Supplementary tables:MetaFetcheR: An R package for complete mapping of small compound data
type: Dataset
distribution: Landing page for the dataset
description: The dataset includes a PDF file containing the results and an Excel file with the following tables: Table S1 Results of comparing the performance of MetaFetcheR to MetaboAnalystR using Diamanti et al. Table S2 Results of comparing the performance of MetaFetcheR to MetaboAnalystR for Priolo et al. Table S3 Results of comparing the performance of MetaFetcheR to MetaboAnalyst 5.0 webtool using Diamanti et al. Table S4 Results of comparing the performance of MetaFetcheR to MetaboAnalyst 5.0 webtool for Priolo et al. Table S5 Data quality test results for running 100 iterations on HMDB database. Table S6 Data quality test results for running 100 iterations on KEGG database. Table S7 Data quality test results for running 100 iterations on ChEBI database. Table S8 Data quality test results for running 100 iterations on PubChem database. Table S9 Data quality test results for running 100 iterations on LIPID MAPS database. Table S10 The list of metabolites that were not mapped by MetaboAnalystR for Diamanti et al. Table S11 An example of an input matrix for MetaFetcheR. Table S12 Results of comparing the performance of MetaFetcheR to MS_targeted using Diamanti et al. Table S13 Data set from Diamanti et al. Table S14 Data set from Priolo et al. Table S15 Results of comparing the performance of MetaFetcheR to CTS using KEGG identifiers available in Diamanti et al. Table S16 Results of comparing the performance of MetaFetcheR to CTS using LIPID MAPS identifiers available in Diamanti et al. Table S17 Results of comparing the performance of MetaFetcheR to CTS using KEGG identifiers available in Priolo et al. Table S18 Results of comparing the performance of MetaFetcheR to CTS using KEGG identifiers available in Priolo et al. (See the "index" tab in the Excel file for more information) Small-compound databases contain a large amount of information for metabolites and metabolic pathways. However, the plethora of such databases and the redundancy of their information lead to major i…
description: The dataset includes a PDF file containing the results and an Excel file with the following tables: Table S1 Results of comparing the performance of MetaFetcheR to MetaboAnalystR using Diamanti et al. Table S2 Results of comparing the performance of MetaFetcheR to MetaboAnalystR for Priolo et al. Table S3 Results of comparing the performance of MetaFetcheR to MetaboAnalyst 5.0 webtool using Diamanti et al. Table S4 Results of comparing the performance of MetaFetcheR to MetaboAnalyst 5.0 webtool for Priolo et al. Table S5 Data quality test results for running 100 iterations on HMDB database. Table S6 Data quality test results for running 100 iterations on KEGG database. Table S7 Data quality test results for running 100 iterations on ChEBI database. Table S8 Data quality test results for running 100 iterations on PubChem database. Table S9 Data quality test results for running 100 iterations on LIPID MAPS database. Table S10 The list of metabolites that were not mapped by MetaboAnalystR for Diamanti et al. Table S11 An example of an input matrix for MetaFetcheR. Table S12 Results of comparing the performance of MetaFetcheR to MS_targeted using Diamanti et al. Table S13 Data set from Diamanti et al. Table S14 Data set from Priolo et al. Table S15 Results of comparing the performance of MetaFetcheR to CTS using KEGG identifiers available in Diamanti et al. Table S16 Results of comparing the performance of MetaFetcheR to CTS using LIPID MAPS identifiers available in Diamanti et al. Table S17 Results of comparing the performance of MetaFetcheR to CTS using KEGG identifiers available in Priolo et al. Table S18 Results of comparing the performance of MetaFetcheR to CTS using KEGG identifiers available in Priolo et al. Se engelsk beskrivning för mer information. Datasetet har ursprungligen publicerats i DiVA och flyttades över till SND 2024. @sv
modified: 2024-06-24T12:29:19.36867Z
issued: 2021-10-07T00:00:00Z
publisher: Uppsala University
access rights: PUBLIC
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Sara A. Yones
    type: Agent
    type: PrivateIndividual(s)
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Rajmund Csombordi
    type: Agent
    type: PrivateIndividual(s)
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Jan Komorowski
    type: Agent
    account: https://orcid.org/0000-0002-0766-8789
    type: PrivateIndividual(s)
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Klev Diamanti
    type: Agent
    account: https://orcid.org/0000-0002-4922-8415
    type: PrivateIndividual(s)
keyword: cell biology
keyword: cellbiologi @sv
keyword: molecular biology
keyword: molekylärbiologi @sv
keyword: data
language: ENG

Landing page for the dataset
type: Distribution
title: Landningssida för datasetet @sv
access URL: Supplementary tables:MetaFetcheR: An R package for complete mapping of small compound data
availability: stable

Uppsala University
type: Agent
name: Uppsala universitet @sv
type: Academia-ScientificOrganisation
source: https://ror.org/048a87296