NPLinker

Cunliang Geng; Giulia Crocioni; Simon Rogers; Andrew Ramsay; Katherine Duncan; J.J.J. van der Hooft; Grímur Hjörleifsson; Sylvia Soldatou; Florian Huber; Joe Wandy; Ronan Daly; J.J.R. Louwen; M.H. Medema

doi:10.5281/zenodo.4680218

NPLinker

Cunliang Geng, Giulia Crocioni, Simon Rogers, Andrew Ramsay, Katherine Duncan, J.J.J. van der Hooft, Grímur Hjörleifsson, Sylvia Soldatou, Florian Huber, Joe Wandy, Ronan Daly, J.J.R. Louwen, M.H. Medema

Bioinformatics

Research output: Non-textual form › Software

Abstract

NPLinker aims to address the significant bottleneck that exists in the realization of the potential of genome-led metabolite discovery, namely the slow manual matching of predicted biosynthetic gene clusters (BGCs) with metabolites produced during bacterial culture; linking phenotype to genotype.
NPLinker implements a new data-centric approach to alleviate this linking problem by searching for patterns of strain presence and absence between groups of similar spectra (molecular families; MF) and groups of similar BGCs (gene cluster families; GCF). Searches can be performed using a number of available analysis methods employed in isolation or together.

Original language	English
Publisher	Zenodo
Media of output	Online
DOIs	https://doi.org/10.5281/zenodo.4680218
Publication status	Published - 12 Apr 2021

Access to Document

10.5281/zenodo.4680218Licence: Apache

1 Article

Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions
Eldjarn, G. H., Ramsay, A., Van Der Hooft, J. J. J., Duncan, K. R., Soldatou, S., Rousu, J., Daly, R., Wandy, J. & Rogers, S., 4 May 2021, In: PLoS Computational Biology. 17, 5 May, e1008920.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
25 Citations (Scopus)

Cite this

@misc{c32b37ca6ee140249f6037c3416de17e,

title = "NPLinker",

abstract = "NPLinker aims to address the significant bottleneck that exists in the realization of the potential of genome-led metabolite discovery, namely the slow manual matching of predicted biosynthetic gene clusters (BGCs) with metabolites produced during bacterial culture; linking phenotype to genotype.NPLinker implements a new data-centric approach to alleviate this linking problem by searching for patterns of strain presence and absence between groups of similar spectra (molecular families; MF) and groups of similar BGCs (gene cluster families; GCF). Searches can be performed using a number of available analysis methods employed in isolation or together.",

author = "Cunliang Geng and Giulia Crocioni and Simon Rogers and Andrew Ramsay and Katherine Duncan and {van der Hooft}, J.J.J. and Gr{\'i}mur Hj{\"o}rleifsson and Sylvia Soldatou and Florian Huber and Joe Wandy and Ronan Daly and J.J.R. Louwen and M.H. Medema",

year = "2021",

month = apr,

day = "12",

doi = "10.5281/zenodo.4680218",

language = "English",

publisher = "Zenodo",

address = "Switzerland",

}

TY - ADVS

T1 - NPLinker

AU - Geng, Cunliang

AU - Crocioni, Giulia

AU - Rogers, Simon

AU - Ramsay, Andrew

AU - Duncan, Katherine

AU - van der Hooft, J.J.J.

AU - Hjörleifsson, Grímur

AU - Soldatou, Sylvia

AU - Huber, Florian

AU - Wandy, Joe

AU - Daly, Ronan

AU - Louwen, J.J.R.

AU - Medema, M.H.

PY - 2021/4/12

Y1 - 2021/4/12

N2 - NPLinker aims to address the significant bottleneck that exists in the realization of the potential of genome-led metabolite discovery, namely the slow manual matching of predicted biosynthetic gene clusters (BGCs) with metabolites produced during bacterial culture; linking phenotype to genotype.NPLinker implements a new data-centric approach to alleviate this linking problem by searching for patterns of strain presence and absence between groups of similar spectra (molecular families; MF) and groups of similar BGCs (gene cluster families; GCF). Searches can be performed using a number of available analysis methods employed in isolation or together.

AB - NPLinker aims to address the significant bottleneck that exists in the realization of the potential of genome-led metabolite discovery, namely the slow manual matching of predicted biosynthetic gene clusters (BGCs) with metabolites produced during bacterial culture; linking phenotype to genotype.NPLinker implements a new data-centric approach to alleviate this linking problem by searching for patterns of strain presence and absence between groups of similar spectra (molecular families; MF) and groups of similar BGCs (gene cluster families; GCF). Searches can be performed using a number of available analysis methods employed in isolation or together.

U2 - 10.5281/zenodo.4680218

DO - 10.5281/zenodo.4680218

M3 - Software

PB - Zenodo

ER -

NPLinker

Abstract

Access to Document

Fingerprint

Research output

Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions

Cite this