In Silico Identification and Characterization of Effector Catalogs
Ronnie de Jonge
Abstract
Ronnie de Jonge
Abstract
Many characterized fungal effector proteins are small secreted proteins. Effectors are defined as those proteins that alter host cell structure and/or function by facilitating pathogen infection. The identification of effectors by molecular and cell biology techniques is a difficult task. However, with the availability of whole-genome sequences, these proteins can now be predicted in silico. Here, we describe in detail how to identify and characterize effectors from a defined fungal proteome using in silico techniques.
OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Many characterized fungal effector proteins are small secreted proteins. Effectors are defined as those proteins that alter host cell structure and/or function by facilitating pathogen infection. The identification of effectors by molecular and cell biology techniques is a difficult task. However, with the availability of whole-genome sequences, these proteins can now be predicted in silico. Here, we describe in detail how to identify and characterize effectors from a defined fungal proteome using in silico techniques.
Key concepts: Effector, In silico, Computational biology, Proteome, Identification (biology), Biology, Function (biology), Genome