S. Uchida, Rebecca Distefano, Mirolyuba Ilieva, Sarah Rennie
{"title":"LncRNA研究中的生物信息学工具建议","authors":"S. Uchida, Rebecca Distefano, Mirolyuba Ilieva, Sarah Rennie","doi":"10.2174/1574893618666230707103956","DOIUrl":null,"url":null,"abstract":"\n\nLong non-coding RNAs (lncRNAs) typically refer to non-protein coding RNAs that are longer than 200 nucleotides. Historically dismissed as junk DNA, over two decades of research have revealed that lncRNAs bind to other macromolecules (e.g., DNA, RNA, and/or proteins) to modulate signaling pathways and maintain organism viability. Their discovery has been significantly aided by the development of bioinformatics tools in recent years. However, the diversity of tools for lncRNA discovery and functional prediction can confuse researchers, especially bench scientists and clinicians. This Perspective article aims to navigate the current landscape of bioinformatic tools suitable for both protein-coding and lncRNA genes. It aims to provide a guide for bench scientists and clinicians to select the appropriate tools for their research questions and experimental designs.\n","PeriodicalId":10801,"journal":{"name":"Current Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recommendations for Bioinformatic Tools in LncRNA Research\",\"authors\":\"S. Uchida, Rebecca Distefano, Mirolyuba Ilieva, Sarah Rennie\",\"doi\":\"10.2174/1574893618666230707103956\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n\\nLong non-coding RNAs (lncRNAs) typically refer to non-protein coding RNAs that are longer than 200 nucleotides. Historically dismissed as junk DNA, over two decades of research have revealed that lncRNAs bind to other macromolecules (e.g., DNA, RNA, and/or proteins) to modulate signaling pathways and maintain organism viability. Their discovery has been significantly aided by the development of bioinformatics tools in recent years. However, the diversity of tools for lncRNA discovery and functional prediction can confuse researchers, especially bench scientists and clinicians. This Perspective article aims to navigate the current landscape of bioinformatic tools suitable for both protein-coding and lncRNA genes. It aims to provide a guide for bench scientists and clinicians to select the appropriate tools for their research questions and experimental designs.\\n\",\"PeriodicalId\":10801,\"journal\":{\"name\":\"Current Bioinformatics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.2174/1574893618666230707103956\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.2174/1574893618666230707103956","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Recommendations for Bioinformatic Tools in LncRNA Research
Long non-coding RNAs (lncRNAs) typically refer to non-protein coding RNAs that are longer than 200 nucleotides. Historically dismissed as junk DNA, over two decades of research have revealed that lncRNAs bind to other macromolecules (e.g., DNA, RNA, and/or proteins) to modulate signaling pathways and maintain organism viability. Their discovery has been significantly aided by the development of bioinformatics tools in recent years. However, the diversity of tools for lncRNA discovery and functional prediction can confuse researchers, especially bench scientists and clinicians. This Perspective article aims to navigate the current landscape of bioinformatic tools suitable for both protein-coding and lncRNA genes. It aims to provide a guide for bench scientists and clinicians to select the appropriate tools for their research questions and experimental designs.
期刊介绍:
Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth/mini-reviews, research papers and guest edited thematic issues written by leaders in the field, covering a wide range of the integration of biology with computer and information science.
The journal focuses on advances in computational molecular/structural biology, encompassing areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Developments in these fields have direct implications on key issues related to health care, medicine, genetic disorders, development of agricultural products, renewable energy, environmental protection, etc.