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kegg compounds  (IROA Technologies LLC)


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    Structured Review

    IROA Technologies LLC kegg compounds
    Effect of varying ppm error thresholds on peak assignments: Number of a monoisotopic and b fine-structure peak matches for peak lists from two technical replicates of a diatom sample (testdata1.asc and testdata1.asc) containing naturally abundant metabolites (blue/light blue bars) with a 13 <t>C-labeled</t> <t>IROA-IS</t> spike-in (orange/pink bars), when compared with a list of 8,529 unique chemical formulas for 16,089 distinct <t>KEGG</t> compounds ranging between 40–1000 Daltons. Comparisons were performed across a range of error thresholds against the theoretical masses of metabolites with either natural isotopic abundance (nat_nist) or 95 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} 13 C-labeling (C13_95). a ) Number of distinct molecular features (monoisotopic masses) identified at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Average number of minor isotopic variants detected per matched chemical formula at a -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm
    Kegg Compounds, supplied by IROA Technologies LLC, used in various techniques. Bioz Stars score: 94/100, based on 16 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/kegg compounds/product/IROA Technologies LLC
    Average 94 stars, based on 16 article reviews
    kegg compounds - by Bioz Stars, 2026-02
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    1) Product Images from "MIMI: Molecular Isotope Mass Identifier for stable isotope-labeled Fourier transform ultra-high mass resolution data analysis"

    Article Title: MIMI: Molecular Isotope Mass Identifier for stable isotope-labeled Fourier transform ultra-high mass resolution data analysis

    Journal: BMC Bioinformatics

    doi: 10.1186/s12859-025-06348-1

    Effect of varying ppm error thresholds on peak assignments: Number of a monoisotopic and b fine-structure peak matches for peak lists from two technical replicates of a diatom sample (testdata1.asc and testdata1.asc) containing naturally abundant metabolites (blue/light blue bars) with a 13 C-labeled IROA-IS spike-in (orange/pink bars), when compared with a list of 8,529 unique chemical formulas for 16,089 distinct KEGG compounds ranging between 40–1000 Daltons. Comparisons were performed across a range of error thresholds against the theoretical masses of metabolites with either natural isotopic abundance (nat_nist) or 95 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} 13 C-labeling (C13_95). a ) Number of distinct molecular features (monoisotopic masses) identified at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Average number of minor isotopic variants detected per matched chemical formula at a -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm
    Figure Legend Snippet: Effect of varying ppm error thresholds on peak assignments: Number of a monoisotopic and b fine-structure peak matches for peak lists from two technical replicates of a diatom sample (testdata1.asc and testdata1.asc) containing naturally abundant metabolites (blue/light blue bars) with a 13 C-labeled IROA-IS spike-in (orange/pink bars), when compared with a list of 8,529 unique chemical formulas for 16,089 distinct KEGG compounds ranging between 40–1000 Daltons. Comparisons were performed across a range of error thresholds against the theoretical masses of metabolites with either natural isotopic abundance (nat_nist) or 95 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} 13 C-labeling (C13_95). a ) Number of distinct molecular features (monoisotopic masses) identified at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Average number of minor isotopic variants detected per matched chemical formula at a -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm

    Techniques Used: Labeling

    Validation rates of chemical formula assignments for monoisotopic masses using relative peak heights of minor isotopic variants : Number of unique CFs with monoisotopic matches (light bars), minor isotope variant matches (medium bars), and validated formulas (dark bars) for two sample types when compared with KEGG compounds between 40–1000 Daltons. The nitrogen-containing IROA metabolite standards dataset (orange) contains 274 unique chemical formulas. The diatom sample (blue; testdata1) contains a mixture of natural and 95% 13 C-labeled isotopes. Comparisons were performed across a range of ppm error thresholds using MIMI’s --iso-validation option with a 30% tolerance for isotopic fine-structure peak height matching. a ) Number of unique CFs detected at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Number of unique CFs detected at -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm.
    Figure Legend Snippet: Validation rates of chemical formula assignments for monoisotopic masses using relative peak heights of minor isotopic variants : Number of unique CFs with monoisotopic matches (light bars), minor isotope variant matches (medium bars), and validated formulas (dark bars) for two sample types when compared with KEGG compounds between 40–1000 Daltons. The nitrogen-containing IROA metabolite standards dataset (orange) contains 274 unique chemical formulas. The diatom sample (blue; testdata1) contains a mixture of natural and 95% 13 C-labeled isotopes. Comparisons were performed across a range of ppm error thresholds using MIMI’s --iso-validation option with a 30% tolerance for isotopic fine-structure peak height matching. a ) Number of unique CFs detected at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Number of unique CFs detected at -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm.

    Techniques Used: Biomarker Discovery, Variant Assay, Labeling



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    Effect of varying ppm error thresholds on peak assignments: Number of a monoisotopic and b fine-structure peak matches for peak lists from two technical replicates of a diatom sample (testdata1.asc and testdata1.asc) containing naturally abundant metabolites (blue/light blue bars) with a 13 <t>C-labeled</t> <t>IROA-IS</t> spike-in (orange/pink bars), when compared with a list of 8,529 unique chemical formulas for 16,089 distinct <t>KEGG</t> compounds ranging between 40–1000 Daltons. Comparisons were performed across a range of error thresholds against the theoretical masses of metabolites with either natural isotopic abundance (nat_nist) or 95 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} 13 C-labeling (C13_95). a ) Number of distinct molecular features (monoisotopic masses) identified at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Average number of minor isotopic variants detected per matched chemical formula at a -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm
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    Image Search Results


    Effect of varying ppm error thresholds on peak assignments: Number of a monoisotopic and b fine-structure peak matches for peak lists from two technical replicates of a diatom sample (testdata1.asc and testdata1.asc) containing naturally abundant metabolites (blue/light blue bars) with a 13 C-labeled IROA-IS spike-in (orange/pink bars), when compared with a list of 8,529 unique chemical formulas for 16,089 distinct KEGG compounds ranging between 40–1000 Daltons. Comparisons were performed across a range of error thresholds against the theoretical masses of metabolites with either natural isotopic abundance (nat_nist) or 95 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} 13 C-labeling (C13_95). a ) Number of distinct molecular features (monoisotopic masses) identified at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Average number of minor isotopic variants detected per matched chemical formula at a -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm

    Journal: BMC Bioinformatics

    Article Title: MIMI: Molecular Isotope Mass Identifier for stable isotope-labeled Fourier transform ultra-high mass resolution data analysis

    doi: 10.1186/s12859-025-06348-1

    Figure Lengend Snippet: Effect of varying ppm error thresholds on peak assignments: Number of a monoisotopic and b fine-structure peak matches for peak lists from two technical replicates of a diatom sample (testdata1.asc and testdata1.asc) containing naturally abundant metabolites (blue/light blue bars) with a 13 C-labeled IROA-IS spike-in (orange/pink bars), when compared with a list of 8,529 unique chemical formulas for 16,089 distinct KEGG compounds ranging between 40–1000 Daltons. Comparisons were performed across a range of error thresholds against the theoretical masses of metabolites with either natural isotopic abundance (nat_nist) or 95 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} 13 C-labeling (C13_95). a ) Number of distinct molecular features (monoisotopic masses) identified at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Average number of minor isotopic variants detected per matched chemical formula at a -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm

    Article Snippet: The expected 13 C-labeled IROA-IS spike-in composition of around 500-1000 KEGG compounds (https://www.iroatech.com/wp-content/uploads/2022/02/TruQuant-Yeast-Extract-QC-Workflow-Kit-USER-MANUAL_022022.pdf) [ ] also compares well with the 618 and 1140 matched features at 0.5 and 1 ppm, respectively.

    Techniques: Labeling

    Validation rates of chemical formula assignments for monoisotopic masses using relative peak heights of minor isotopic variants : Number of unique CFs with monoisotopic matches (light bars), minor isotope variant matches (medium bars), and validated formulas (dark bars) for two sample types when compared with KEGG compounds between 40–1000 Daltons. The nitrogen-containing IROA metabolite standards dataset (orange) contains 274 unique chemical formulas. The diatom sample (blue; testdata1) contains a mixture of natural and 95% 13 C-labeled isotopes. Comparisons were performed across a range of ppm error thresholds using MIMI’s --iso-validation option with a 30% tolerance for isotopic fine-structure peak height matching. a ) Number of unique CFs detected at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Number of unique CFs detected at -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm.

    Journal: BMC Bioinformatics

    Article Title: MIMI: Molecular Isotope Mass Identifier for stable isotope-labeled Fourier transform ultra-high mass resolution data analysis

    doi: 10.1186/s12859-025-06348-1

    Figure Lengend Snippet: Validation rates of chemical formula assignments for monoisotopic masses using relative peak heights of minor isotopic variants : Number of unique CFs with monoisotopic matches (light bars), minor isotope variant matches (medium bars), and validated formulas (dark bars) for two sample types when compared with KEGG compounds between 40–1000 Daltons. The nitrogen-containing IROA metabolite standards dataset (orange) contains 274 unique chemical formulas. The diatom sample (blue; testdata1) contains a mixture of natural and 95% 13 C-labeled isotopes. Comparisons were performed across a range of ppm error thresholds using MIMI’s --iso-validation option with a 30% tolerance for isotopic fine-structure peak height matching. a ) Number of unique CFs detected at varying -p settings of 0.1, 0.5, 1 ppm, with -vp held constant at 0.5 ppm. b ) Number of unique CFs detected at -p setting of 0.5 and varying -vp values of 0.1, 0.5, 1 ppm.

    Article Snippet: The expected 13 C-labeled IROA-IS spike-in composition of around 500-1000 KEGG compounds (https://www.iroatech.com/wp-content/uploads/2022/02/TruQuant-Yeast-Extract-QC-Workflow-Kit-USER-MANUAL_022022.pdf) [ ] also compares well with the 618 and 1140 matched features at 0.5 and 1 ppm, respectively.

    Techniques: Biomarker Discovery, Variant Assay, Labeling

    Summary of published machine learning-based models for predicting CYP450s – substrates/inhibitors interactions.

    Journal: Computational and Structural Biotechnology Journal

    Article Title: Investigation of in silico studies for cytochrome P450 isoforms specificity

    doi: 10.1016/j.csbj.2024.08.002

    Figure Lengend Snippet: Summary of published machine learning-based models for predicting CYP450s – substrates/inhibitors interactions.

    Article Snippet: CypReact , Learning based model , Physicochemical and structure descriptors , 1632 compounds from Human Metabolome Database, KEGG, DrugBank, PubChem, literature , 1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4 (substrates) , 2018 , .

    Techniques: