https://github.com/carrascomj/kair

COnstraint-Based Reconstruction and Analysis in Rust
https://github.com/carrascomj/kair

cobra metabolism modeling simulation systems-biology

Last synced: about 2 months ago
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COnstraint-Based Reconstruction and Analysis in Rust

• Host: GitHub
• URL: https://github.com/carrascomj/kair
• Owner: carrascomj
• License: gpl-2.0
• Created: 2020-10-16T12:21:20.000Z (about 4 years ago)
• Default Branch: trunk
• Last Pushed: 2021-05-09T14:28:06.000Z (over 3 years ago)
• Last Synced: 2024-10-11T09:42:56.392Z (2 months ago)
• Topics: cobra, metabolism, modeling, simulation, systems-biology
• Language: Rust
• Homepage:
• Size: 140 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# KAIr (COBRA Alternative In rust)

[![Crates.io](https://img.shields.io/crates/v/kair.svg)](https://crates.io/crates/kair)

[![Documentation](https://docs.rs/kair/badge.svg)](https://docs.rs/kair/)

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[![Codecov](https://codecov.io/github/carrascomj/kair/coverage.svg?branch=trunk)](https://codecov.io/gh/carrascomj/kair)

*COnstraint-Based Reconstruction and Analysis* (COBRA) methods

enable the use of knowledge-based reconstructions of the metabolism of a

particular organism to simulate its metabolic network.

**kair** provides the translation from a [SBML](http://sbml.org/Special/specifications/sbml-level-3/version-2/core/release-2/sbml-level-3-version-2-release-2-core.pdf) (using [rust_sbml](https://github.com/carrascomj/rust_sbml/)) document to the most basic

Linear Programming formulation of COBRA: Flux Balance Analysis (FBA). Being

`f(z)` a function to optimize (historically, the biomass pseudoreaction or the ATPase),

`S` and stoichimetry matrix; and `v` the flux vector representing

the reactions in the reconstruction:



The FBA problem can then be optimized thanks to [lp_modeler](https://github.com/jcavat/rust-lp-modeler).

See [What is flux balance analysis?, Orth et al., 2010](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3108565/)

for a brief description of FBA.

## Installation

Add **kair** it to your Cargo.toml:

```toml

[dependencies]

kair = "0.5.0"

```

In addition, add [`good_lp`](https://github.com/rust-or/good_lp) with the solver of choice, for instance `coin_cbc` (default):

```toml

[dependencies]

good_lp = { version="1.1.0", default_features=true }

```

Make sure you have installed the [Cbc solver](https://github.com/coin-or/Cbc#binaries)

(other solvers do not require installation).

```shell

# Debian

sudo apt install coinor-cbc

# Arch

sudo pacman -S coin-or

# Mac OS

brew tap coin-or-tools/coinor && brew install coin-or-tools/coinor/cbc

```

## Example

Some `use` statements to get started.

```rust

use kair::{ModelLP, fba, flux_analysis::fva};

use good_lp::default_solver;

use std::str::FromStr;

```

First, read the SBML document, we will be using the [e_coli_core model](http://bigg.ucsd.edu/models/e_coli_core).

```rust

let file_str = std::fs::read_to_string("examples/EcoliCore.xml").unwrap();

let model = ModelLP::from_str(&file_str).unwrap();

```

Now, we can optimize it and print the solution, which is just a

[HashMap](https://doc.rust-lang.org/std/collections/struct.HashMap.html) of

pairs _variable name_ -> _solution value_.

```rust

for (name, val) in fba(&mut model, default_solver).unwrap().iter() {

    println!("{} = {}", name, val)

}

```

_Output_

```

R_EX_co2_e_ = 22.809834

R_ATPM_ = 8.39

R_H2Ot_ = -29.175827

R_GLNS_ = 0.22346173

...

R_BIOMASS_Ecoli_core_w_GAM_ = 0.8739215

...

R_EX_pi_e_ = -3.214895

R_SUCOAS_ = -5.064376

R_PGL_ = 4.959985

R_TKT1_ = 1.4969838

```

To run this example, on the root of this repository, run

```shell

cargo run --example ecoli

```

Flux variability analysis is also implemented:

```rust

let reactions: Vec = model.reactions.iter().map(|(k, _v)| k.clone()).collect();

for (name, val) in fva(&mut model, default_solver, reactions).unwrap().iter() {

    println!("{} = {:?}", name, val)

}

```

_Output (you would need to use a bigger model to see the difference)_

```

R_ACONTa = (6.007249575350586, 6.007249575350007)

R_ACALD = (0.0, 0.0)

R_ACKr = (-0.0, -0.0)

R_ICDHyr = (6.007249575351851, 6.007249575350007)

R_CO2t = (-22.80983331020489, -22.809833310205118)

R_RPI = (-2.2815030940668573, -2.2815030940674283)

R_ADK1 = (-0.0, -0.0000000000003395200787181807)

R_PGK = (-16.0235261431673, -16.02352614316787)

R_SUCCt3 = (0.0, -0.0000000000004168517383125921)

R_EX_pyr_e = (0.0, 0.0)

```