{"title":"小世界的大数据:微生物研究数据库和资源综述","authors":"Pratyay Sengupta, Shobhan Karthick Muthamilselvi Sivabalan, Amrita Mahesh, Indumathi Palanikumar, Dinesh Kumar Kuppa Baskaran, Karthik Raman","doi":"10.1007/s41745-023-00370-z","DOIUrl":null,"url":null,"abstract":"<div><p>Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.</p></div>","PeriodicalId":675,"journal":{"name":"Journal of the Indian Institute of Science","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Big Data for a Small World: A Review on Databases and Resources for Studying Microbiomes\",\"authors\":\"Pratyay Sengupta, Shobhan Karthick Muthamilselvi Sivabalan, Amrita Mahesh, Indumathi Palanikumar, Dinesh Kumar Kuppa Baskaran, Karthik Raman\",\"doi\":\"10.1007/s41745-023-00370-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.</p></div>\",\"PeriodicalId\":675,\"journal\":{\"name\":\"Journal of the Indian Institute of Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2023-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Indian Institute of Science\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s41745-023-00370-z\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Indian Institute of Science","FirstCategoryId":"103","ListUrlMain":"https://link.springer.com/article/10.1007/s41745-023-00370-z","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Big Data for a Small World: A Review on Databases and Resources for Studying Microbiomes
Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.
期刊介绍:
Started in 1914 as the second scientific journal to be published from India, the Journal of the Indian Institute of Science became a multidisciplinary reviews journal covering all disciplines of science, engineering and technology in 2007. Since then each issue is devoted to a specific topic of contemporary research interest and guest-edited by eminent researchers. Authors selected by the Guest Editor(s) and/or the Editorial Board are invited to submit their review articles; each issue is expected to serve as a state-of-the-art review of a topic from multiple viewpoints.