chemical.dissimilarity

This function calculates the structural dissimilarity between different metabolites using the simplified molecular-input line-entry system (SMILE) of each metabolite as input.

A new pipeline to explore chemical structural similarity across metabolites. It allows the metabolite classification in structurally-related modules and identifies common shared functional groups. The KODAMA algorithm is used to highlight structural similarity between metabolites. See Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. (2017) Bioinformatics <doi:10.1093/bioinformatics/btw705>, Cacciatore S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA <doi:10.1073/pnas.1220873111>, and Abdel-Shafy EA, Melak T, MacIntyre DA, Zadra G, Zerbini LF, Piazza S, Cacciatore S. (2023) Bioinformatics Advances <doi:10.1093/bioadv/vbad053>.

Stefano Cacciatore

MetChem

Chemical Structural Similarity Analysis

Ebtesam Abdel-Shafy

Tadele Melak

David A. MacIntyre

Giorgia Zadra

Luiz F. Zerbini

Silvano Piazza

chemical.dissimilarity function

<dl><dt>smiles</dt>
<dd>A vector of smile notations.</dd><dt>method</dt>
<dd>The method used to calculated the distance between molecular fingerprint ("tanimoto" as default). For more information see <code>fp.sim.matrix</code> function.</dd><dt>type</dt>
<dd>The type of fingerprint applied to the SMILEs ("extended" as default). For more information see <code>get.fingerprint</code> function.</dd></dl>

Arguments

Chemical dissimilarity. — chemical.dissimilarity

<dl>

<dt>smiles</dt>
<dd>A vector of smile notations.</dd>

<dt>method</dt>
<dd>The method used to calculated the distance between molecular fingerprint ("tanimoto" as default). For more information see <code>fp.sim.matrix</code> function.</dd>

<dt>type</dt>
<dd>The type of fingerprint applied to the SMILEs ("extended" as default). For more information see <code>get.fingerprint</code> function.</dd>

</dl>

chemical.dissimilarity: Chemical dissimilarity.

Description

Usage

Value

Arguments

See Also

Examples