Develop a method to quantify splice site strength across vertebrate species using computational models to analyze splice site sequences and predict splicing outcomes.
Splice site strength is a critical determinant in the accurate recognition and processing of pre-mRNA during splicing, a process that plays a pivotal role in gene expression regulation. This project aims to develop a novel method for quantifying splice site strength across various vertebrate species by systematically analysing splice site sequences. By leveraging advanced computational approaches, we will identify and compare sequence patterns of both donor (5') and acceptor (3') splice sites, focusing on conserved motifs and species-specific variations. Using a combination of position weight matrices (PWM) and maximum entropy models (MaxEntScan), we will create a scoring framework that accurately predicts splice site strength. Our approach will integrate both nucleotide composition and sequence context, accounting for evolutionary divergence among vertebrates. The resulting scoring method will provide valuable insights into splicing mechanisms, potential regulatory elements, and the evolutionary conservation of splicing signals. Ultimately, this project will contribute to a deeper understanding of splicing regulation in vertebrates and pave the way for more accurate predictions of splicing outcomes in genomic studies.
Provide instructions on how to install and set up the project, such as installing dependencies and preparing the environment.
# Example command to install dependencies (Python)
pip install project-dependencies
# Example command to install dependencies (R)
install.packages("project-dependencies")Provide a basic usage example or minimal code snippet that demonstrates how to use the project.
# Example usage (Python)
import my_project
demo = my_project.example_function()
print(demo)# Example usage (R)
library(my_project)
demo <- example_function()
print(demo)Add detailed information and examples on how to use the project, covering its major features and functions.
# More usage examples (Python)
import my_project
demo = my_project.advanced_function(parameter1='value1')
print(demo)# More usage examples (R)
library(demoProject)
demo <- advanced_function(parameter1 = "value1")
print(demo)Contributions are welcome! If you'd like to contribute, please open an issue or submit a pull request. See the contribution guidelines for more information.
If you have any issues or need help, please open an issue or contact the project maintainers.
This project is licensed under the MIT License.