Uses old Rust 2015
|new 0.1.9||Feb 2, 2023|
|0.1.6||Dec 27, 2022|
|0.1.5||Nov 23, 2022|
|0.1.2||Jul 26, 2022|
#73 in Science
168 downloads per month
Used in consalign
Trainable Probability Inference Engine on RNA Structural Alignment
This project is written in Rust, a systems programming language. You need to install Rust components, i.e., rustc (the Rust compiler), cargo (the Rust package manager), and the Rust standard library. Visit the Rust website to see more about Rust. You can install Rust components with the following one line:
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
Rustup arranges the above installation and enables to switch a compiler in use easily. You can install ConsProb:
# AVX, SSE, and MMX enabled for rustc # Another example: RUSTFLAGS='--emit asm -C target-feature=+avx2 -C target-feature=+ssse3 -C target-feature=+mmx -C target-feature=+fma' RUSTFLAGS='--emit asm -C target-feature=+avx -C target-feature=+ssse3 -C target-feature=+mmx' \ cargo install consprob-trained
Check if you have installed ConsProb properly:
# Its available command options will be displayed consprob_trained
You can run ConsProb with a prepared test set of sampled tRNAs:
git clone https://github.com/heartsh/consprob-trained \ && cd consprob-trained cargo test --release # The below command requires Gnuplot (http://www.gnuplot.info) # Benchmark results will be found at "./target/criterion/report/index.html" cargo bench
I offer my Docker-based playground for RNA software and its instruction to replay my computational experiments easily.
ConsProb-Turner can compute a variety of sparse posterior probabilities on RNA pairwise structural alignment using Turner's model. This repository offers ConsProb-trained, a machine-learning counterpart of ConsProb-Turner. This repository also includes a ConsTrain, structural alignment-based machine-learning method for ConsProb-trained.
Copyright (c) 2018 Heartsh
Licensed under the MIT license.