newly sequenced genomes, aiding in the annotation process. It can also be used in research studies investigating the role of SR proteins in RNA splicing and other cellular processes.

See Also[edit | edit source]

References[edit | edit source]

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Contributors: Prab R. Tumpati, MD