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An Overview of Databases and Tools for lncRNA Genomics Advancing Precision Medicine

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Machine Learning and Systems Biology in Genomics and Health

Abstract

The completion of the human genome project revealed many elusive questions about the “junk DNA” in the genome. One of the promising observations was the pervasive transcription and discovery of noncoding RNAs, which put aside the assumption of RNA as a mere messenger in the central dogma of molecular biology. It became evident that RNA plays more critical regulatory roles than simply being the genetic information carrier. The advancements in the next-generation sequencing methods in the last decade identified large numbers of long noncoding RNAs (lncRNAs) expressed during different conditions and performing diverse functions. Despite the rapidly growing advancements in various omics techniques to identify, annotate, and analyze the role of lncRNAs during different diseases, their molecular functions are still unexplored. To keep the pace of rapidly growing data and utilize them in novel lncRNA prediction, numerous computational repositories and predictive algorithms have been published in order to expand our horizons of the understanding and functions of lncRNAs. In this chapter, we described the current tools and computational repositories in the area of lncRNA biology covering numerous aspects like lncRNA identification, annotation, role in disease- or cell-type-specific expression, and detailed literature on their recent novel offbeat functions.

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  1. Amarinder Singh Thind, Karambir Kaur and Isha Monga contributed equally with all other contributors.

Authors and Affiliations

  1. School of Medicine, University of Wollongong, Wollongong, NSW, Australia

    Amarinder Singh Thind

  2. llawarra Health & Medical Research Institute, Wollongong, NSW, Australia

    Amarinder Singh Thind

  3. National Agri-Food Biotechnology Institute (NABI), Department of Biotechnology, Ministry of Science and Technology (Government of India), Mohali, Punjab, India

    Karambir Kaur

  4. Department of Dermatology, Columbia University Medical Center (CUMC), New York, NY, USA

    Isha Monga

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  1. Amarinder Singh Thind
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  2. Karambir Kaur
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  3. Isha Monga
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Correspondence to Amarinder Singh Thind .

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  1. Department of Pathogenesis and Cellular Response, National Centre for Cell Science, Pune, Maharashtra, India

    Shailza Singh

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Thind, A.S., Kaur, K., Monga, I. (2022). An Overview of Databases and Tools for lncRNA Genomics Advancing Precision Medicine. In: Singh, S. (eds) Machine Learning and Systems Biology in Genomics and Health. Springer, Singapore. https://doi.org/10.1007/978-981-16-5993-5_3

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