PAVOOC: designing CRISPR sgRNAs using 3D protein structures and functional domain annotations
| Autor: | Bertram Weiss, Djork-Arné Clevert, Andreas Steffen, Moritz Schaefer |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
Source code Computer science media_common.quotation_subject Computational biology Biochemistry Domain (software engineering) 03 medical and health sciences Protein structure Genome editing CRISPR Clustered Regularly Interspaced Short Palindromic Repeats Molecular Biology Gene 030304 developmental biology media_common Subgenomic mRNA computer.programming_language chemistry.chemical_classification Gene Editing 0303 health sciences 030302 biochemistry & molecular biology Python (programming language) Genome Analysis Applications Notes Computer Science Applications Visualization Amino acid Computational Mathematics Computational Theory and Mathematics chemistry CRISPR-Cas Systems Protein crystallization computer Algorithms Software RNA Guide Kinetoplastida |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4811 |
| Popis: | Summary Single-guide RNAs (sgRNAs) targeting the same gene can significantly vary in terms of efficacy and specificity. PAVOOC (Prediction And Visualization of On- and Off-targets for CRISPR) is a web-based CRISPR sgRNA design tool that employs state of the art machine learning models to prioritize most effective candidate sgRNAs. In contrast to other tools, it maps sgRNAs to functional domains and protein structures and visualizes cut sites on corresponding protein crystal structures. Furthermore, PAVOOC supports homology-directed repair template generation for genome editing experiments and the visualization of the mutated amino acids in 3D. Availability and implementation PAVOOC is available under https://pavooc.me and accessible using modern browsers (Chrome/Chromium recommended). The source code is hosted at github.com/moritzschaefer/pavooc under the MIT License. The backend, including data processing steps, and the frontend are implemented in Python 3 and ReactJS, respectively. All components run in a simple Docker environment. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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