MACC : a visual interactive knowledgebase of metabolite-associated cell communications
© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research..
Metabolite-associated cell communications play critical roles in maintaining the normal biological function of human through coordinating cells, organs and physiological systems. Though substantial information of MACCs has been continuously reported, no relevant database has become available so far. To address this gap, we here developed the first knowledgebase (MACC), to comprehensively describe human metabolite-associated cell communications through curation of experimental literatures. MACC currently contains: (a) 4206 carefully curated metabolite-associated cell communications pairs involving 244 human endogenous metabolites and reported biological effects in vivo and in vitro; (b) 226 comprehensive cell subtypes and 296 disease states, such as cancers, autoimmune diseases, and pathogenic infections; (c) 4508 metabolite-related enzymes and transporters, involving 542 pathways; (d) an interactive tool with user-friendly interface to visualize networks of multiple metabolite-cell interactions. (e) overall expression landscape of metabolite-associated gene sets derived from over 1500 single-cell expression profiles to infer metabolites variations across different cells in the sample. Also, MACC enables cross-links to well-known databases, such as HMDB, DrugBank, TTD and PubMed etc. In complement to ligand-receptor databases, MACC may give new perspectives of alternative communication between cells via metabolite secretion and adsorption, together with the resulting biological functions. MACC is publicly accessible at: http://macc.badd-cao.net/.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:52 |
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| Enthalten in: |
Nucleic acids research - 52(2024), D1 vom: 05. Jan., Seite D633-D639 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Gao, Jian [VerfasserIn] |
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| Anmerkungen: |
Date Completed 31.01.2024 Date Revised 31.01.2024 published: Print Citation Status MEDLINE |
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| doi: |
10.1093/nar/gkad914 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM363893792 |
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| 520 | |a © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. | ||
| 520 | |a Metabolite-associated cell communications play critical roles in maintaining the normal biological function of human through coordinating cells, organs and physiological systems. Though substantial information of MACCs has been continuously reported, no relevant database has become available so far. To address this gap, we here developed the first knowledgebase (MACC), to comprehensively describe human metabolite-associated cell communications through curation of experimental literatures. MACC currently contains: (a) 4206 carefully curated metabolite-associated cell communications pairs involving 244 human endogenous metabolites and reported biological effects in vivo and in vitro; (b) 226 comprehensive cell subtypes and 296 disease states, such as cancers, autoimmune diseases, and pathogenic infections; (c) 4508 metabolite-related enzymes and transporters, involving 542 pathways; (d) an interactive tool with user-friendly interface to visualize networks of multiple metabolite-cell interactions. (e) overall expression landscape of metabolite-associated gene sets derived from over 1500 single-cell expression profiles to infer metabolites variations across different cells in the sample. Also, MACC enables cross-links to well-known databases, such as HMDB, DrugBank, TTD and PubMed etc. In complement to ligand-receptor databases, MACC may give new perspectives of alternative communication between cells via metabolite secretion and adsorption, together with the resulting biological functions. MACC is publicly accessible at: http://macc.badd-cao.net/ | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Mo, Saifeng |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Jun |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Mou |e verfasserin |4 aut | |
| 700 | 1 | |a Shi, Yao |e verfasserin |4 aut | |
| 700 | 1 | |a Zhu, Chuhan |e verfasserin |4 aut | |
| 700 | 1 | |a Shang, Yuxuan |e verfasserin |4 aut | |
| 700 | 1 | |a Tang, Xinyue |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Shiyue |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Xinwen |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Xinyan |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yiheng |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Zihao |e verfasserin |4 aut | |
| 700 | 1 | |a Zheng, Genhui |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Zikun |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Qiming |e verfasserin |4 aut | |
| 700 | 1 | |a Tang, Kailin |e verfasserin |4 aut | |
| 700 | 1 | |a Cao, Zhiwei |e verfasserin |4 aut | |
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