We present SWIMmeR, an open-source version of its predecessor SWIM (SWitchMiner) that is a network-based tool for mining key (switch) genes that are associated with intriguing patterns of molecular coabundance and may play a crucial role in phenotypic transitions in various biological settings. SWIM was originally written in MATLABVR , a proprietary programming language that requires the purchase of a license to install, manipulate, operate and run the software. Over the last years, SWIM has sparked a widespread interest within the scientific community thanks to the promising results obtained through its application in a broad range of phenotype-specific scenarios, spanning from complex diseases to grapevine berry maturation. This success has created the call for it to be distributed in a freely accessible, open-source, runtime environment, such as R, aimed at a general audience of non-expert users that cannot afford the leading proprietary solution. SWIMmeR is provided as a comprehensive collection of R functions and it also includes several additional features that make it less intensive in terms of computer time and more efficient in terms of usability and further implementation and extension.

SWIMmeR: An R-based software to unveiling crucial nodes in complex biological networks / Paci, P.; Fiscon, G.. - In: BIOINFORMATICS. - ISSN 1367-4803. - 38:2(2022), pp. 586-588. [10.1093/bioinformatics/btab657]

SWIMmeR: An R-based software to unveiling crucial nodes in complex biological networks

Paci P.
;
Fiscon G.
2022

Abstract

We present SWIMmeR, an open-source version of its predecessor SWIM (SWitchMiner) that is a network-based tool for mining key (switch) genes that are associated with intriguing patterns of molecular coabundance and may play a crucial role in phenotypic transitions in various biological settings. SWIM was originally written in MATLABVR , a proprietary programming language that requires the purchase of a license to install, manipulate, operate and run the software. Over the last years, SWIM has sparked a widespread interest within the scientific community thanks to the promising results obtained through its application in a broad range of phenotype-specific scenarios, spanning from complex diseases to grapevine berry maturation. This success has created the call for it to be distributed in a freely accessible, open-source, runtime environment, such as R, aimed at a general audience of non-expert users that cannot afford the leading proprietary solution. SWIMmeR is provided as a comprehensive collection of R functions and it also includes several additional features that make it less intensive in terms of computer time and more efficient in terms of usability and further implementation and extension.
2022
network medicine; co-expression network; gene expression; algorithms
01 Pubblicazione su rivista::01a Articolo in rivista
SWIMmeR: An R-based software to unveiling crucial nodes in complex biological networks / Paci, P.; Fiscon, G.. - In: BIOINFORMATICS. - ISSN 1367-4803. - 38:2(2022), pp. 586-588. [10.1093/bioinformatics/btab657]
File allegati a questo prodotto
File Dimensione Formato  
Paci_SWIMmeR_2022.pdf

solo gestori archivio

Note: https://doi.org/10.1093/bioinformatics/btab657
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 512.67 kB
Formato Adobe PDF
512.67 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1610414
Citazioni
  • ???jsp.display-item.citation.pmc??? 6
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 8
social impact